@62d/generator-62d@0.0.0

Vulnerabilities

43 via 192 paths

Dependencies

682

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 1
  • 25
  • 14
  • 3
Status
  • 43
  • 0
  • 0

critical severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution in zipObjectDeep due to an incomplete fix for CVE-2020-8203.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

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

Prototype Pollution

  • Vulnerable module: ajv
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 request@2.81.0 har-validator@4.2.1 ajv@4.11.8

Overview

ajv is an Another JSON Schema Validator

Affected versions of this package are vulnerable to Prototype Pollution. A carefully crafted JSON schema could be provided that allows execution of other code by prototype pollution. (While untrusted schemas are recommended against, the worst case of an untrusted schema should be a denial of service, not execution of code.)

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade ajv to version 6.12.3 or higher.

References

high severity
new

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ansi-regex
  • Introduced through: yosay@1.2.1, chalk@1.1.3 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yosay@1.2.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to chalk@2.0.0.
  • Introduced through: @62d/generator-62d@0.0.0 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to chalk@2.0.0.
  • Introduced through: @62d/generator-62d@0.0.0 yosay@1.2.1 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yosay@1.2.1 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yosay@1.2.1 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yosay@1.2.1 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 yosay@1.2.1 wrap-ansi@2.1.0 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-environment@1.6.6 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-welcome@1.0.1 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-environment@1.6.6 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-welcome@1.0.1 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yosay@1.2.1 wrap-ansi@2.1.0 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 columnify@1.5.4 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-environment@1.6.6 inquirer@1.2.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@2.0.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-environment@1.6.6 inquirer@1.2.3 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@2.0.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-environment@1.6.6 log-symbols@1.0.2 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-environment@1.6.6 inquirer@1.2.3 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@2.0.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-environment@1.6.6 log-symbols@1.0.2 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-environment@1.6.6 inquirer@1.2.3 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@2.0.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 npmlog@4.1.2 gauge@2.7.4 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 npmlog@4.0.2 gauge@2.7.4 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 request@2.75.0 har-validator@2.0.6 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 request@2.75.0 har-validator@2.0.6 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 npmlog@4.1.2 gauge@2.7.4 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 npmlog@4.0.2 gauge@2.7.4 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 npmlog@3.1.2 gauge@2.6.0 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 npm-registry-client@7.2.1 npmlog@3.1.2 gauge@2.6.0 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 npmlog@3.1.2 gauge@2.6.0 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 npm-registry-client@7.2.1 npmlog@3.1.2 gauge@2.6.0 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tar@3.1.0 strip-dirs@1.1.1 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@0.24.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tarbz2@3.1.0 strip-dirs@1.1.1 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@0.24.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-targz@3.1.0 strip-dirs@1.1.1 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@0.24.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-unzip@3.4.0 strip-dirs@1.1.1 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tar@3.1.0 strip-dirs@1.1.1 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@0.24.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tarbz2@3.1.0 strip-dirs@1.1.1 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@0.24.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-targz@3.1.0 strip-dirs@1.1.1 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to yeoman-generator@0.24.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-unzip@3.4.0 strip-dirs@1.1.1 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tar@3.1.0 strip-dirs@1.1.1 sum-up@1.0.3 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tarbz2@3.1.0 strip-dirs@1.1.1 sum-up@1.0.3 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-targz@3.1.0 strip-dirs@1.1.1 sum-up@1.0.3 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-unzip@3.4.0 strip-dirs@1.1.1 sum-up@1.0.3 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tar@3.1.0 strip-dirs@1.1.1 sum-up@1.0.3 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tarbz2@3.1.0 strip-dirs@1.1.1 sum-up@1.0.3 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-targz@3.1.0 strip-dirs@1.1.1 sum-up@1.0.3 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-unzip@3.4.0 strip-dirs@1.1.1 sum-up@1.0.3 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 npmlog@4.1.2 gauge@2.7.4 wide-align@1.1.3 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 npmlog@4.0.2 gauge@2.7.4 wide-align@1.1.3 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 npmlog@3.1.2 gauge@2.6.0 wide-align@1.1.3 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 npm-registry-client@7.2.1 npmlog@3.1.2 gauge@2.6.0 wide-align@1.1.3 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 ansi-regex@1.1.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 readline2@0.1.1 strip-ansi@2.0.1 ansi-regex@1.1.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 chalk@0.5.1 has-ansi@0.1.0 ansi-regex@0.2.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 chalk@0.5.1 strip-ansi@0.3.0 ansi-regex@0.2.1
    Remediation: Upgrade to yeoman-generator@0.20.0.

