Vulnerabilities |
55 via 462 paths |
---|---|
Dependencies |
450 |
Source |
npm |
Find, fix and prevent vulnerabilities in your code.
critical severity
- Vulnerable module: growl
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5 › growl@1.8.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5 › growl@1.8.1
Overview
growl is a package adding Growl support for Nodejs.
Affected versions of this package are vulnerable to Arbitrary Code Injection due to unsafe use of the eval()
function. Node.js provides the eval()
function by default, and is used to translate strings into Javascript code. An attacker can craft a malicious payload to inject arbitrary commands.
Remediation
Upgrade growl
to version 1.10.0 or higher.
References
critical severity
- Vulnerable module: adm-zip
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › adm-zip@0.2.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › adm-zip@0.2.1
Overview
adm-zip is a JavaScript implementation for zip data compression for NodeJS.
Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip).
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 adm-zip
to version 0.4.11 or higher.
References
high severity
- Vulnerable module: shell-quote
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › browserify@9.0.8 › shell-quote@0.0.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › browserify@9.0.8 › shell-quote@0.0.1
Overview
shell-quote is a package used to quote and parse shell commands.
Affected versions of this package are vulnerable to Command Injection. The quote
function does not properly escape the following special characters <
, >
, ;
, {
, }
, and as a result can be used by an attacker to inject malicious shell commands or leak sensitive information.
Proof of Concept
Consider the following poc.js
application
var quote = require('shell-quote').quote;
var exec = require('child_process').exec;
var userInput = process.argv[2];
var safeCommand = quote(['echo', userInput]);
exec(safeCommand, function (err, stdout, stderr) {
console.log(stdout);
});
Running the following command will not only print the character a
as expected, but will also run the another command, i.e touch malicious.sh
$ node poc.js 'a;{touch,malicious.sh}'
Remediation
Upgrade shell-quote
to version 1.6.1 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: vigour-config@0.0.14, vigour-wrapper@2.2.36 and others
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6Remediation: Open PR to patch lodash@4.16.6.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6Remediation: Open PR to patch lodash@4.16.6.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The function zipObjectDeep
can be tricked into adding or modifying properties of the Object prototype. These properties will be present on all objects.
PoC
const _ = require('lodash');
_.zipObjectDeep(['__proto__.z'],[123])
console.log(z) // 123
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.20 or higher.
References
high severity
- Vulnerable module: shell-quote
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › browserify@9.0.8 › shell-quote@0.0.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › browserify@9.0.8 › shell-quote@0.0.1
Overview
shell-quote is a package used to quote and parse shell commands.
Affected versions of this package are vulnerable to Remote Code Execution (RCE). An attacker can inject unescaped shell metacharacters through a regex designed to support Windows drive letters. If the output of this package is passed to a real shell as a quoted argument to a command with exec(), an attacker can inject arbitrary commands. This is because the Windows drive letter regex character class is {A-z]
instead of the correct {A-Za-z]
. Several shell metacharacters exist in the space between capital letter Z and lower case letter a, such as the backtick character.
Remediation
Upgrade shell-quote
to version 1.7.3 or higher.
References
high severity
- Vulnerable module: bl
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › tar-stream@1.1.5 › bl@0.9.5
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › tar-stream@1.1.5 › bl@0.9.5
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
- Vulnerable module: async
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › async@0.9.2
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › async@0.9.2
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › form-data@0.1.4 › async@0.9.2
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › form-data@0.1.4 › async@0.9.2
Overview
Affected versions of this package are vulnerable to Prototype Pollution via the mapValues()
method.
PoC
//when objects are parsed, all properties are created as own (the objects can come from outside sources (http requests/ file))
const hasOwn = JSON.parse('{"__proto__": {"isAdmin": true}}');
//does not have the property, because it's inside object's own "__proto__"
console.log(hasOwn.isAdmin);
async.mapValues(hasOwn, (val, key, cb) => cb(null, val), (error, result) => {
// after the method executes, hasOwn.__proto__ value (isAdmin: true) replaces the prototype of the newly created object, leading to potential exploits.
console.log(result.isAdmin);
});
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade async
to version 2.6.4, 3.2.2 or higher.
References
high severity
- Vulnerable module: fresh
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › fresh@0.2.4
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › fresh@0.2.4
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › fresh@0.2.4
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › fresh@0.2.4
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › fresh@0.2.4
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › fresh@0.2.4
Overview
fresh
is HTTP response freshness testing.
Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks. A Regular Expression (/ *, */
) was used for parsing HTTP headers and take about 2 seconds matching time for 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade fresh
to version 0.5.2 or higher.
