Vulnerabilities |
36 via 83 paths |
---|---|
Dependencies |
162 |
Source |
npm |
Find, fix and prevent vulnerabilities in your code.
high severity
- Vulnerable module: tar
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Write. node-tar
aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.
This logic was insufficient when extracting tar
files that contained both a directory and a symlink with the same name as the directory, where the symlink and directory names in the archive entry used backslashes as a path separator on posix systems. The cache checking logic used both \
and /
characters as path separators. However, \
is a valid filename character on posix systems.
By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar
symlink checks on directories, essentially allowing an untrusted tar
file to symlink into an arbitrary location. This can lead to extracting arbitrary files into that location, thus allowing arbitrary file creation and overwrite.
Additionally, a similar confusion could arise on case-insensitive filesystems. If a tar
archive contained a directory at FOO
, followed by a symbolic link named foo
, then on case-insensitive file systems, the creation of the symbolic link would remove the directory from the filesystem, but not from the internal directory cache, as it would not be treated as a cache hit. A subsequent file entry within the FOO
directory would then be placed in the target of the symbolic link, thinking that the directory had already been created.
Remediation
Upgrade tar
to version 6.1.7, 5.0.8, 4.4.16 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Write. node-tar
aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.
This logic is insufficient when extracting tar
files that contain two directories and a symlink with names containing unicode values that normalized to the same value. Additionally, on Windows systems, long path portions would resolve to the same file system entities as their 8.3 "short path" counterparts.
A specially crafted tar
archive can include directories with two forms of the path that resolve to the same file system entity, followed by a symbolic link with a name in the first form, lastly followed by a file using the second form. This leads to bypassing node-tar
symlink checks on directories, essentially allowing an untrusted tar
file to symlink into an arbitrary location and extracting arbitrary files into that location.
Remediation
Upgrade tar
to version 6.1.9, 5.0.10, 4.4.18 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Write. node-tar
aims to guarantee that any file whose location would be outside of the extraction target directory is not extracted. This is, in part, accomplished by sanitizing absolute paths of entries within the archive, skipping archive entries that contain ..
path portions, and resolving the sanitized paths against the extraction target directory.
This logic is insufficient on Windows systems when extracting tar
files that contain a path that is not an absolute path, but specify a drive letter different from the extraction target, such as C:some\path
. If the drive letter does not match the extraction target, for example D:\extraction\dir
, then the result of path.resolve(extractionDirectory, entryPath)
resolves against the current working directory on the C:
drive, rather than the extraction target directory.
Additionally, a ..
portion of the path can occur immediately after the drive letter, such as C:../foo
, and is not properly sanitized by the logic that checks for ..
within the normalized and split portions of the path.
Note: This only affects users of node-tar
on Windows systems.
Remediation
Upgrade tar
to version 6.1.9, 5.0.10, 4.4.18 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.23.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › lodash@2.4.2
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › lodash@2.1.0
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 4.17.20 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient symlink protection.
node-tar
aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat
calls to determine whether a given path is a directory, paths are cached when directories are created.
This logic is insufficient when extracting tar files that contain both a directory and a symlink with the same name as the directory. This order of operations results in the directory being created and added to the node-tar
directory cache. When a directory is present in the directory cache, subsequent calls to mkdir
for that directory are skipped.
However, this is also where node-tar
checks for symlinks occur. By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar
symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and subsequently extracting arbitrary files into that location.
Remediation
Upgrade tar
to version 3.2.3, 4.4.15, 5.0.7, 6.1.2 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient absolute path sanitization.
node-tar
aims to prevent extraction of absolute file paths by turning absolute paths into relative paths when the preservePaths
flag is not set to true
. This is achieved by stripping the absolute path root from any absolute file paths contained in a tar file. For example, the path /home/user/.bashrc
would turn into home/user/.bashrc
.
This logic is insufficient when file paths contain repeated path roots such as ////home/user/.bashrc
. node-tar
only strips a single path root from such paths. When given an absolute file path with repeating path roots, the resulting path (e.g. ///home/user/.bashrc
) still resolves to an absolute path.