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the sub-patterns [[\\]()#;?]* and (?:;[-a-zA-Z\\d\\/#&.:=?%@~_]*)*.

PoC

import ansiRegex from 'ansi-regex';

for(var i = 1; i <= 50000; i++) {
    var time = Date.now();
    var attack_str = "\u001B["+";".repeat(i*10000);
    ansiRegex().test(attack_str)
    var time_cost = Date.now() - time;
    console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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 ansi-regex to version 6.0.1, 5.0.1 or higher.

References

high severity

Remote Memory Exposure

  • Vulnerable module: bl
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 request@2.75.0 bl@1.1.2
    Remediation: Upgrade to nodegit@0.6.0.

Overview

bl is a library that allows you to collect buffers and access with a standard readable buffer interface.

Affected versions of this package are vulnerable to Remote Memory Exposure. If user input ends up in consume() argument and can become negative, BufferList state can be corrupted, tricking it into exposing uninitialized memory via regular .slice() calls.

PoC by chalker

const { BufferList } = require('bl')
const secret = require('crypto').randomBytes(256)
for (let i = 0; i < 1e6; i++) {
  const clone = Buffer.from(secret)
  const bl = new BufferList()
  bl.append(Buffer.from('a'))
  bl.consume(-1024)
  const buf = bl.slice(1)
  if (buf.indexOf(clone) !== -1) {
    console.error(`Match (at ${i})`, buf)
  }
}

Remediation

Upgrade bl to version 2.2.1, 3.0.1, 4.0.3, 1.2.3 or higher.

References

high severity

Command Injection

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

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

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

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

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

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

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

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 and test2 is now in the Object.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

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

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

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

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

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

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

Command Injection

  • Vulnerable module: lodash.template
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 gulp-util@3.0.8 lodash.template@3.6.2

Overview

lodash.template is a The Lodash method _.template exported as a Node.js module.

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

There is no fixed version for lodash.template.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 findup-sync@0.2.1 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to yeoman-generator@0.21.0.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 findup-sync@0.2.1 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to yeoman-generator@0.21.0.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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

Directory Traversal

  • Vulnerable module: nodegit
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0
    Remediation: Upgrade to nodegit@0.26.3.

Overview

nodegit is a Node bindings to the libgit2 project.

Affected versions of this package are vulnerable to Directory Traversal. While the only permitted drive letters for physical drives on Windows are letters of the US-English alphabet, this restriction does not apply to virtual drives assigned via subst <letter>: <path>. Git mistook such paths for relative paths, allowing writing outside of the worktree while cloning.

This vulnerability can only be exploited on Windows, and only when the targeted user is known to use non-alphabetical drive letters on logical drives registered with the subst.exe command, allowing to overwrite arbitrary files on said logical drive during a regular git clone.

Remediation

Upgrade nodegit to version 0.26.3 or higher.

References

high severity

Improper Handling of Alternate Data Stream

  • Vulnerable module: nodegit
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0
    Remediation: Upgrade to nodegit@0.26.3.

Overview

nodegit is a Node bindings to the libgit2 project.

Affected versions of this package are vulnerable to Improper Handling of Alternate Data Stream. Git was unaware of NTFS Alternate Data Streams, allowing files inside the .git/ directory to be overwritten during a clone.

While the description contains "NTFS", this vulnerability can not only be exploited on Windows, but also on macOS when working on smb://-mounted network shares. The exploit involves naming a directory .git::$INDEX_ALLOCATION, allowing remote code execution during a regular git clone.