References
high severity
- Vulnerable module: minimatch
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › glob@4.3.5 › minimatch@2.0.10
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › browserify@9.0.8 › glob@4.5.3 › minimatch@2.0.10
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › glob@4.3.5 › minimatch@2.0.10
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › browserify@9.0.8 › glob@4.5.3 › minimatch@2.0.10
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5 › glob@3.2.3 › minimatch@0.2.14
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5 › glob@3.2.3 › minimatch@0.2.14
Overview
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via complicated and illegal regexes.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade minimatch
to version 3.0.2 or higher.
References
high severity
- Vulnerable module: minimatch
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › glob@4.3.5 › minimatch@2.0.10Remediation: Open PR to patch minimatch@2.0.10.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › browserify@9.0.8 › glob@4.5.3 › minimatch@2.0.10Remediation: Open PR to patch minimatch@2.0.10.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › glob@4.3.5 › minimatch@2.0.10Remediation: Open PR to patch minimatch@2.0.10.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › browserify@9.0.8 › glob@4.5.3 › minimatch@2.0.10Remediation: Open PR to patch minimatch@2.0.10.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5 › glob@3.2.3 › minimatch@0.2.14Remediation: Open PR to patch minimatch@0.2.14.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5 › glob@3.2.3 › minimatch@0.2.14Remediation: Open PR to patch minimatch@0.2.14.
Overview
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS).
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade minimatch
to version 3.0.2 or higher.
References
high severity
- Vulnerable module: mocha
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5
Overview
mocha is a javascript test framework for node.js & the browser.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). If the stack trace in utils.js
begins with a large error message (>= 20k characters), and full-trace
is not undisabled, utils.stackTraceFilter()
will take exponential time to run.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade mocha
to version 6.0.0 or higher.
References
high severity
- Vulnerable module: negotiator
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › accepts@1.2.13 › negotiator@0.5.3Remediation: Open PR to patch negotiator@0.5.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › accepts@1.2.13 › negotiator@0.5.3Remediation: Open PR to patch negotiator@0.5.3.
Overview
negotiator is an HTTP content negotiator for Node.js.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS)
when parsing Accept-Language
http header.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade negotiator
to version 0.6.1 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › qs@0.6.6Remediation: Open PR to patch qs@0.6.6.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › qs@0.6.6Remediation: Open PR to patch qs@0.6.6.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Denial of Service (DoS).
During parsing, the qs
module may create a sparse area (an array where no elements are filled), and grow that array to the necessary size based on the indices used on it. An attacker can specify a high index value in a query string, thus making the server allocate a respectively big array. Truly large values can cause the server to run out of memory and cause it to crash - thus enabling a Denial-of-Service attack.
Remediation
Upgrade qs
to version 1.0.0 or higher.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
References
high severity
- Vulnerable module: qs
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › body-parser@1.12.2 › qs@2.4.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › qs@2.4.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › body-parser@1.12.2 › qs@2.4.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › qs@2.4.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › qs@0.6.6
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › qs@0.6.6
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Prototype Override Protection Bypass. By default qs
protects against attacks that attempt to overwrite an object's existing prototype properties, such as toString()
, hasOwnProperty()
,etc.
From qs
documentation:
By default parameters that would overwrite properties on the object prototype are ignored, if you wish to keep the data from those fields either use plainObjects as mentioned above, or set allowPrototypes to true which will allow user input to overwrite those properties. WARNING It is generally a bad idea to enable this option as it can cause problems when attempting to use the properties that have been overwritten. Always be careful with this option.
Overwriting these properties can impact application logic, potentially allowing attackers to work around security controls, modify data, make the application unstable and more.
In versions of the package affected by this vulnerability, it is possible to circumvent this protection and overwrite prototype properties and functions by prefixing the name of the parameter with [
or ]
. e.g. qs.parse("]=toString")
will return {toString = true}
, as a result, calling toString()
on the object will throw an exception.
Example:
qs.parse('toString=foo', { allowPrototypes: false })
// {}
qs.parse("]=toString", { allowPrototypes: false })
// {toString = true} <== prototype overwritten
For more information, you can check out our blog.
Disclosure Timeline
- February 13th, 2017 - Reported the issue to package owner.
- February 13th, 2017 - Issue acknowledged by package owner.
- February 16th, 2017 - Partial fix released in versions
6.0.3
,6.1.1
,6.2.2
,6.3.1
. - March 6th, 2017 - Final fix released in versions
6.4.0
,6.3.2
,6.2.3
,6.1.2
and6.0.4
Remediation
Upgradeqs
to version 6.0.4, 6.1.2, 6.2.3, 6.3.2 or higher.References
- GitHub Commit
- GitHub Issue
high severity
- Vulnerable module: adm-zip
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › adm-zip@0.2.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › adm-zip@0.2.1
Overview
adm-zip is a JavaScript implementation for zip data compression for NodeJS.
