Find, fix and prevent vulnerabilities in your code.
critical severity
- Vulnerable module: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.1.0.
Overview
handlebars is an extension to the Mustache templating language.
Affected versions of this package are vulnerable to Prototype Pollution. It is possible to add or modify properties to the Object prototype through a malicious template. This may allow attackers to crash the application or execute Arbitrary Code in specific conditions.
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 mergeProperty 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 handlebars
to version 3.0.8, 4.5.3 or higher.
References
high severity
- Vulnerable module: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.1.0.
Overview
handlebars is an extension to the Mustache templating language.
Affected versions of this package are vulnerable to Arbitrary Code Execution. The package's lookup helper doesn't validate templates correctly, allowing attackers to submit templates that execute arbitrary JavaScript in the system.
PoC
{{#with split as |a|}}
{{pop (push "alert('Vulnerable Handlebars JS');")}}
{{#with (concat (lookup join (slice 0 1)))}}
{{#each (slice 2 3)}}
{{#with (apply 0 a)}}
{{.}}
{{/with}}
{{/each}}
{{/with}}
{{/with}}
{{/with}}
Remediation
Upgrade handlebars
to version 3.0.8, 4.5.3 or higher.
References
high severity
- Vulnerable module: bl
- Introduced through: request@2.74.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › bl@1.1.2Remediation: Upgrade to request@2.76.0.
Overview
bl is a library that allows you to collect buffers and access with a standard readable buffer interface.
Affected versions of this package are vulnerable to Remote Memory Exposure. If user input ends up in consume()
argument and can become negative, BufferList state can be corrupted, tricking it into exposing uninitialized memory via regular .slice()
calls.
PoC by chalker
const { BufferList } = require('bl')
const secret = require('crypto').randomBytes(256)
for (let i = 0; i < 1e6; i++) {
const clone = Buffer.from(secret)
const bl = new BufferList()
bl.append(Buffer.from('a'))
bl.consume(-1024)
const buf = bl.slice(1)
if (buf.indexOf(clone) !== -1) {
console.error(`Match (at ${i})`, buf)
}
}
Remediation
Upgrade bl
to version 2.2.1, 3.0.1, 4.0.3, 1.2.3 or higher.
References
high severity
- Vulnerable module: ansi-regex
- Introduced through: request@2.74.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › har-validator@2.0.6 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › har-validator@2.0.6 › chalk@1.1.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the sub-patterns [[\\]()#;?]*
and (?:;[-a-zA-Z\\d\\/#&.:=?%@~_]*)*
.
PoC
import ansiRegex from 'ansi-regex';
for(var i = 1; i <= 50000; i++) {
var time = Date.now();
var attack_str = "\u001B["+";".repeat(i*10000);
ansiRegex().test(attack_str)
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- 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 ansi-regex
to version 3.0.1, 4.1.1, 5.0.1, 6.0.1 or higher.
References
high severity
- Vulnerable module: fresh
- Introduced through: express@4.14.0 and serve-favicon@2.2.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › serve-favicon@2.2.1 › fresh@0.2.4Remediation: Upgrade to serve-favicon@2.4.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › serve-favicon@2.2.1 › fresh@0.2.4Remediation: Upgrade to serve-favicon@2.4.5.
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: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.1.0.
Overview
handlebars is an extension to the Mustache templating language.
Affected versions of this package are vulnerable to Denial of Service (DoS). The package's parser may be forced into an endless loop while processing specially-crafted templates, which may allow attackers to exhaust system resources leading to Denial of Service.
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 handlebars
to version 4.4.5 or higher.
References
high severity
- Vulnerable module: markdown-it
- Introduced through: markdown-it@6.0.5
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › markdown-it@6.0.5Remediation: Upgrade to markdown-it@13.0.2.
Overview
markdown-it is a modern pluggable markdown parser.
Affected versions of this package are vulnerable to Infinite loop in linkify inline rule when using malformed input.
Remediation
Upgrade markdown-it
to version 13.0.2 or higher.