The fix for this CVE requires the fix for CVE-2019-1353.

Remediation

Upgrade nodegit to version 0.26.3 or higher.

References

high severity

Improper Handling of Alternate Data Stream

  • Vulnerable module: nodegit
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0
    Remediation: Upgrade to nodegit@0.26.3.

Overview

nodegit is a Node bindings to the libgit2 project.

Affected versions of this package are vulnerable to Improper Handling of Alternate Data Stream. When running Git in the Windows Subsystem for Linux (also known as "WSL") while accessing a working directory on a regular Windows drive, none of the NTFS protections were active.

This vulnerability affects Git when running inside the Windows Subsystem for Linux and only when working on Windows drives where NTFS short names are enabled (which is the case, by default, for the system drive, i.e. C:).

The exploit uses a directory named git~1 and it allows remote code execution during a regular git clone.

For this reason, Git now turns on core.protectNTFS by default, which is also required to address CVE-2019-1352.

Remediation

Upgrade nodegit to version 0.26.3 or higher.

References

high severity

Improper Link Resolution Before File Access

  • Vulnerable module: nodegit
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0
    Remediation: Upgrade to nodegit@0.26.3.

Overview

nodegit is a Node bindings to the libgit2 project.

Affected versions of this package are vulnerable to Improper Link Resolution Before File Access. Filenames on Linux/Unix can contain backslashes. On Windows, backslashes are directory separators. Git did not use to refuse to write out tracked files with such filenames.

The exploit uses backslashes in the file names stored in tree objects, allowing arbitrary files even outside of the Git worktree to be over-written.

Note: This is a Windows-only vulnerability.

Remediation

Upgrade nodegit to version 0.26.3 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: npm
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10
    Remediation: Upgrade to nodegit@0.6.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. It fails to prevent existing globally-installed binaries to be overwritten by other package installations. For example, if a package was installed globally and created a serve binary, any subsequent installs of packages that also create a serve binary would overwrite the first binary. This only affects files in /usr/local/bin.

For npm, this behaviour is still allowed in local installations and also through install scripts. This vulnerability bypasses a user using the --ignore-scripts install option.

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 npm to version 6.13.4 or higher.

References

high severity

Arbitrary File Write

  • Vulnerable module: npm
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10
    Remediation: Upgrade to nodegit@0.6.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Arbitrary File Write. It fails to prevent access to folders outside of the intended node_modules folder through the bin field.

For npm, a properly constructed entry in the package.json bin field would allow a package publisher to modify and/or gain access to arbitrary files on a user’s system when the package is installed. This behaviour is possible through install scripts. This vulnerability bypasses a user using the --ignore-scripts install option.

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 npm to version 6.13.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: npm-user-validate
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 npm-user-validate@0.1.5
    Remediation: Upgrade to nodegit@0.6.0.

Overview

npm-user-validate is an User validations for npm

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The regex that validates user emails took exponentially longer to process long input strings beginning with @ 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:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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 npm-user-validate to version 1.0.1 or higher.

References

high severity
new

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: nth-check
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 css-select@1.0.0 nth-check@1.0.2

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) mainly due to the sub-pattern \s*(?:([+-]?)\s*(\d+))? in RE_NTH_ELEMENT with quantified overlapping adjacency.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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 nth-check to version 2.0.1 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar@2.2.2
    Remediation: Upgrade to nodegit@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar-pack@3.4.1 tar@2.2.2
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.

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

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar@2.2.2
    Remediation: Upgrade to nodegit@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar-pack@3.4.1 tar@2.2.2
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.

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
new

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar@2.2.2
    Remediation: Upgrade to nodegit@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar-pack@3.4.1 tar@2.2.2
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.

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
new

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar@2.2.2
    Remediation: Upgrade to nodegit@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar-pack@3.4.1 tar@2.2.2
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.

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
new

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar@2.2.2
    Remediation: Upgrade to nodegit@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar-pack@3.4.1 tar@2.2.2
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.