Affected versions of this package are vulnerable to Directory Traversal. It could extract files outside the target folder.
Details
A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.
Directory Traversal vulnerabilities can be generally divided into two types:
- Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.
st
is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public
route.
If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.
curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa
Note %2e
is the URL encoded version of .
(dot).
- Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as
Zip-Slip
.
One way to achieve this is by using a malicious zip
archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.
The following is an example of a zip
archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/
overwriting the authorized_keys
file:
2018-04-15 22:04:29 ..... 19 19 good.txt
2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys
Remediation
Upgrade adm-zip
to version 0.5.2 or higher.
References
high severity
new
- Vulnerable module: hawk
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0
Overview
hawk is a library for the HTTP Hawk Authentication Scheme.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in header parsing where each added character in the attacker's input increases the computation time exponentially.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
A fix was pushed into the master
branch but not yet published.
References
high severity
- Vulnerable module: npmconf
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › npmconf@0.0.24
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › npmconf@0.0.24
Overview
npmconf is a package to reintegrate directly into npm.
Affected versions of this package are vulnerable to Uninitialized Memory Exposure. It allocates and writes to disk uninitialized memory content when a typed number is passed as input.
Note npmconf
is deprecated and should not be used.
Note This is vulnerable only for Node <=4
Details
The Buffer class on Node.js is a mutable array of binary data, and can be initialized with a string, array or number.
const buf1 = new Buffer([1,2,3]);
// creates a buffer containing [01, 02, 03]
const buf2 = new Buffer('test');
// creates a buffer containing ASCII bytes [74, 65, 73, 74]
const buf3 = new Buffer(10);
// creates a buffer of length 10
The first two variants simply create a binary representation of the value it received. The last one, however, pre-allocates a buffer of the specified size, making it a useful buffer, especially when reading data from a stream.
When using the number constructor of Buffer, it will allocate the memory, but will not fill it with zeros. Instead, the allocated buffer will hold whatever was in memory at the time. If the buffer is not zeroed
by using buf.fill(0)
, it may leak sensitive information like keys, source code, and system info.
Remediation
Upgrade npmconf
to version 2.1.3 or higher.
References
high severity
- Vulnerable module: ini
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › npmconf@0.0.24 › ini@1.1.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › npmconf@0.0.24 › ini@1.1.0
Overview
ini is an An ini encoder/decoder for node
Affected versions of this package are vulnerable to Prototype Pollution. If an attacker submits a malicious INI file to an application that parses it with ini.parse
, they will pollute the prototype on the application. This can be exploited further depending on the context.
PoC by Eugene Lim
payload.ini
[__proto__]
polluted = "polluted"
poc.js:
var fs = require('fs')
var ini = require('ini')
var parsed = ini.parse(fs.readFileSync('./payload.ini', 'utf-8'))
console.log(parsed)
console.log(parsed.__proto__)
console.log(polluted)
> node poc.js
{}
{ polluted: 'polluted' }
{ polluted: 'polluted' }
polluted
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade ini
to version 1.3.6 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: vigour-config@0.0.14, vigour-wrapper@2.2.36 and others
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The function defaultsDeep
could be tricked into adding or modifying properties of Object.prototype
using a constructor
payload.
PoC by Snyk
const mergeFn = require('lodash').defaultsDeep;
const payload = '{"constructor": {"prototype": {"a0": true}}}'
function check() {
mergeFn({}, JSON.parse(payload));
if (({})[`a0`] === true) {
console.log(`Vulnerable to Prototype Pollution via ${payload}`);
}
}
check();
For more information, check out our blog post
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.12 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: vigour-config@0.0.14, vigour-wrapper@2.2.36 and others
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution via the setWith
and set
functions.
PoC by awarau
- Create a JS file with this contents:
lod = require('lodash') lod.setWith({}, "__proto__[test]", "123") lod.set({}, "__proto__[test2]", "456") console.log(Object.prototype)
- Execute it with
node
- Observe that
test
andtest2
is now in theObject.prototype
.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.17 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: vigour-config@0.0.14, vigour-wrapper@2.2.36 and others
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The functions merge
, mergeWith
, and defaultsDeep
could be tricked into adding or modifying properties of Object.prototype
. This is due to an incomplete fix to CVE-2018-3721
.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.11 or higher.
References
high severity
- Vulnerable module: lodash.set
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-util@1.4.0 › lodash.set@4.3.2
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-util@1.4.0 › lodash.set@4.3.2
Overview
lodash.set is a lodash method _.set exported as a Node.js module.
Affected versions of this package are vulnerable to Prototype Pollution via the setWith
and set
functions.