References
high severity
- Vulnerable module: moment
- Introduced through: moment@2.15.2
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › moment@2.15.2Remediation: Upgrade to moment@2.29.2.
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Directory Traversal when a user provides a locale string which is directly used to switch moment locale.
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 moment
to version 2.29.2 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: body-parser@1.12.4 and express@4.14.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › body-parser@1.12.4 › qs@2.4.2Remediation: Upgrade to body-parser@1.17.1.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › qs@6.2.0Remediation: Upgrade to express@4.15.2.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › body-parser@1.12.4 › qs@2.4.2Remediation: Upgrade to body-parser@1.17.1.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › qs@6.2.0Remediation: Upgrade to express@4.15.2.
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
Upgrade qs
to version 6.0.4, 6.1.2, 6.2.3, 6.3.2 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: body-parser@1.12.4 and express@4.14.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › body-parser@1.12.4 › qs@2.4.2Remediation: Upgrade to body-parser@1.19.2.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › qs@6.2.0Remediation: Upgrade to express@4.17.3.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Prototype Poisoning which allows attackers to cause a Node process to hang, processing an Array object whose prototype has been replaced by one with an excessive length value.
Note: In many typical Express use cases, an unauthenticated remote attacker can place the attack payload in the query string of the URL that is used to visit the application, such as a[__proto__]=b&a[__proto__]&a[length]=100000000
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade qs
to version 6.2.4, 6.3.3, 6.4.1, 6.5.3, 6.6.1, 6.7.3, 6.8.3, 6.9.7, 6.10.3 or higher.
References
high severity
- Vulnerable module: hawk
- Introduced through: request@2.74.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › hawk@3.1.3Remediation: Upgrade to request@2.87.0.
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
Upgrade hawk
to version 9.0.1 or higher.
References
high severity
- Vulnerable module: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.0.2.
Overview
handlebars is an extension to the Mustache templating language.
Affected versions of this package are vulnerable to Prototype Pollution. Templates may alter an Objects' prototype, thus allowing an attacker to execute arbitrary code on the server.
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 mergeProperty 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
Web browser
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 handlebars
to version 3.0.7, 4.0.13, 4.1.2 or higher.
References
high severity
- Vulnerable module: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.0.4.
Overview
handlebars is an extension to the Mustache templating language.
Affected versions of this package are vulnerable to Prototype Pollution. A Prototype Pollution allowing Remote Code Execution can be exploited using the constructor, via the 'lookup' helper.
This vulnerability is due to an incomplete fix for: SNYK-JS-HANDLEBARS-173692
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 mergeProperty 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
Web browser
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 handlebars
to version 3.0.7, 4.1.2, 4.0.14 or higher.
References
high severity
- Vulnerable module: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.0.5.
Overview
handlebars is a extension to the Mustache templating language.
Affected versions of this package are vulnerable to Prototype Pollution.
Templates may alter an Object's __proto__
and __defineGetter__
properties, which may allow an attacker to execute arbitrary code on the server through crafted payloads.
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 mergeProperty 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 handlebars
to version 4.3.0, 3.0.8 or higher.
References
high severity
- Vulnerable module: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.1.2.
Overview
handlebars is an extension to the Mustache templating language.
Affected versions of this package are vulnerable to Remote Code Execution (RCE) when selecting certain compiling options to compile templates coming from an untrusted source.
POC
<script src="https://cdn.jsdelivr.net/npm/handlebars@latest/dist/handlebars.js"></script>
<script>
// compile the template
var s = `
{{#with (__lookupGetter__ "__proto__")}}
{{#with (./constructor.getOwnPropertyDescriptor . "valueOf")}}
{{#with ../constructor.prototype}}
{{../../constructor.defineProperty . "hasOwnProperty" ..}}
{{/with}}
{{/with}}
{{/with}}
{{#with "constructor"}}
{{#with split}}
{{pop (push "alert('Vulnerable Handlebars JS when compiling in strict mode');")}}
{{#with .}}
{{#with (concat (lookup join (slice 0 1)))}}
{{#each (slice 2 3)}}
{{#with (apply 0 ../..)}}
{{.}}
{{/with}}
{{/each}}
{{/with}}
{{/with}}
{{/with}}
{{/with}}
`;
var template = Handlebars.compile(s, {
strict: true
});
// execute the compiled template and print the output to the console console.log(template({}));
</script>
Remediation
Upgrade handlebars
to version 4.7.7 or higher.
