@hasaki-ui/hsk-garen@1.3.4
Vulnerabilities |
54 via 117 paths |
---|---|
Dependencies |
1133 |
Source |
npm |
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high severity
- Vulnerable module: ajv
- Introduced through: extract-text-webpack-plugin@3.0.2
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › extract-text-webpack-plugin@3.0.2 › schema-utils@0.3.0 › ajv@5.5.2
Overview
ajv is an Another JSON Schema Validator
Affected versions of this package are vulnerable to Prototype Pollution. A carefully crafted JSON schema could be provided that allows execution of other code by prototype pollution. (While untrusted schemas are recommended against, the worst case of an untrusted schema should be a denial of service, not execution of code.)
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade ajv
to version 6.12.3 or higher.
References
high severity
- Vulnerable module: diff
- Introduced through: mocha@4.1.0
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › mocha@4.1.0 › diff@3.3.1Remediation: Upgrade to mocha@5.0.3.
Overview
diff is a javascript text differencing implementation.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). This can cause an impact of about 10 seconds matching time for data 48K characters long.
Disclosure Timeline
- Feb 15th, 2018 - Initial Disclosure to package owner
- Feb 16th, 2018 - Initial Response from package owner
- Mar 5th, 2018 - Fix issued
- Mar 6th, 2018 - Vulnerability published
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade diff
to version 3.5.0 or higher.
References
high severity
- Vulnerable module: engine.io
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › engine.io@1.8.3Remediation: Upgrade to karma@6.0.0.
Overview
engine.io is a realtime engine behind Socket.IO. It provides the foundation of a bidirectional connection between client and server
Affected versions of this package are vulnerable to Denial of Service (DoS) via a POST request to the long polling transport.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade engine.io
to version 4.0.0 or higher.
References
high severity
- Vulnerable module: js-yaml
- Introduced through: css-loader@0.28.11
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › css-loader@0.28.11 › cssnano@3.10.0 › postcss-svgo@2.1.6 › svgo@0.7.2 › js-yaml@3.7.0Remediation: Upgrade to css-loader@1.0.0.
Overview
js-yaml is a human-friendly data serialization language.
Affected versions of this package are vulnerable to Arbitrary Code Execution. When an object with an executable toString()
property used as a map key, it will execute that function. This happens only for load()
, which should not be used with untrusted data anyway. safeLoad()
is not affected because it can't parse functions.
Remediation
Upgrade js-yaml
to version 3.13.1 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Command Injection via template
.
PoC
var _ = require('lodash');
_.template('', { variable: '){console.log(process.env)}; with(obj' })()
Remediation
Upgrade lodash
to version 4.17.21 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The function defaultsDeep
could be tricked into adding or modifying properties of Object.prototype
using a constructor
payload.
PoC by Snyk
const mergeFn = require('lodash').defaultsDeep;
const payload = '{"constructor": {"prototype": {"a0": true}}}'
function check() {
mergeFn({}, JSON.parse(payload));
if (({})[`a0`] === true) {
console.log(`Vulnerable to Prototype Pollution via ${payload}`);
}
}
check();
For more information, check out our blog post
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.12 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution in zipObjectDeep
due to an incomplete fix for CVE-2020-8203.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.20 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution via the setWith
and set
functions.
PoC by awarau
- Create a JS file with this contents:
lod = require('lodash') lod.setWith({}, "__proto__[test]", "123") lod.set({}, "__proto__[test2]", "456") console.log(Object.prototype)
- Execute it with
node
- Observe that
test
andtest2
is now in theObject.prototype
.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.17 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The functions merge
, mergeWith
, and defaultsDeep
could be tricked into adding or modifying properties of Object.prototype
. This is due to an incomplete fix to CVE-2018-3721
.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.11 or higher.
References
high severity
- Vulnerable module: mocha
- Introduced through: mocha@4.1.0
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › mocha@4.1.0Remediation: Upgrade to mocha@6.0.0.
Overview
mocha is a javascript test framework for node.js & the browser.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). If the stack trace in utils.js
begins with a large error message (>= 20k characters), and full-trace
is not undisabled, utils.stackTraceFilter()
will take exponential time to run.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade mocha
to version 6.0.0 or higher.