Remediation
Upgrade tar
to version 3.2.2, 4.4.14, 5.0.6, 6.1.1 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Overwrite. Extracting tarballs containing a hard-link to a file that already exists in the system, and a file that matches the hard-link may overwrite system's files with the contents of the extracted file.
Remediation
Upgrade tar
to version 2.2.2, 4.4.2 or higher.
References
high severity
- Vulnerable module: async
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › async@0.2.10Remediation: Upgrade to yeoman-generator@0.24.1.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › async@0.2.10Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › form-data@0.1.4 › async@0.9.2Remediation: Upgrade to generator-zf5@0.7.3.
Overview
Affected versions of this package are vulnerable to Prototype Pollution via the mapValues()
method.
PoC
//when objects are parsed, all properties are created as own (the objects can come from outside sources (http requests/ file))
const hasOwn = JSON.parse('{"__proto__": {"isAdmin": true}}');
//does not have the property, because it's inside object's own "__proto__"
console.log(hasOwn.isAdmin);
async.mapValues(hasOwn, (val, key, cb) => cb(null, val), (error, result) => {
// after the method executes, hasOwn.__proto__ value (isAdmin: true) replaces the prototype of the newly created object, leading to potential exploits.
console.log(result.isAdmin);
});
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 async
to version 2.6.4, 3.2.2 or higher.
References
high severity
- Vulnerable module: minimatch
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › glob@3.2.11 › minimatch@0.3.0Remediation: Upgrade to generator-zf5@0.9.10.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › glob@3.2.11 › minimatch@0.3.0Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › glob@3.2.11 › minimatch@0.3.0
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › glob@3.2.11 › minimatch@0.3.0
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › minimatch@0.2.14
Overview
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via complicated and illegal regexes.
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 minimatch
to version 3.0.2 or higher.
References
high severity
- Vulnerable module: minimatch
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › glob@3.2.11 › minimatch@0.3.0Remediation: Upgrade to generator-zf5@0.9.10.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › glob@3.2.11 › minimatch@0.3.0Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › glob@3.2.11 › minimatch@0.3.0Remediation: Open PR to patch minimatch@0.3.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › glob@3.2.11 › minimatch@0.3.0Remediation: Open PR to patch minimatch@0.3.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › minimatch@0.2.14Remediation: Open PR to patch minimatch@0.2.14.
Overview
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS).
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 minimatch
to version 3.0.2 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › qs@0.6.6Remediation: Upgrade to generator-zf5@0.7.3.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Denial of Service (DoS).
During parsing, the qs
module may create a sparse area (an array where no elements are filled), and grow that array to the necessary size based on the indices used on it. An attacker can specify a high index value in a query string, thus making the server allocate a respectively big array. Truly large values can cause the server to run out of memory and cause it to crash - thus enabling a Denial-of-Service attack.
Remediation
Upgrade qs
to version 1.0.0 or higher.
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
References
high severity
- Vulnerable module: qs
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › qs@0.6.6Remediation: Upgrade to generator-zf5@0.7.3.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Prototype Override Protection Bypass. By default qs
protects against attacks that attempt to overwrite an object's existing prototype properties, such as toString()
, hasOwnProperty()
,etc.
From qs
documentation:
By default parameters that would overwrite properties on the object prototype are ignored, if you wish to keep the data from those fields either use plainObjects as mentioned above, or set allowPrototypes to true which will allow user input to overwrite those properties. WARNING It is generally a bad idea to enable this option as it can cause problems when attempting to use the properties that have been overwritten. Always be careful with this option.
Overwriting these properties can impact application logic, potentially allowing attackers to work around security controls, modify data, make the application unstable and more.
In versions of the package affected by this vulnerability, it is possible to circumvent this protection and overwrite prototype properties and functions by prefixing the name of the parameter with [
or ]
. e.g. qs.parse("]=toString")
will return {toString = true}
, as a result, calling toString()
on the object will throw an exception.
Example:
qs.parse('toString=foo', { allowPrototypes: false })
// {}
qs.parse("]=toString", { allowPrototypes: false })
// {toString = true} <== prototype overwritten
For more information, you can check out our blog.