References
medium severity
- Vulnerable module: morgan
- Introduced through: morgan@1.5.3
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › morgan@1.5.3Remediation: Upgrade to morgan@1.9.1.
Overview
morgan is a HTTP request logger middleware for node.js.
Affected versions of this package are vulnerable to Arbitrary Code Injection. An attacker could use the format parameter to inject arbitrary commands.
Remediation
Upgrade morgan
to version 1.9.1 or higher.
References
medium severity
- Vulnerable module: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.1.1.
Overview
handlebars is an extension to the Mustache templating language.
Affected versions of this package are vulnerable to Prototype Pollution. Prototype access to the template engine allows for potential code execution.
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 handlebars
to version 4.6.0 or higher.
References
medium severity
- Vulnerable module: request
- Introduced through: request@2.74.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0
Overview
request is a simplified http request client.
Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to insufficient checks in the lib/redirect.js
file by allowing insecure redirects in the default configuration, via an attacker-controller server that does a cross-protocol redirect (HTTP to HTTPS, or HTTPS to HTTP).
NOTE: request
package has been deprecated, so a fix is not expected. See https://github.com/request/request/issues/3142.
Remediation
A fix was pushed into the master
branch but not yet published.
References
medium severity
- Vulnerable module: tough-cookie
- Introduced through: request@2.74.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › tough-cookie@2.3.4
Overview
tough-cookie is a RFC6265 Cookies and CookieJar module for Node.js.
Affected versions of this package are vulnerable to Prototype Pollution due to improper handling of Cookies when using CookieJar in rejectPublicSuffixes=false
mode. Due to an issue with the manner in which the objects are initialized, an attacker can expose or modify a limited amount of property information on those objects. There is no impact to availability.
PoC
// PoC.js
async function main(){
var tough = require("tough-cookie");
var cookiejar = new tough.CookieJar(undefined,{rejectPublicSuffixes:false});
// Exploit cookie
await cookiejar.setCookie(
"Slonser=polluted; Domain=__proto__; Path=/notauth",
"https://__proto__/admin"
);
// normal cookie
var cookie = await cookiejar.setCookie(
"Auth=Lol; Domain=google.com; Path=/notauth",
"https://google.com/"
);
//Exploit cookie
var a = {};
console.log(a["/notauth"]["Slonser"])
}
main();
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 mergeProperty 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
Web browser
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 tough-cookie
to version 4.1.3 or higher.
References
medium severity
- Vulnerable module: json5
- Introduced through: config@1.19.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › config@1.19.0 › json5@0.4.0Remediation: Upgrade to config@1.31.0.
Overview
Affected versions of this package are vulnerable to Prototype Pollution via the parse
method , which does not restrict parsing of keys named __proto__
, allowing specially crafted strings to pollute the prototype of the resulting object. This pollutes the prototype of the object returned by JSON5.parse
and not the global Object prototype (which is the commonly understood definition of Prototype Pollution). Therefore, the actual impact will depend on how applications utilize the returned object and how they filter unwanted keys.
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 mergeProperty 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
Web browser
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 json5
to version 1.0.2, 2.2.2 or higher.
References
medium severity
- Vulnerable module: hoek
- Introduced through: request@2.74.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › hawk@3.1.3 › hoek@2.16.3Remediation: Upgrade to request@2.82.0.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › hawk@3.1.3 › boom@2.10.1 › hoek@2.16.3Remediation: Upgrade to request@2.82.0.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › hawk@3.1.3 › sntp@1.0.9 › hoek@2.16.3Remediation: Upgrade to request@2.82.0.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › hawk@3.1.3 › cryptiles@2.0.5 › boom@2.10.1 › hoek@2.16.3Remediation: Upgrade to request@2.82.0.