References
high severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to NULL Pointer Dereference in the function Sass::Functions::selector_append
which could be leveraged by an attacker to cause a denial of service (application crash) or possibly have unspecified other impact. node-sass
is affected by this vulnerability due to its bundled usage of libsass
.
Remediation
There is no fixed version for node-sass
.
References
high severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Out-of-bounds Read via the function Sass::Prelexer::exactly()
which could be leveraged by an attacker to disclose information or manipulated to read from unmapped memory causing a denial of service. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
high severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Out-of-bounds Read via the function Sass::handle_error
which could be leveraged by an attacker to disclose information or manipulated to read from unmapped memory causing a denial of service. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
high severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Use After Free via the SharedPtr
class in SharedPtr.cpp
(or SharedPtr.hpp
) that may cause a denial of service (application crash) or possibly have unspecified other impact. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
high severity
- Vulnerable module: parsejson
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › engine.io-client@1.8.3 › parsejson@0.0.3
Overview
parsejson is a method that parses a JSON string and returns a JSON object.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks. An attacker may pass a specially crafted JSON data, causing the server to hang.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
There is no fixed version for parsejson
.
References
high severity
- Vulnerable module: serialize-javascript
- Introduced through: compression-webpack-plugin@1.1.12 and copy-webpack-plugin@4.6.0
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › compression-webpack-plugin@1.1.12 › serialize-javascript@1.9.1Remediation: Upgrade to compression-webpack-plugin@4.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › copy-webpack-plugin@4.6.0 › serialize-javascript@1.9.1Remediation: Upgrade to copy-webpack-plugin@5.1.2.
Overview
serialize-javascript is a package to serialize JavaScript to a superset of JSON that includes regular expressions and functions.
Affected versions of this package are vulnerable to Arbitrary Code Injection. An object like {"foo": /1"/, "bar": "a\"@__R-<UID>-0__@"}
would be serialized as {"foo": /1"/, "bar": "a\/1"/}
, meaning an attacker could escape out of bar
if they controlled both foo
and bar
and were able to guess the value of <UID>
. UID is generated once on startup, is chosen using Math.random()
and has a keyspace of roughly 4 billion, so within the realm of an online attack.
PoC
eval('('+ serialize({"foo": /1" + console.log(1)/i, "bar": '"@__R-<UID>-0__@'}) + ')');
Remediation
Upgrade serialize-javascript
to version 3.1.0 or higher.
References
high severity
- Vulnerable module: serialize-javascript
- Introduced through: compression-webpack-plugin@1.1.12 and copy-webpack-plugin@4.6.0
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › compression-webpack-plugin@1.1.12 › serialize-javascript@1.9.1Remediation: Upgrade to compression-webpack-plugin@3.0.1.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › copy-webpack-plugin@4.6.0 › serialize-javascript@1.9.1Remediation: Upgrade to copy-webpack-plugin@5.0.5.
Overview
serialize-javascript is a package to serialize JavaScript to a superset of JSON that includes regular expressions and functions.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS). It does not properly sanitize against unsafe characters in serialized regular expressions. This vulnerability is not affected on Node.js environment since Node.js's implementation of RegExp.prototype.toString()
backslash-escapes all forward slashes in regular expressions.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade serialize-javascript
to version 2.1.1 or higher.
References
high severity
- Vulnerable module: socket.io-parser
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-parser@2.3.1Remediation: Upgrade to karma@5.0.8.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-adapter@0.5.0 › socket.io-parser@2.3.1
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › socket.io-parser@2.3.1Remediation: Upgrade to karma@5.0.8.
Overview
socket.io-parser is a socket.io protocol parser
Affected versions of this package are vulnerable to Denial of Service (DoS) via a large packet because a concatenation approach is used.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade socket.io-parser
to version 3.3.2, 3.4.1 or higher.
References
high severity
- Vulnerable module: ssri
- Introduced through: compression-webpack-plugin@1.1.12 and copy-webpack-plugin@4.6.0
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › compression-webpack-plugin@1.1.12 › cacache@10.0.4 › ssri@5.3.0Remediation: Upgrade to compression-webpack-plugin@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › copy-webpack-plugin@4.6.0 › cacache@10.0.4 › ssri@5.3.0Remediation: Upgrade to copy-webpack-plugin@5.0.0.