Disclosure Timeline
- February 13th, 2017 - Reported the issue to package owner.
- February 13th, 2017 - Issue acknowledged by package owner.
- February 16th, 2017 - Partial fix released in versions
6.0.3
,6.1.1
,6.2.2
,6.3.1
. - March 6th, 2017 - Final fix released in versions
6.4.0
,6.3.2
,6.2.3
,6.1.2
and6.0.4
Remediation
Upgradeqs
to version 6.0.4, 6.1.2, 6.2.3, 6.3.2 or higher.References
- GitHub Commit
- GitHub Issue
high severity
- Vulnerable module: tar
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Symlink File Overwrite. It does not properly normalize symbolic links pointing to targets outside the extraction root. As a result, packages may hold symbolic links to parent and sibling directories and overwrite those files when the package is extracted.
Remediation
Upgrade tar
to version 2.0.0 or higher.
References
high severity
- Vulnerable module: tough-cookie
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › tough-cookie@0.9.15Remediation: Upgrade to generator-zf5@0.7.3.
Overview
tough-cookie is a RFC6265 Cookies and CookieJar module for Node.js.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). An attacker can provide a cookie, which nearly matches the pattern being matched. This will cause the regular expression matching to take a long time, all the while occupying the event loop and preventing it from processing other requests and making the server unavailable (a Denial of Service attack).
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 tough-cookie
to version 2.3.0 or higher.
References
high severity
- Vulnerable module: adm-zip
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › adm-zip@0.4.16Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
adm-zip is a JavaScript implementation for zip data compression for NodeJS.
Affected versions of this package are vulnerable to Directory Traversal. It could extract files outside the target folder.
Details
A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.
Directory Traversal vulnerabilities can be generally divided into two types:
- Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.
st
is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public
route.
If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.
curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa
Note %2e
is the URL encoded version of .
(dot).
- Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as
Zip-Slip
.
One way to achieve this is by using a malicious zip
archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.
The following is an example of a zip
archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/
overwriting the authorized_keys
file:
2018-04-15 22:04:29 ..... 19 19 good.txt
2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys
Remediation
Upgrade adm-zip
to version 0.5.2 or higher.
References
high severity
new
- Vulnerable module: hawk
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › hawk@1.0.0
Overview
hawk is a library for the HTTP Hawk Authentication Scheme.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in header parsing where each added character in the attacker's input increases the computation time exponentially.
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: fstream
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20 › fstream@0.1.31Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
fstream is a package that supports advanced FS Streaming for Node.
Affected versions of this package are vulnerable to Arbitrary File Overwrite. Extracting tarballs containing a hardlink to a file that already exists in the system and a file that matches the hardlink will overwrite the system's file with the contents of the extracted file.
Remediation
Upgrade fstream
to version 1.0.12 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.23.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › lodash@2.4.2
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › lodash@2.1.0
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: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.23.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › lodash@2.4.2
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › lodash@2.1.0
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: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.23.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › lodash@2.4.2
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › lodash@2.1.0
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: lodash
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.23.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › lodash@2.4.2
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › lodash@2.1.0
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: shelljs
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › shelljs@0.2.6Remediation: Upgrade to yeoman-generator@2.0.3.
Overview
shelljs is a wrapper for the Unix shell commands for Node.js.
Affected versions of this package are vulnerable to Improper Privilege Management. When ShellJS
is used to create shell scripts which may be running as root
, users with low-level privileges on the system can leak sensitive information such as passwords (depending on implementation) from the standard output of the privileged process OR shutdown privileged ShellJS
processes via the exec
function when triggering EACCESS errors.
Note: Thi only impacts the synchronous version of shell.exec()
.
Remediation
Upgrade shelljs
to version 0.8.5 or higher.
References
medium severity
- Vulnerable module: http-signature
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › http-signature@0.10.1Remediation: Upgrade to generator-zf5@0.7.3.
Overview
http-signature
is a reference implementation of Joyent's HTTP Signature scheme.
Affected versions of the package are vulnerable to Timing Attacks due to time-variable comparison of signatures.