PoC by awarau
- Create a JS file with this contents:
lod = require('lodash') lod.setWith({}, "__proto__[test]", "123") lod.set({}, "__proto__[test2]", "456") console.log(Object.prototype)
- Execute it with
node
- Observe that
test
andtest2
is now in theObject.prototype
.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
There is no fixed version for lodash.set
.
References
high severity
- Vulnerable module: lodash
- Introduced through: vigour-config@0.0.14, vigour-wrapper@2.2.36 and others
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Command Injection via template
.
PoC
var _ = require('lodash');
_.template('', { variable: '){console.log(process.env)}; with(obj' })()
Remediation
Upgrade lodash
to version 4.17.21 or higher.
References
high severity
- Vulnerable module: plist
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0
Overview
plist
is a Mac OS X Plist parser/builder for Node.js and browsers
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks due to bundling a vulnerable version of the XMLBuilder package. This can cause an impact of about 10 seconds matching time for data 60 characters long.
Disclosure Timeline
- Feb 5th, 2018 - Initial Disclosure to package owner
- Feb 6th, 2018 - Initial Response from package owner
- Mar 18th, 2018 - Fix issued
- Apr 15th, 2018 - Vulnerability published
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade plist
to version 3.0.1 or higher.
References
high severity
- Vulnerable module: plist
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0
Overview
plist is a Mac OS X Plist parser/builder for Node.js and browsers.
Affected versions of this package are vulnerable to Prototype Pollution via the .parse()
, exploiting this vulnerability may lead to Denial of Service (DoS) and Remote Code Execution.
PoC:
var plist = require('plist');
var xmlPollution = `
<plist version="1.0">
<dict>
<key>__proto__</key>
<dict>
<key>length</key>
<string>polluted</string>
</dict>
</dict>
</plist>`;
console.log(plist.parse(xmlPollution).length); // polluted
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade plist
to version 3.0.4 or higher.
References
medium severity
- Vulnerable module: http-signature
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › http-signature@0.10.1Remediation: Open PR to patch http-signature@0.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › http-signature@0.10.1Remediation: Open PR to patch http-signature@0.10.1.
Overview
http-signature
is a reference implementation of Joyent's HTTP Signature scheme.
Affected versions of the package are vulnerable to Timing Attacks due to time-variable comparison of signatures.
The library implemented a character to character comparison, similar to the built-in string comparison mechanism, ===
, and not a time constant string comparison. As a result, the comparison will fail faster when the first characters in the signature are incorrect.
An attacker can use this difference to perform a timing attack, essentially allowing them to guess the signature one character at a time.
You can read more about timing attacks in Node.js on the Snyk blog.
Remediation
Upgrade http-signature
to version 1.0.0 or higher.
References
medium severity
- Vulnerable module: qs
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › qs@0.6.6Remediation: Open PR to patch qs@0.6.6.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › qs@0.6.6Remediation: Open PR to patch qs@0.6.6.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Denial of Service (DoS). When parsing a string representing a deeply nested object, qs will block the event loop for long periods of time. Such a delay may hold up the server's resources, keeping it from processing other requests in the meantime, thus enabling a Denial-of-Service attack.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade qs
to version 1.0.0 or higher.
References
medium severity
- Vulnerable module: xmldom
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmldom@0.1.31
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmldom@0.1.31
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmldom@0.1.31
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmldom@0.1.31
Overview
xmldom is an A pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module.
Affected versions of this package are vulnerable to Improper Input Validation. It does not correctly escape special characters when serializing elements are removed from their ancestor. This may lead to unexpected syntactic changes during XML processing in some downstream applications.
Note: Customers who use "xmldom" package, should use "@xmldom/xmldom" instead, as "xmldom" is no longer maintained.
Remediation
There is no fixed version for xmldom
.
References
medium severity
- Vulnerable module: hoek
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0 › hoek@0.9.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0 › boom@0.4.2 › hoek@0.9.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0 › sntp@0.2.4 › hoek@0.9.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0 › hoek@0.9.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0 › cryptiles@0.2.2 › boom@0.4.2 › hoek@0.9.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0 › boom@0.4.2 › hoek@0.9.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0 › sntp@0.2.4 › hoek@0.9.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0 › cryptiles@0.2.2 › boom@0.4.2 › hoek@0.9.1
Overview
hoek is an Utility methods for the hapi ecosystem.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade hoek
to version 4.2.1, 5.0.3 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: vigour-config@0.0.14, vigour-wrapper@2.2.36 and others
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1Remediation: Open PR to patch lodash@3.10.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var _= require('lodash');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
_.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.5 or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The em
regex within src/rules.js
file have multiple unused capture groups which could lead to a denial of service attack if user input is reachable.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade marked
to version 1.1.1 or higher.