Overview
ssri is a Standard Subresource Integrity library -- parses, serializes, generates, and verifies integrity metadata according to the SRI spec.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). Malicious SRIs could take an extremely long time to process, leading to denial of service. This issue only affects consumers using the strict
option.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ssri
to version 8.0.1, 6.0.2 or higher.
References
high severity
new
- Vulnerable module: ssri
- Introduced through: compression-webpack-plugin@1.1.12 and copy-webpack-plugin@4.6.0
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › compression-webpack-plugin@1.1.12 › cacache@10.0.4 › ssri@5.3.0Remediation: Upgrade to compression-webpack-plugin@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › copy-webpack-plugin@4.6.0 › cacache@10.0.4 › ssri@5.3.0Remediation: Upgrade to copy-webpack-plugin@5.0.0.
Overview
ssri is a Standard Subresource Integrity library -- parses, serializes, generates, and verifies integrity metadata according to the SRI spec.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). ssri
processes SRIs using a regular expression which is vulnerable to a denial of service. Malicious SRIs could take an extremely long time to process, leading to denial of service. This issue only affects consumers using the strict option.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ssri
to version 6.0.2, 8.0.1 or higher.
References
high severity
- Vulnerable module: useragent
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › useragent@2.3.0
Overview
useragent allows you to parse user agent string with high accuracy by using hand tuned dedicated regular expressions for browser matching.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when passing long user-agent strings.
This is due to incomplete fix for this vulnerability: https://snyk.io/vuln/SNYK-JS-USERAGENT-11000.
An attempt to fix the vulnerability has been pushed to master.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
A fix was pushed into the master
branch but not yet published.
References
high severity
- Vulnerable module: ws
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › engine.io@1.8.3 › ws@1.1.2Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › engine.io-client@1.8.3 › ws@1.1.2Remediation: Upgrade to karma@2.0.0.
Overview
ws is a simple to use websocket client, server and console for node.js.
Affected versions of this package are vulnerable to Denial of Service (DoS)
attacks. A specially crafted value of the Sec-WebSocket-Extensions
header that used Object.prototype
property names as extension or parameter names could be used to make a ws server crash.
PoC:
const WebSocket = require('ws');
const net = require('net');
const wss = new WebSocket.Server({ port: 3000 }, function () {
const payload = 'constructor'; // or ',;constructor'
const request = [
'GET / HTTP/1.1',
'Connection: Upgrade',
'Sec-WebSocket-Key: test',
'Sec-WebSocket-Version: 8',
`Sec-WebSocket-Extensions: ${payload}`,
'Upgrade: websocket',
'\r\n'
].join('\r\n');
const socket = net.connect(3000, function () {
socket.resume();
socket.write(request);
});
});
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade ws
to version 1.1.5, 3.3.1 or higher.
References
high severity
- Vulnerable module: xmlhttprequest-ssl
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › engine.io-client@1.8.3 › xmlhttprequest-ssl@1.5.3
Overview
xmlhttprequest-ssl is a fork of xmlhttprequest
.
Affected versions of this package are vulnerable to Arbitrary Code Injection. Provided requests are sent synchronously (async=False
on xhr.open
), malicious user input flowing into xhr.send
could result in arbitrary code being injected and run.
POC
const { XMLHttpRequest } = require("xmlhttprequest")
const xhr = new XMLHttpRequest()
xhr.open("POST", "http://localhost.invalid/", false /* use synchronize request */)
xhr.send("\\');require(\"fs\").writeFileSync(\"/tmp/aaaaa.txt\", \"poc-20210306\");req.end();//")
Remediation
There is no fixed version for xmlhttprequest-ssl
.
References
medium severity
- Vulnerable module: color-string
- Introduced through: css-loader@0.28.11
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › css-loader@0.28.11 › cssnano@3.10.0 › postcss-colormin@2.2.2 › colormin@1.1.2 › color@0.11.4 › color-string@0.3.0
Overview
color-string is a Parser and generator for CSS color strings
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the hwb
regular expression in the cs.get.hwb
function in index.js. The affected regular expression exhibits quadratic worst-case time complexity.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade color-string
to version 1.5.5 or higher.