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

Denial of Service (DoS)

  • Vulnerable module: trim-newlines
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 dateformat@1.0.12 meow@3.7.0 trim-newlines@1.0.0
    Remediation: Upgrade to yeoman-generator@1.1.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 pretty-bytes@1.0.4 meow@3.7.0 trim-newlines@1.0.0
    Remediation: Upgrade to yeoman-generator@5.0.0.

Overview

trim-newlines is a Trim newlines from the start and/or end of a string

Affected versions of this package are vulnerable to Denial of Service (DoS) via the end() method.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade trim-newlines to version 3.0.1, 4.0.1 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: underscore.string
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 underscore.string@3.3.5

Overview

underscore.string is a Javascript lacks complete string manipulation operations.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

There is no fixed version for underscore.string.

References

medium severity

Time of Check Time of Use (TOCTOU)

  • Vulnerable module: chownr
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 chownr@1.0.1
    Remediation: Upgrade to nodegit@0.6.0.

Overview

chownr is a package that takes the same arguments as fs.chown()

Affected versions of this package are vulnerable to Time of Check Time of Use (TOCTOU). Affected versions of this package are vulnerable toTime of Check Time of Use (TOCTOU) attacks.

It does not dereference symbolic links and changes the owner of the link, which can trick it into descending into unintended trees if a non-symlink is replaced by a symlink at a critical moment:

      fs.lstat(pathChild, function(er, stats) {
        if (er)
          return cb(er)
        if (!stats.isSymbolicLink())
          chownr(pathChild, uid, gid, then)

Remediation

Upgrade chownr to version 1.1.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: css-what
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 css-select@1.0.0 css-what@1.0.0

Overview

css-what is an a CSS selector parser

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via attribute parsing.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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 css-what to version 5.0.1 or higher.

References

medium severity

Arbitrary File Write via Archive Extraction (Zip Slip)

  • Vulnerable module: decompress
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0
    Remediation: 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

Arbitrary File Write via Archive Extraction (Zip Slip)

  • Vulnerable module: decompress-tar
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tar@3.1.0

Overview

decompress-tar is a tar plugin for decompress.

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

There is no fixed version for decompress-tar.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: glob-parent
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 vinyl-fs@2.4.4 glob-stream@5.3.5 glob-parent@3.1.0
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 vinyl-fs@2.4.4 glob-stream@5.3.5 glob-parent@3.1.0
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0

Overview

glob-parent is a package that helps extracting the non-magic parent path from a glob string.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The enclosure regex used to check for strings ending in enclosure containing path separator.

PoC by Yeting Li

var globParent = require("glob-parent")
function build_attack(n) {
var ret = "{"
for (var i = 0; i < n; i++) {
ret += "/"
}

return ret;
}

globParent(build_attack(5000));

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade glob-parent to version 5.1.2 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: hoek
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 hawk@3.1.3 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 hawk@3.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 hawk@3.1.3 sntp@1.0.9 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 request@2.81.0 hawk@3.1.3 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 request@2.75.0 hawk@3.1.3 hoek@2.16.3
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 hawk@3.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 request@2.81.0 hawk@3.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 request@2.75.0 hawk@3.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 request@2.81.0 hawk@3.1.3 sntp@1.0.9 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 request@2.75.0 hawk@3.1.3 sntp@1.0.9 hoek@2.16.3
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 request@2.81.0 hawk@3.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 request@2.75.0 hawk@3.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to nodegit@0.6.0.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: hosted-git-info
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 hosted-git-info@2.1.5
    Remediation: Upgrade to nodegit@0.6.0.

Overview

hosted-git-info is a Provides metadata and conversions from repository urls for Github, Bitbucket and Gitlab

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via regular expression shortcutMatch in the fromUrl function in index.js. The affected regular expression exhibits polynomial worst-case time complexity.