Overview
hoek is an Utility methods for the hapi ecosystem.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- 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: express
- Introduced through: express@4.14.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0Remediation: Upgrade to express@4.19.2.
Overview
express is a minimalist web framework.
Affected versions of this package are vulnerable to Open Redirect due to the implementation of URL encoding using encodeurl
before passing it to the location
header. This can lead to unexpected evaluations of malformed URLs by common redirect allow list implementations in applications, allowing an attacker to bypass a properly implemented allow list and redirect users to malicious sites.
Remediation
Upgrade express
to version 4.19.2, 5.0.0-beta.3 or higher.
References
medium severity
- Vulnerable module: handlebars
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5Remediation: Upgrade to hbs@4.1.2.
Overview
handlebars is an extension to the Mustache templating language.
Affected versions of this package are vulnerable to Prototype Pollution when selecting certain compiling options to compile templates coming from an untrusted source.
POC
<script src="https://cdn.jsdelivr.net/npm/handlebars@latest/dist/handlebars.js"></script>
<script>
// compile the template
var s2 = `{{'a/.") || alert("Vulnerable Handlebars JS when compiling in compat mode'}}`;
var template = Handlebars.compile(s2, {
compat: true
});
// execute the compiled template and print the output to the console console.log(template({}));
</script>
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 mergeProperty 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
Web browser
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 handlebars
to version 4.7.7 or higher.
References
medium severity
- Vulnerable module: minimist
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5 › optimist@0.6.1 › minimist@0.0.10
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 mergeProperty 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
Web browser
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: markdown-it
- Introduced through: markdown-it@6.0.5
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › markdown-it@6.0.5Remediation: Upgrade to markdown-it@12.3.2.
Overview
markdown-it is a modern pluggable markdown parser.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the /s+$/
in line 23 of lib/rules_inline/newline.js
. This expression is used to remove trailing whitespaces from a string, however, it also matches non-trailing whitespaces.
In the worst-case scenario, the matching process would take computation time proportional to the square of the length of the non-trailing whitespaces. It is possible that a string containing more than tens of thousands characters, as markdown-it
handles Markdown
, would be passed over the network, resulting in significant computational time.
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 markdown-it
to version 12.3.2 or higher.
References
medium severity
- Vulnerable module: markdown-it
- Introduced through: markdown-it@6.0.5
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › markdown-it@6.0.5Remediation: Upgrade to markdown-it@10.0.0.
Overview
markdown-it is a modern pluggable markdown parser.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). Parsing _*… takes quadratic time, this could be a denial of service vulnerability in an application that parses user input.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade markdown-it
to version 10.0.0 or higher.
References
medium severity
- Vulnerable module: uglify-js
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5 › uglify-js@2.8.29Remediation: Upgrade to hbs@4.0.2.
Overview
uglify-js is a JavaScript parser, minifier, compressor and beautifier toolkit.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the string_template
and the decode_template
functions.
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 uglify-js
to version 3.14.3 or higher.
References
medium severity
- Vulnerable module: tunnel-agent
- Introduced through: request@2.74.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › request@2.74.0 › tunnel-agent@0.4.3Remediation: Upgrade to request@2.81.0.
Overview
tunnel-agent
is HTTP proxy tunneling agent. Affected versions of the package are vulnerable to Uninitialized Memory Exposure.
A possible memory disclosure vulnerability exists when a value of type number
is used to set the proxy.auth option of a request request
and results in a possible uninitialized memory exposures in the request body.
This is a result of unobstructed use of the Buffer
constructor, whose insecure default constructor increases the odds of memory leakage.
Details
Constructing a Buffer
class with integer N
creates a Buffer
of length N
with raw (not "zero-ed") memory.
In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":
// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');
tunnel-agent
's request
construction uses the default Buffer
constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed
flaw in OpenSSL.