References
medium severity
- Vulnerable module: ejs
- Introduced through: webpack-bundle-analyzer@2.13.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › webpack-bundle-analyzer@2.13.1 › ejs@2.7.4Remediation: Upgrade to webpack-bundle-analyzer@4.0.0.
Overview
ejs is a popular JavaScript templating engine.
Affected versions of this package are vulnerable to Arbitrary Code Injection via the render
and renderFile
. If external input is flowing into the options
parameter, an attacker is able run arbitrary code. This include the filename
, compileDebug
, and client
option.
POC
let ejs = require('ejs')
ejs.render('./views/test.ejs',{
filename:'/etc/passwd\nfinally { this.global.process.mainModule.require(\'child_process\').execSync(\'touch EJS_HACKED\') }',
compileDebug: true,
message: 'test',
client: true
})
Remediation
Upgrade ejs
to version 3.1.6 or higher.
References
medium severity
- Vulnerable module: glob-parent
- Introduced through: karma@1.7.1, anymatch@1.3.2 and others
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › chokidar@1.7.0 › glob-parent@2.0.0Remediation: Upgrade to karma@4.2.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › anymatch@1.3.2 › micromatch@2.3.11 › parse-glob@3.0.4 › glob-base@0.3.0 › glob-parent@2.0.0
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › http-proxy-middleware@0.17.4 › micromatch@2.3.11 › parse-glob@3.0.4 › glob-base@0.3.0 › glob-parent@2.0.0
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › babel-plugin-istanbul@4.1.6 › test-exclude@4.2.3 › micromatch@2.3.11 › parse-glob@3.0.4 › glob-base@0.3.0 › glob-parent@2.0.0
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › chokidar@1.7.0 › anymatch@1.3.2 › micromatch@2.3.11 › parse-glob@3.0.4 › glob-base@0.3.0 › glob-parent@2.0.0
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › webpack@3.12.0 › watchpack@1.7.5 › watchpack-chokidar2@2.0.1 › chokidar@2.1.8 › glob-parent@3.1.0
Overview
glob-parent is a package that helps extracting the non-magic parent path from a glob string.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The enclosure
regex used to check for strings ending in enclosure containing path separator.
PoC by Yeting Li
var globParent = require("glob-parent")
function build_attack(n) {
var ret = "{"
for (var i = 0; i < n; i++) {
ret += "/"
}
return ret;
}
globParent(build_attack(5000));
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade glob-parent
to version 5.1.2 or higher.
References
medium severity
- Vulnerable module: is-svg
- Introduced through: css-loader@0.28.11
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › css-loader@0.28.11 › cssnano@3.10.0 › postcss-svgo@2.1.6 › is-svg@2.1.0Remediation: Upgrade to css-loader@1.0.0.
Overview
is-svg is a Check if a string or buffer is SVG
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). If an attacker provides a malicious string, is-svg will get stuck processing the input for a very long time.
You are only affected if you use this package on a server that accepts SVG as user-input.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade is-svg
to version 4.2.2 or higher.
References
medium severity
- Vulnerable module: js-yaml
- Introduced through: css-loader@0.28.11
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › css-loader@0.28.11 › cssnano@3.10.0 › postcss-svgo@2.1.6 › svgo@0.7.2 › js-yaml@3.7.0Remediation: Upgrade to css-loader@1.0.0.
Overview
js-yaml is a human-friendly data serialization language.
Affected versions of this package are vulnerable to Denial of Service (DoS). The parsing of a specially crafted YAML file may exhaust the system resources.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade js-yaml
to version 3.13.0 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The function zipObjectDeep
can be tricked into adding or modifying properties of the Object prototype. These properties will be present on all objects.
PoC
const _ = require('lodash');
_.zipObjectDeep(['__proto__.z'],[123])
console.log(z) // 123
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.16 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var _= require('lodash');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
_.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.5 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the toNumber
, trim
and trimEnd
functions.
POC
var lo = require('lodash');
function build_blank (n) {
var ret = "1"
for (var i = 0; i < n; i++) {
ret += " "
}
return ret + "1";
}
var s = build_blank(50000)
var time0 = Date.now();
lo.trim(s)
var time_cost0 = Date.now() - time0;
console.log("time_cost0: " + time_cost0)
var time1 = Date.now();
lo.toNumber(s)
var time_cost1 = Date.now() - time1;
console.log("time_cost1: " + time_cost1)
var time2 = Date.now();
lo.trimEnd(s)
var time_cost2 = Date.now() - time2;
console.log("time_cost2: " + time_cost2)
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade lodash
to version 4.17.21 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › lodash@3.10.1Remediation: Upgrade to karma@2.0.0.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It parses dates using regex strings, which may cause a slowdown of 2 seconds per 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade lodash
to version 4.17.11 or higher.