PoC by Yeting Li

var hostedGitInfo = require("hosted-git-info")
function build_attack(n) {
    var ret = "a:"
    for (var i = 0; i < n; i++) {
        ret += "a"
    }
    return ret + "!";
}

for(var i = 1; i <= 5000000; i++) {
   if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       var parsedInfo = hostedGitInfo.fromUrl(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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 hosted-git-info to version 3.0.8, 2.8.9 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

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

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.16 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

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

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: lodash
  • Introduced through: request-promise@1.0.2, yeoman-generator@0.19.2 and others

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 request-promise@1.0.2 lodash@3.10.1
    Remediation: Upgrade to request-promise@2.0.1.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.21.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 mem-fs-editor@1.2.3 lodash@3.10.1
    Remediation: Upgrade to yeoman-generator@0.20.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: @62d/generator-62d@0.0.0 wp-cli@0.0.5 lodash@2.4.2
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 yeoman-assert@1.0.0 lodash@2.4.2
    Remediation: Upgrade to yeoman-generator@0.20.0.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade lodash to version 4.17.11 or higher.

References

medium severity

Access Restriction Bypass

  • Vulnerable module: npm
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10
    Remediation: Upgrade to nodegit@0.6.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Access Restriction Bypass. It might allow local users to bypass intended filesystem access restrictions due to ownerships of /etc and /usr directories are being changed unexpectedly, related to a "correctMkdir" issue.

Remediation

Upgrade npm to version 5.7.1 or higher.

References

medium severity

Insertion of Sensitive Information into Log File

  • Vulnerable module: npm
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10
    Remediation: Upgrade to nodegit@0.6.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Insertion of Sensitive Information into Log File. The CLI supports URLs like <protocol>://[<user>[:<password>]@]<hostname>[:<port>][:][/]<path>. The password value is not redacted and is printed to stdout and also to any generated log files.

Remediation

Upgrade npm to version 6.14.6 or higher.

References

medium severity

Uninitialized Memory Exposure

  • Vulnerable module: tunnel-agent
  • Introduced through: nodegit@0.5.0 and yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 request@2.75.0 tunnel-agent@0.4.3
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 caw@1.2.0 tunnel-agent@0.4.3
    Remediation: Upgrade to yeoman-generator@0.24.1.

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

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: braces
  • Introduced through: yeoman-generator@0.19.2

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 braces@1.8.5
  • Introduced through: @62d/generator-62d@0.0.0 yeoman-generator@0.19.2 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 braces@1.8.5

Overview

braces is a Bash-like brace expansion, implemented in JavaScript.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\{(,+(?:(\{,+\})*),*|,*(?:(\{,+\})*),+)\}) in order to detects empty braces. This can cause an impact of about 10 seconds matching time for data 50K characters long.

Disclosure Timeline

  • Feb 15th, 2018 - Initial Disclosure to package owner
  • Feb 16th, 2018 - Initial Response from package owner
  • Feb 18th, 2018 - Fix issued
  • Feb 19th, 2018 - Vulnerability published

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade braces to version 2.3.1 or higher.

References

low severity

Unauthorized File Access

  • Vulnerable module: npm
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10
    Remediation: Upgrade to nodegit@0.6.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Unauthorized File Access. It is possible for packages to create symlinks to files outside of thenode_modules folder through the bin field upon installation.

For npm, a properly constructed entry in the package.json bin field would allow a package publisher to create a symlink pointing to arbitrary files on a user’s system when the package is installed. This behaviour is possible through install scripts. This vulnerability bypasses a user using the --ignore-scripts install option.

Remediation

Upgrade npm to version 6.13.3 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: tar
  • Introduced through: nodegit@0.5.0

Detailed paths

  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar@2.2.2
    Remediation: Upgrade to nodegit@0.23.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 node-pre-gyp@0.6.39 tar-pack@3.4.1 tar@2.2.2
  • Introduced through: @62d/generator-62d@0.0.0 nodegit@0.5.0 npm@3.10.10 node-gyp@3.4.0 tar@2.2.2
    Remediation: Upgrade to nodegit@0.6.0.

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:

  1. CCC
  2. CC+C
  3. C+CC
  4. 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.

References