References
medium severity
- Vulnerable module: minimist
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5 › mkdirp@0.5.0 › minimist@0.0.8
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5 › mkdirp@0.5.0 › minimist@0.0.8
Overview
minimist is a parse argument options module.
Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype
using a constructor
or __proto__
payload.
PoC by Snyk
require('minimist')('--__proto__.injected0 value0'.split(' '));
console.log(({}).injected0 === 'value0'); // true
require('minimist')('--constructor.prototype.injected1 value1'.split(' '));
console.log(({}).injected1 === 'value1'); // true
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade minimist
to version 0.2.1, 1.2.3 or higher.
References
medium severity
- Vulnerable module: simple-plist
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4
Overview
simple-plist is an A wrapper utility for interacting with plist data.
Affected versions of this package are vulnerable to Prototype Pollution via the .parse()
function. This vulnerability can be exploited when parsing a specially crafted XML.
PoC
var xmlPollution = `
<plist version="1.0">
<dict>
<key>__proto__</key>
<dict>
<key>length</key>
<string>polluted</string>
</dict>
</dict>
</plist>`;
console.log(plist.parse(xmlPollution).length); // polluted
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
There is no fixed version for simple-plist
.
References
medium severity
- Vulnerable module: xmldom
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmldom@0.1.31
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmldom@0.1.31
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmldom@0.1.31
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmldom@0.1.31
Overview
xmldom is an A pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module.
Affected versions of this package are vulnerable to XML External Entity (XXE) Injection. Does not correctly preserve system identifiers, FPIs or namespaces when repeatedly parsing and serializing maliciously crafted documents.
Details
XXE Injection is a type of attack against an application that parses XML input. XML is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. By default, many XML processors allow specification of an external entity, a URI that is dereferenced and evaluated during XML processing. When an XML document is being parsed, the parser can make a request and include the content at the specified URI inside of the XML document.
Attacks can include disclosing local files, which may contain sensitive data such as passwords or private user data, using file: schemes or relative paths in the system identifier.
For example, below is a sample XML document, containing an XML element- username.
<xml>
<?xml version="1.0" encoding="ISO-8859-1"?>
<username>John</username>
</xml>
An external XML entity - xxe
, is defined using a system identifier and present within a DOCTYPE header. These entities can access local or remote content. For example the below code contains an external XML entity that would fetch the content of /etc/passwd
and display it to the user rendered by username
.
<xml>
<?xml version="1.0" encoding="ISO-8859-1"?>
<!DOCTYPE foo [
<!ENTITY xxe SYSTEM "file:///etc/passwd" >]>
<username>&xxe;</username>
</xml>
Other XXE Injection attacks can access local resources that may not stop returning data, possibly impacting application availability and leading to Denial of Service.
Remediation
Upgrade xmldom
to version 0.5.0 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: vigour-config@0.0.14, vigour-wrapper@2.2.36 and others
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the toNumber
, trim
and trimEnd
functions.
POC
var lo = require('lodash');
function build_blank (n) {
var ret = "1"
for (var i = 0; i < n; i++) {
ret += " "
}
return ret + "1";
}
var s = build_blank(50000)
var time0 = Date.now();
lo.trim(s)
var time_cost0 = Date.now() - time0;
console.log("time_cost0: " + time_cost0)
var time1 = Date.now();
lo.toNumber(s)
var time_cost1 = Date.now() - time1;
console.log("time_cost1: " + time_cost1)
var time2 = Date.now();
lo.trimEnd(s)
var time_cost2 = Date.now() - time2;
console.log("time_cost2: " + time_cost2)
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade lodash
to version 4.17.21 or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The inline.text regex
may take quadratic time to scan for potential email addresses starting at every point.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade marked
to version 0.6.2 or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when passing unsanitized user input to inline.reflinkSearch
, if it is not being parsed by a time-limited worker thread.
PoC
import * as marked from 'marked';
console.log(marked.parse(`[x]: x
\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](`));
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade marked
to version 4.0.10 or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when unsanitized user input is passed to block.def
.
PoC
import * as marked from "marked";
marked.parse(`[x]:${' '.repeat(1500)}x ${' '.repeat(1500)} x`);
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade marked
to version 4.0.10 or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › marked@0.3.19
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). A Denial of Service condition could be triggered through exploitation of the heading
regex.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade marked
to version 0.4.0 or higher.