References
medium severity
- Vulnerable module: mem
- Introduced through: webpack@3.12.0
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › webpack@3.12.0 › yargs@8.0.2 › os-locale@2.1.0 › mem@1.1.0Remediation: Upgrade to webpack@4.0.0.
Overview
mem is an optimization used to speed up consecutive function calls by caching the result of calls with identical input.
Affected versions of this package are vulnerable to Denial of Service (DoS). Old results were deleted from the cache and could cause a memory leak.
details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade mem to version 4.0.0 or higher.
References
medium severity
- Vulnerable module: minimist
- Introduced through: karma@1.7.1, karma-mocha@1.3.0 and others
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › optimist@0.6.1 › minimist@0.0.10
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma-mocha@1.3.0 › minimist@1.2.0Remediation: Upgrade to karma-mocha@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › mocha@4.1.0 › mkdirp@0.5.1 › minimist@0.0.8Remediation: Upgrade to mocha@6.2.3.
Overview
minimist is a parse argument options module.
Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype
using a constructor
or __proto__
payload.
PoC by Snyk
require('minimist')('--__proto__.injected0 value0'.split(' '));
console.log(({}).injected0 === 'value0'); // true
require('minimist')('--constructor.prototype.injected1 value1'.split(' '));
console.log(({}).injected1 === 'value1'); // true
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade minimist
to version 0.2.1, 1.2.3 or higher.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Denial of Service (DoS). Uncontrolled recursion is possible in Sass::Complex_Selector::perform
in ast.hpp
and Sass::Inspect::operator
in inspect.cpp
. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Denial of Service (DoS). The parsing component allows attackers to cause uncontrolled recursion in Sass::Parser::parse_css_variable_value
in parser.cpp. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Improper Certificate Validation. Certificate validation is disabled by default when requesting binaries, even if the user is not specifying an alternative download path.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to NULL Pointer Dereference. In LibSass 3.5.5, a NULL Pointer Dereference in the function Sass::Eval::operator()``(Sass::Supports_Operator*)
in eval.cpp
may cause a Denial of Service (application crash) via a crafted sass input file.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to NULL Pointer Dereference via Sass::Parser::parseCompoundSelector
in parser_selectors.cpp
. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to NULL Pointer Dereference. The function Sass::Selector_List::populate_extends
in SharedPtr.hpp
(used by ast.cpp
and ast_selectors.cpp
) may cause a Denial of Service (application crash) via a crafted sass input file. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Out-of-Bounds. A heap-based buffer over-read exists in Sass::Prelexer::parenthese_scope
in prelexer.hpp
. node-sass
is affected by this vulnerability due to its bundled usage of libsass
.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Out-of-Bounds via Sass::Prelexer::alternatives
in prelexer.hpp
. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Out-of-bounds Read via Sass::weaveParents
in ast_sel_weave.cpp
. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Out-of-bounds Read via Sass::Prelexer::skip_over_scopes
in prelexer.hpp
when called from Sass::Parser::parse_import()
, a similar issue to CVE-2018-11693. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Out-of-bounds Read. The function handle_error
in sass_context.cpp
allows attackers to cause a denial-of-service resulting from a heap-based buffer over-read via a crafted sass file. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
medium severity
- Vulnerable module: node-sass
- Introduced through: node-sass@4.14.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › node-sass@4.14.1
Overview
node-sass is a Node.js bindings package for libsass.
Affected versions of this package are vulnerable to Uncontrolled Recursion via Sass::Eval::operator()(Sass::Binary_Expression*)
in eval.cpp
. Note: node-sass
is affected by this vulnerability due to its bundled usage of the libsass
package.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
There is no fixed version for node-sass
.