The library implemented a character to character comparison, similar to the built-in string comparison mechanism, ===
, and not a time constant string comparison. As a result, the comparison will fail faster when the first characters in the signature are incorrect.
An attacker can use this difference to perform a timing attack, essentially allowing them to guess the signature one character at a time.
You can read more about timing attacks in Node.js on the Snyk blog.
Remediation
Upgrade http-signature
to version 1.0.0 or higher.
References
medium severity
- Vulnerable module: qs
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › qs@0.6.6Remediation: Upgrade to generator-zf5@0.7.3.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Denial of Service (DoS). When parsing a string representing a deeply nested object, qs will block the event loop for long periods of time. Such a delay may hold up the server's resources, keeping it from processing other requests in the meantime, thus enabling a Denial-of-Service attack.
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 qs
to version 1.0.0 or higher.
References
medium severity
- Vulnerable module: decompress
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
decompress is a package that can be used for extracting archives.
Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip). It is possible to bypass the security measures provided by decompress and conduct ZIP path traversal through symlinks.
PoC
const decompress = require('decompress');
decompress('slip.tar.gz', 'dist').then(files => {
console.log('done!');
});
Details
It is exploited using a specially crafted zip archive, that holds path traversal filenames. When exploited, a filename in a malicious archive is concatenated to the target extraction directory, which results in the final path ending up outside of the target folder. For instance, a zip may hold a file with a "../../file.exe" location and thus break out of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.
The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicous file will result in traversing out of the target folder, ending up in /root/.ssh/
overwriting the authorized_keys
file:
+2018-04-15 22:04:29 ..... 19 19 good.txt
+2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys
Remediation
Upgrade decompress
to version 4.2.1 or higher.
References
medium severity
- Vulnerable module: hoek
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › hawk@1.0.0 › hoek@0.9.1Remediation: Upgrade to generator-zf5@0.7.3.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › hawk@1.0.0 › boom@0.4.2 › hoek@0.9.1Remediation: Upgrade to generator-zf5@0.7.3.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › hawk@1.0.0 › sntp@0.2.4 › hoek@0.9.1Remediation: Upgrade to generator-zf5@0.7.3.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › hawk@1.0.0 › cryptiles@0.2.2 › boom@0.4.2 › hoek@0.9.1Remediation: Upgrade to generator-zf5@0.7.3.
Overview
hoek is an Utility methods for the hapi ecosystem.
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 Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
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 hoek
to version 4.2.1, 5.0.3 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.23.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › lodash@2.4.2
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › lodash@2.1.0
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: tough-cookie
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › tough-cookie@0.9.15Remediation: Upgrade to generator-zf5@0.7.3.
Overview
tough-cookie
is RFC6265 Cookies and Cookie Jar for node.js.
Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks. An attacker may pass a specially crafted cookie, 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
Upgrade to version 2.3.3
or newer.
References
medium severity
- Vulnerable module: underscore
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › cheerio@0.13.1 › underscore@1.5.2Remediation: Upgrade to yeoman-generator@0.19.0.
Overview
underscore is a JavaScript's functional programming helper library.
Affected versions of this package are vulnerable to Arbitrary Code Injection via the template
function, particularly when the variable
option is taken from _.templateSettings
as it is not sanitized.
PoC
const _ = require('underscore');
_.templateSettings.variable = "a = this.process.mainModule.require('child_process').execSync('touch HELLO')";
const t = _.template("")();
Remediation
Upgrade underscore
to version 1.13.0-2, 1.12.1 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.23.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › lodash@2.4.2
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › lodash@2.1.0
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: request
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0Remediation: Upgrade to generator-zf5@0.7.3.
Overview
request is a simplified http request client.
Affected versions of this package are vulnerable to Remote Memory Exposure.
A potential remote memory exposure vulnerability exists in request
. If a request
uses a multipart attachment and the body type option is number
with value X, then X bytes of uninitialized memory will be sent in the body of the request.
Note that while the impact of this vulnerability is high (memory exposure), exploiting it is likely difficult, as the attacker needs to somehow control the body type of the request. One potential exploit scenario is when a request is composed based on JSON input, including the body type, allowing a malicious JSON to trigger the memory leak.