References
medium severity
- Vulnerable module: ms
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › body-parser@1.12.2 › debug@2.1.3 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › debug@2.1.3 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › body-parser@1.12.2 › debug@2.1.3 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › finalhandler@0.3.4 › debug@2.1.3 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › debug@2.1.3 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › debug@2.1.3 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › finalhandler@0.3.4 › debug@2.1.3 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › debug@2.1.3 › ms@0.7.0Remediation: Open PR to patch ms@0.7.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5 › debug@2.0.0 › ms@0.6.2Remediation: Open PR to patch ms@0.6.2.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5 › debug@2.0.0 › ms@0.6.2Remediation: Open PR to patch ms@0.6.2.
Overview
ms is a tiny milisecond conversion utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS)
attack when converting a time period string (i.e. "2 days"
, "1h"
) into a milliseconds integer. A malicious user could pass extremely long strings to ms()
, causing the server to take a long time to process, subsequently blocking the event loop for that extended period.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ms
to version 0.7.1 or higher.
References
medium severity
- Vulnerable module: mustache
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mustache@0.8.2
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mustache@0.8.2
Overview
When using attributes without quotes in a mustache template, an attacker can manipulate the input to introduce additional attributes, potentially executing code. This may lead to a Cross-site Scripting (XSS) vulnerability, assuming an attacker can influence the value entered into the template. If the mustache template is used to render user-generated content, this vulnerability may escalate to a persistent XSS vulnerability.
Example
For example, assume mustache was used to display user comments, using the following template:
<a href={{email}}>{{name}}</a><pre>{{comment}}</pre>
If an attacker spoofed his email address and provided the following value:
jane@evil.org onload=alert(document.cookie)
The resulting HTML would be:
<a href=wizard@evil.org onload=alert(document.cookie)>Evil Wizard</a><pre>Busted!</pre>
References
medium severity
- Vulnerable module: semver
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › npmconf@0.0.24 › semver@1.1.4
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › npmconf@0.0.24 › semver@1.1.4
Overview
semver is a semantic version parser used by npm.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The semver module uses regular expressions when parsing a version string. For a carefully crafted input, the time it takes to process these regular expressions is not linear to the length of the input. Since the semver module did not enforce a limit on the version string length, an attacker could provide a long string that would take up a large amount of resources, potentially taking a server down. This issue therefore enables a potential Denial of Service attack.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade semver
to version 4.3.2 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isSlug
function
PoC
var validator = require("validator")
function build_attack(n) {
var ret = "111"
for (var i = 0; i < n; i++) {
ret += "a"
}
return ret+"_";
}
for(var i = 1; i <= 50000; i++) {
if (i % 10000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isSlug(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:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the rtrim
function.
PoC
var validator = require("validator")
function build_attack(n) {
var ret = ""
for (var i = 0; i < n; i++) {
ret += " "
}
return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
if (i % 10000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.rtrim(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:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.7.0 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isHSL
function.
PoC
var validator = require("validator")
function build_attack(n) {
var ret = "hsla(0"
for (var i = 0; i < n; i++) {
ret += " "
}
return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
if (i % 1000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isHSL(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:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isEmail
function.
PoC
var validator = require("validator")
function build_attack(n) {
var ret = ""
for (var i = 0; i < n; i++) {
ret += "<"
}
return ret+"";
}
for(var i = 1; i <= 50000; i++) {
if (i % 10000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isEmail(attack_str,{ allow_display_name: true })
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.
References
medium severity
- Vulnerable module: request
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0Remediation: Open PR to patch request@2.36.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0Remediation: Open PR to patch request@2.36.0.
Overview
request is a simplified http request client.
Affected versions of this package are vulnerable to Remote Memory Exposure.
A potential remote memory exposure vulnerability exists in request
. If a request
uses a multipart attachment and the body type option is number
with value X, then X bytes of uninitialized memory will be sent in the body of the request.
Note that while the impact of this vulnerability is high (memory exposure), exploiting it is likely difficult, as the attacker needs to somehow control the body type of the request. One potential exploit scenario is when a request is composed based on JSON input, including the body type, allowing a malicious JSON to trigger the memory leak.
Details
Constructing a Buffer
class with integer N
creates a Buffer
of length N
with non zero-ed out memory.
Example:
var x = new Buffer(100); // uninitialized Buffer of length 100
// vs
var x = new Buffer('100'); // initialized Buffer with value of '100'
Initializing a multipart body in such manner will cause uninitialized memory to be sent in the body of the request.
Proof of concept
var http = require('http')
var request = require('request')
http.createServer(function (req, res) {
var data = ''
req.setEncoding('utf8')
req.on('data', function (chunk) {
console.log('data')
data += chunk
})
req.on('end', function () {
// this will print uninitialized memory from the client
console.log('Client sent:\n', data)
})
res.end()
}).listen(8000)
request({
method: 'POST',
uri: 'http://localhost:8000',
multipart: [{ body: 1000 }]
},
function (err, res, body) {
if (err) return console.error('upload failed:', err)
console.log('sent')
})
Remediation
Upgrade request
to version 2.68.0 or higher.