References
medium severity
new
- Vulnerable module: postcss
- Introduced through: optimize-css-assets-webpack-plugin@3.2.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › css-declaration-sorter@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › cssnano-util-raw-cache@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-calc@7.0.5 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-colormin@4.0.3 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-convert-values@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-discard-comments@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-discard-duplicates@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-discard-empty@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-discard-overridden@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-merge-longhand@4.0.11 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-merge-rules@4.0.3 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-minify-font-values@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-minify-gradients@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-minify-params@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-minify-selectors@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-charset@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-display-values@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-positions@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-repeat-style@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-string@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-timing-functions@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-unicode@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-url@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-normalize-whitespace@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-ordered-values@4.1.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-reduce-initial@4.0.3 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-reduce-transforms@4.0.2 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-svgo@4.0.3 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-unique-selectors@4.0.1 › postcss@7.0.35
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › optimize-css-assets-webpack-plugin@3.2.1 › cssnano@4.1.11 › cssnano-preset-default@4.0.8 › postcss-merge-longhand@4.0.11 › stylehacks@4.0.3 › postcss@7.0.35
Overview
postcss is a PostCSS is a tool for transforming styles with JS plugins.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) during source map parsing.
PoC
var postcss = require("postcss")
function build_attack(n) {
var ret = "a{}/*# sourceMappingURL="
for (var i = 0; i < n; i++) {
ret += " "
}
return ret + "!";
}
// postcss.parse('a{}/*# sourceMappingURL=a.css.map */')
for(var i = 1; i <= 500000; i++) {
if (i % 10000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
try{
postcss.parse(attack_str)
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
}
catch(e){
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
}
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade postcss
to version 8.2.10 or higher.
References
medium severity
- Vulnerable module: socket.io
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3Remediation: Upgrade to karma@5.0.8.
Overview
socket.io is a node.js realtime framework server.
Affected versions of this package are vulnerable to Insecure Defaults due to CORS Misconfiguration. All domains are whitelisted by default.
Remediation
Upgrade socket.io
to version 2.4.0 or higher.
References
medium severity
- Vulnerable module: webpack-bundle-analyzer
- Introduced through: webpack-bundle-analyzer@2.13.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › webpack-bundle-analyzer@2.13.1Remediation: Upgrade to webpack-bundle-analyzer@3.3.2.
Overview
webpack-bundle-analyzer is a package that can be used to create visual size of webpack output files with an interactive zoomable treemap.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS)
due to the usage of the JSON.stringify
method which accepts server-rendered HTML and returns it as part of the chartData()
,enableWebSocket()
or defaultSizes()
function.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
ֿInjecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade webpack-bundle-analyzer
to version 3.3.2 or higher.
References
medium severity
- Vulnerable module: yargs-parser
- Introduced through: webpack@3.12.0
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › webpack@3.12.0 › yargs@8.0.2 › yargs-parser@7.0.0Remediation: Upgrade to webpack@4.0.0.
Overview
yargs-parser is a mighty option parser used by yargs.
Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype
using a __proto__
payload.
Our research team checked several attack vectors to verify this vulnerability:
- It could be used for privilege escalation.
- The library could be used to parse user input received from different sources:
- terminal emulators
- system calls from other code bases
- CLI RPC servers
PoC by Snyk
const parser = require("yargs-parser");
console.log(parser('--foo.__proto__.bar baz'));
console.log(({}).bar);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade yargs-parser
to version 5.0.0-security.0, 13.1.2, 15.0.1, 18.1.1 or higher.
References
low severity
- Vulnerable module: braces
- Introduced through: anymatch@1.3.2, http-proxy-middleware@0.17.4 and others
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › anymatch@1.3.2 › micromatch@2.3.11 › braces@1.8.5Remediation: Upgrade to anymatch@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › http-proxy-middleware@0.17.4 › micromatch@2.3.11 › braces@1.8.5Remediation: Upgrade to http-proxy-middleware@0.18.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › babel-plugin-istanbul@4.1.6 › test-exclude@4.2.3 › micromatch@2.3.11 › braces@1.8.5Remediation: Upgrade to babel-plugin-istanbul@5.0.1.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › chokidar@1.7.0 › anymatch@1.3.2 › micromatch@2.3.11 › braces@1.8.5Remediation: Upgrade to karma@2.0.3.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › expand-braces@0.1.2 › braces@0.1.5
Overview
braces is a Bash-like brace expansion, implemented in JavaScript.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\{(,+(?:(\{,+\})*),*|,*(?:(\{,+\})*),+)\}
) in order to detects empty braces. This can cause an impact of about 10 seconds matching time for data 50K characters long.