Proof of concept by ChALkeR
require('request')({
method: 'GET',
uri: 'http://www.example.com',
tunnel: true,
proxy:{
protocol: 'http:',
host:"127.0.0.1",
port:8080,
auth:80
}
});
You can read more about the insecure Buffer
behavior on our blog.
Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.
Remediation
Upgrade tunnel-agent
to version 0.6.0 or higher.
Note This is vulnerable only for Node <=4
References
low severity
- Vulnerable module: debug
- Introduced through: debug@2.2.0, body-parser@1.12.4 and others
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › debug@2.2.0Remediation: Upgrade to debug@2.6.9.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › body-parser@1.12.4 › debug@2.2.0Remediation: Upgrade to body-parser@1.18.2.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › morgan@1.5.3 › debug@2.2.0Remediation: Upgrade to morgan@1.9.0.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › finalhandler@0.5.0 › debug@2.2.0Remediation: Upgrade to express@4.15.0.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
Overview
debug is a small debugging utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the function useColors
via manipulation of the str
argument.
The vulnerability can cause a very low impact of about 2 seconds of matching time for data 50k characters long.
Note: CVE-2017-20165 is a duplicate of this vulnerability.
PoC
Use the following regex in the %o
formatter.
/\s*\n\s*/
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, 3.2.7, 4.3.1 or higher.
References
low severity
- Vulnerable module: mime
- Introduced through: express@4.14.0
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
Overview
mime is a comprehensive, compact MIME type module.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It uses regex the following regex /.*[\.\/\\]/
in its lookup, which can cause a slowdown of 2 seconds for 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade mime
to version 1.4.1, 2.0.3 or higher.
References
low severity
- Vulnerable module: minimist
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1 › handlebars@4.0.5 › optimist@0.6.1 › minimist@0.0.10
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 mergeProperty 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
Web browser
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 0.2.4, 1.2.6 or higher.
References
low severity
- Vulnerable module: moment
- Introduced through: moment@2.15.2
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › moment@2.15.2Remediation: Upgrade to moment@2.19.3.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › moment@2.15.2Remediation: Upgrade to moment@2.19.3.
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (/[0-9]*['a-z\u00A0-\u05FF\u0700-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]+|[\u0600-\u06FF\/]+(\s*?[\u0600-\u06FF]+){1,2}/i
) in order to parse dates specified as strings. 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 moment
to version 2.19.3 or higher.
References
low severity
- Vulnerable module: ms
- Introduced through: debug@2.2.0, serve-favicon@2.2.1 and others
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to debug@2.6.7.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › serve-favicon@2.2.1 › ms@0.7.1Remediation: Upgrade to serve-favicon@2.4.3.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › body-parser@1.12.4 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to body-parser@1.17.2.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › morgan@1.5.3 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to morgan@1.8.2.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › finalhandler@0.5.0 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.0.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › ms@0.7.2Remediation: Upgrade to express@4.15.3.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to debug@2.6.7.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › serve-favicon@2.2.1 › ms@0.7.1Remediation: Upgrade to serve-favicon@2.4.3.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › body-parser@1.12.4 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to body-parser@1.17.2.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › morgan@1.5.3 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to morgan@1.8.2.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › finalhandler@0.5.0 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.0.
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Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › send@0.14.1 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › express@4.14.0 › serve-static@1.11.2 › send@0.14.2 › ms@0.7.2Remediation: Upgrade to express@4.15.3.
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: hbs
- Introduced through: hbs@4.0.1
Detailed paths
-
Introduced through: glib-mock@cloudspokes/GLIB-mock#d7b056d64dee7c6d44d7e42b7accacc709466f5e › hbs@4.0.1
Overview
hbs is an Express.js template engine plugin for Handlebars
Affected versions of this package are vulnerable to Information Exposure. hbs
mixes pure template data with engine configuration options through the Express
render API. By overwriting internal configuration options a file disclosure vulnerability may be triggered in downstream applications.
Remediation
There is no fixed version for hbs
.