References
medium severity
- Vulnerable module: tunnel-agent
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › tunnel-agent@0.4.3Remediation: Open PR to patch tunnel-agent@0.4.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › tunnel-agent@0.4.3Remediation: Open PR to patch tunnel-agent@0.4.3.
Overview
tunnel-agent
is HTTP proxy tunneling agent. Affected versions of the package are vulnerable to Uninitialized Memory Exposure.
A possible memory disclosure vulnerability exists when a value of type number
is used to set the proxy.auth option of a request request
and results in a possible uninitialized memory exposures in the request body.
This is a result of unobstructed use of the Buffer
constructor, whose insecure default constructor increases the odds of memory leakage.
Details
Constructing a Buffer
class with integer N
creates a Buffer
of length N
with raw (not "zero-ed") memory.
In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":
// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');
tunnel-agent
's request
construction uses the default Buffer
constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed
flaw in OpenSSL.
Proof of concept by ChALkeR
require('request')({
method: 'GET',
uri: 'http://www.example.com',
tunnel: true,
proxy:{
protocol: 'http:',
host:"127.0.0.1",
port:8080,
auth:80
}
});
You can read more about the insecure Buffer
behavior on our blog.
Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.
Remediation
Upgrade tunnel-agent
to version 0.6.0 or higher.
Note This is vulnerable only for Node <=4
References
medium severity
- Vulnerable module: lodash
- Introduced through: vigour-config@0.0.14, vigour-wrapper@2.2.36 and others
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › lodash@3.10.1Remediation: Upgrade to vigour-statusbar@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-js@0.4.4 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › vigour-config@0.0.14 › vigour-js@0.5.3 › vigour-util@0.1.1 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › xcode@0.8.9 › simple-plist@0.1.4 › plist@1.2.0 › xmlbuilder@4.0.0 › lodash@3.10.1
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › archiver@0.14.4 › zip-stream@0.5.2 › lodash@3.2.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › lodash@4.16.6
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It parses dates using regex strings, which may cause a slowdown of 2 seconds per 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade lodash
to version 4.17.11 or higher.
References
low severity
- Vulnerable module: debug
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › body-parser@1.12.2 › debug@2.1.3Remediation: Open PR to patch debug@2.1.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › debug@2.1.3Remediation: Open PR to patch debug@2.1.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › body-parser@1.12.2 › debug@2.1.3Remediation: Open PR to patch debug@2.1.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › finalhandler@0.3.4 › debug@2.1.3Remediation: Open PR to patch debug@2.1.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › debug@2.1.3Remediation: Open PR to patch debug@2.1.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › debug@2.1.3Remediation: Open PR to patch debug@2.1.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › finalhandler@0.3.4 › debug@2.1.3Remediation: Open PR to patch debug@2.1.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › debug@2.1.3Remediation: Open PR to patch debug@2.1.3.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › debug@2.2.0Remediation: Open PR to patch debug@2.2.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › debug@2.2.0Remediation: Open PR to patch debug@2.2.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5 › debug@2.0.0Remediation: Open PR to patch debug@2.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5 › debug@2.0.0Remediation: Open PR to patch debug@2.0.0.
Overview
debug
is a JavaScript debugging utility modelled after Node.js core's debugging technique..
debug
uses printf-style formatting. Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks via the the %o
formatter (Pretty-print an Object all on a single line). It used a regular expression (/\s*\n\s*/g
) in order to strip whitespaces and replace newlines with spaces, in order to join the data into a single line. This can cause a very low impact of about 2 seconds matching time for data 50k characters long.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade debug
to version 2.6.9, 3.1.0 or higher.
References
low severity
- Vulnerable module: hawk
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0Remediation: Open PR to patch hawk@1.0.0.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › hawk@1.0.0Remediation: Open PR to patch hawk@1.0.0.
Overview
hawk
is an HTTP authentication scheme using a message authentication code (MAC) algorithm to provide partial HTTP request cryptographic verification.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
You can read more about Regular Expression Denial of Service (ReDoS)
on our blog.
References
low severity
- Vulnerable module: mime
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › mime@1.3.4Remediation: Open PR to patch mime@1.3.4.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › mime@1.3.4Remediation: Open PR to patch mime@1.3.4.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › mime@1.3.4Remediation: Open PR to patch mime@1.3.4.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › mime@1.3.4Remediation: Open PR to patch mime@1.3.4.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › mime@1.2.11Remediation: Open PR to patch mime@1.2.11.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › form-data@0.1.4 › mime@1.2.11Remediation: Open PR to patch mime@1.2.11.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › mime@1.2.11Remediation: Open PR to patch mime@1.2.11.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha-phantomjs@4.1.0 › phantomjs@1.9.7-15 › request@2.36.0 › form-data@0.1.4 › mime@1.2.11Remediation: Open PR to patch mime@1.2.11.