Disclosure Timeline
- Feb 15th, 2018 - Initial Disclosure to package owner
- Feb 16th, 2018 - Initial Response from package owner
- Feb 18th, 2018 - Fix issued
- Feb 19th, 2018 - Vulnerability published
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade braces
to version 2.3.1 or higher.
References
low severity
- Vulnerable module: debug
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › debug@2.3.3Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › engine.io@1.8.3 › debug@2.3.3Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-adapter@0.5.0 › debug@2.3.3Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › debug@2.3.3Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › engine.io-client@1.8.3 › debug@2.3.3Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-parser@2.3.1 › debug@2.2.0Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-adapter@0.5.0 › socket.io-parser@2.3.1 › debug@2.2.0Remediation: Open PR to patch debug@2.2.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › socket.io-parser@2.3.1 › debug@2.2.0Remediation: Upgrade to karma@2.0.0.
Overview
debug
is a JavaScript debugging utility modelled after Node.js core's debugging technique..
debug
uses printf-style formatting. Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks via the the %o
formatter (Pretty-print an Object all on a single line). It used a regular expression (/\s*\n\s*/g
) in order to strip whitespaces and replace newlines with spaces, in order to join the data into a single line. This can cause a very low impact of about 2 seconds matching time for data 50k characters long.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade debug
to version 2.6.9, 3.1.0 or higher.
References
low severity
- Vulnerable module: mime
- Introduced through: url-loader@0.5.9
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › url-loader@0.5.9 › mime@1.3.6Remediation: Upgrade to url-loader@0.6.0.
Overview
mime is a comprehensive, compact MIME type module.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It uses regex the following regex /.*[\.\/\\]/
in its lookup, which can cause a slowdown of 2 seconds for 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade mime
to version 1.4.1, 2.0.3 or higher.
References
low severity
- Vulnerable module: ms
- Introduced through: karma@1.7.1
Detailed paths
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › debug@2.3.3 › ms@0.7.2Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › engine.io@1.8.3 › debug@2.3.3 › ms@0.7.2Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-adapter@0.5.0 › debug@2.3.3 › ms@0.7.2Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › debug@2.3.3 › ms@0.7.2Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › engine.io-client@1.8.3 › debug@2.3.3 › ms@0.7.2Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-parser@2.3.1 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to karma@2.0.0.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-adapter@0.5.0 › socket.io-parser@2.3.1 › debug@2.2.0 › ms@0.7.1Remediation: Open PR to patch ms@0.7.1.
-
Introduced through: @hasaki-ui/hsk-garen@1.3.4 › karma@1.7.1 › socket.io@1.7.3 › socket.io-client@1.7.3 › socket.io-parser@2.3.1 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to karma@2.0.0.
Overview
ms
is a tiny millisecond conversion utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an incomplete fix for previously reported vulnerability npm:ms:20151024. The fix limited the length of accepted input string to 10,000 characters, and turned to be insufficient making it possible to block the event loop for 0.3 seconds (on a typical laptop) with a specially crafted string passed to ms()
function.
Proof of concept
ms = require('ms');
ms('1'.repeat(9998) + 'Q') // Takes about ~0.3s
Note: Snyk's patch for this vulnerability limits input length to 100 characters. This new limit was deemed to be a breaking change by the author. Based on user feedback, we believe the risk of breakage is very low, while the value to your security is much greater, and therefore opted to still capture this change in a patch for earlier versions as well. Whenever patching security issues, we always suggest to run tests on your code to validate that nothing has been broken.
For more information on Regular Expression Denial of Service (ReDoS)
attacks, go to our blog.
Disclosure Timeline
- Feb 9th, 2017 - Reported the issue to package owner.
- Feb 11th, 2017 - Issue acknowledged by package owner.
- April 12th, 2017 - Fix PR opened by Snyk Security Team.
- May 15th, 2017 - Vulnerability published.
- May 16th, 2017 - Issue fixed and version
2.0.0
released. - May 21th, 2017 - Patches released for versions
>=0.7.1, <=1.0.0
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ms
to version 2.0.0 or higher.