Details
Constructing a Buffer
class with integer N
creates a Buffer
of length N
with non zero-ed out memory.
Example:
var x = new Buffer(100); // uninitialized Buffer of length 100
// vs
var x = new Buffer('100'); // initialized Buffer with value of '100'
Initializing a multipart body in such manner will cause uninitialized memory to be sent in the body of the request.
Proof of concept
var http = require('http')
var request = require('request')
http.createServer(function (req, res) {
var data = ''
req.setEncoding('utf8')
req.on('data', function (chunk) {
console.log('data')
data += chunk
})
req.on('end', function () {
// this will print uninitialized memory from the client
console.log('Client sent:\n', data)
})
res.end()
}).listen(8000)
request({
method: 'POST',
uri: 'http://localhost:8000',
multipart: [{ body: 1000 }]
},
function (err, res, body) {
if (err) return console.error('upload failed:', err)
console.log('sent')
})
Remediation
Upgrade request
to version 2.68.0 or higher.
References
medium severity
- Vulnerable module: tunnel-agent
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › tunnel-agent@0.3.0Remediation: Upgrade to generator-zf5@0.7.3.
Overview
tunnel-agent
is HTTP proxy tunneling agent. Affected versions of the package are vulnerable to Uninitialized Memory Exposure.
A possible memory disclosure vulnerability exists when a value of type number
is used to set the proxy.auth option of a request request
and results in a possible uninitialized memory exposures in the request body.
This is a result of unobstructed use of the Buffer
constructor, whose insecure default constructor increases the odds of memory leakage.
Details
Constructing a Buffer
class with integer N
creates a Buffer
of length N
with raw (not "zero-ed") memory.
In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":
// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');
tunnel-agent
's request
construction uses the default Buffer
constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed
flaw in OpenSSL.
Proof of concept by ChALkeR
require('request')({
method: 'GET',
uri: 'http://www.example.com',
tunnel: true,
proxy:{
protocol: 'http:',
host:"127.0.0.1",
port:8080,
auth:80
}
});
You can read more about the insecure Buffer
behavior on our blog.
Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.
Remediation
Upgrade tunnel-agent
to version 0.6.0 or higher.
Note This is vulnerable only for Node <=4
References
medium severity
- Vulnerable module: lodash
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.23.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › findup-sync@0.1.3 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › inquirer@0.4.1 › lodash@2.4.2Remediation: Upgrade to yeoman-generator@0.21.0.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › findup-sync@0.1.3 › lodash@2.4.2
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › file-utils@0.1.5 › lodash@2.1.0
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
low severity
- Vulnerable module: hawk
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › hawk@1.0.0Remediation: Upgrade to generator-zf5@0.7.3.
Overview
hawk
is an HTTP authentication scheme using a message authentication code (MAC) algorithm to provide partial HTTP request cryptographic verification.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks.
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.
You can read more about Regular Expression Denial of Service (ReDoS)
on our blog.
References
low severity
- Vulnerable module: mime
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › mime@1.2.11Remediation: Upgrade to generator-zf5@0.7.3.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › mime@1.2.11Remediation: Upgrade to generator-zf5@0.7.3.
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › request@2.30.0 › form-data@0.1.4 › mime@1.2.11Remediation: Upgrade to generator-zf5@0.7.3.
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: tar
- Introduced through: yeoman-generator@0.16.0
Detailed paths
-
Introduced through: generator-zf5@0.6.4 › yeoman-generator@0.16.0 › download@0.1.19 › decompress@0.2.5 › tar@0.1.20Remediation: Upgrade to yeoman-generator@0.24.1.
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). When stripping the trailing slash from files
arguments, the f.replace(/\/+$/, '')
performance of this function can exponentially degrade when f
contains many /
characters resulting in ReDoS.
This vulnerability is not likely to be exploitable as it requires that the untrusted input is being passed into the tar.extract()
or tar.list()
array of entries to parse/extract, which would be unusual.
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 tar
to version 6.1.4, 5.0.8, 4.4.16 or higher.