Overview
mime is a comprehensive, compact MIME type module.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It uses regex the following regex /.*[\.\/\\]/
in its lookup, which can cause a slowdown of 2 seconds for 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade mime
to version 1.4.1, 2.0.3 or higher.
References
low severity
- Vulnerable module: minimist
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5 › mkdirp@0.5.0 › minimist@0.0.8
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5 › mkdirp@0.5.0 › minimist@0.0.8
Overview
minimist is a parse argument options module.
Affected versions of this package are vulnerable to Prototype Pollution due to a missing handler to Function.prototype
.
Notes:
This vulnerability is a bypass to CVE-2020-7598
The reason for the different CVSS between CVE-2021-44906 to CVE-2020-7598, is that CVE-2020-7598 can pollute objects, while CVE-2021-44906 can pollute only function.
PoC by Snyk
require('minimist')('--_.constructor.constructor.prototype.foo bar'.split(' '));
console.log((function(){}).foo); // bar
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
- Unsafe
Object
recursive merge - Property definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named _proto_
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to _proto_.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
Object.freeze (Object.prototype)
. - Require schema validation of JSON input.
- Avoid using unsafe recursive merge functions.
- Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution. - As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade minimist
to version 1.2.6 or higher.
References
low severity
- Vulnerable module: ms
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › body-parser@1.12.2 › debug@2.1.3 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › debug@2.1.3 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › body-parser@1.12.2 › debug@2.1.3 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › finalhandler@0.3.4 › debug@2.1.3 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › debug@2.1.3 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › debug@2.1.3 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › finalhandler@0.3.4 › debug@2.1.3 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › send@0.12.2 › debug@2.1.3 › ms@0.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › ms@0.7.1Remediation: Open PR to patch ms@0.7.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › debug@2.2.0 › ms@0.7.1Remediation: Open PR to patch ms@0.7.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › ms@0.7.1Remediation: Open PR to patch ms@0.7.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › express@4.12.3 › serve-static@1.9.3 › send@0.12.3 › debug@2.2.0 › ms@0.7.1Remediation: Open PR to patch ms@0.7.1.
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › mocha@2.2.5 › debug@2.0.0 › ms@0.6.2
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › mocha@2.2.5 › debug@2.0.0 › ms@0.6.2
Overview
ms
is a tiny millisecond conversion utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an incomplete fix for previously reported vulnerability npm:ms:20151024. The fix limited the length of accepted input string to 10,000 characters, and turned to be insufficient making it possible to block the event loop for 0.3 seconds (on a typical laptop) with a specially crafted string passed to ms()
function.
Proof of concept
ms = require('ms');
ms('1'.repeat(9998) + 'Q') // Takes about ~0.3s
Note: Snyk's patch for this vulnerability limits input length to 100 characters. This new limit was deemed to be a breaking change by the author. Based on user feedback, we believe the risk of breakage is very low, while the value to your security is much greater, and therefore opted to still capture this change in a patch for earlier versions as well. Whenever patching security issues, we always suggest to run tests on your code to validate that nothing has been broken.
For more information on Regular Expression Denial of Service (ReDoS)
attacks, go to our blog.
Disclosure Timeline
- Feb 9th, 2017 - Reported the issue to package owner.
- Feb 11th, 2017 - Issue acknowledged by package owner.
- April 12th, 2017 - Fix PR opened by Snyk Security Team.
- May 15th, 2017 - Vulnerability published.
- May 16th, 2017 - Issue fixed and version
2.0.0
released. - May 21th, 2017 - Patches released for versions
>=0.7.1, <=1.0.0
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ms
to version 2.0.0 or higher.
References
low severity
- Vulnerable module: validator
- Introduced through: vigour-wrapper@2.2.36 and vigour-env@1.0.23
Detailed paths
-
Introduced through: vigour-statusbar@1.0.12 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
-
Introduced through: vigour-statusbar@1.0.12 › vigour-env@1.0.23 › vigour-wrapper@2.2.36 › vigour-shutter@2.0.25 › express-validator@2.21.0 › validator@5.7.0
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\s*data:([a-z]+\/[a-z0-9\-\+]+(;[a-z\-]+=[a-z0-9\-]+)?)?(;base64)?,[a-z0-9!\$&',\(\)\*\+,;=\-\._~:@\/\?%\s]*\s*$
) in order to validate Data URIs. This can cause an impact of about 10 seconds matching time for data 70K 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 18th, 2018 - Vulnerability published
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 9.4.1 or higher.