Find, fix and prevent vulnerabilities in your code.

Overview

Affected versions of this package are vulnerable to Information Exposure due to the handling of the Proxy-Authorization header across hosts. When using a dependent library, it only clears the authorization header during cross-domain redirects but allows the proxy-authentication header, which contains credentials, to persist. This behavior may lead to the unintended leakage of credentials if an attacker can trigger a cross-domain redirect and capture the persistent proxy-authentication header.

PoC

const axios = require('axios');

axios.get('http://127.0.0.1:10081/',{
headers: {
'AuThorization': 'Rear Test',
'ProXy-AuthoriZation': 'Rear Test',
'coOkie': 't=1'
}
}).then(function (response) {
console.log(response);
})

Remediation

Upgrade follow-redirects to version 1.15.6 or higher.

References

• GitHub Commit
• RedHat Bugzilla Bug

Overview

graphql-playground-html is a GraphQL IDE for better development workflows (GraphQL Subscriptions, interactive docs & collaboration).

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) via the renderPlaygroundPage() function.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Affected environments

The following environments are susceptible to an XSS attack:

• Web servers
• Application servers
• Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

• Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
• Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
• Give users the option to disable client-side scripts.
• Redirect invalid requests.
• Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
• Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
• Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

Upgrade graphql-playground-html to version 1.6.22 or higher.

References

• Exploit Code
• GitHub Commit

Overview

node-fetch is a light-weight module that brings window.fetch to node.js

Affected versions of this package are vulnerable to Information Exposure when fetching a remote url with Cookie, if it get a Location response header, it will follow that url and try to fetch that url with provided cookie. This can lead to forwarding secure headers to 3th party.

Remediation

Upgrade node-fetch to version 2.6.7, 3.1.1 or higher.

References

• Github Commit
• GitHub Commit
• GitHub Commit
• GitHub PR

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

• GitHub Commit
• GitHub Issue
• GitHub PR

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 merge

• Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

• Application server

• Web server

• Web browser

How to prevent

1. Freeze the prototype— use Object.freeze (Object.prototype).

2. Require schema validation of JSON input.

3. Avoid using unsafe recursive merge functions.

4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

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

Remediation

Upgrade tough-cookie to version 4.1.3 or higher.

References

• GitHub Commit
• GitHub Issue
• GitHub Release

Overview

Affected versions of this package are vulnerable to Missing Release of Resource after Effective Lifetime via the makeres function due to improperly deleting keys from the reqs object after execution of callbacks. This behavior causes the keys to remain in the reqs object, which leads to resource exhaustion.

Exploiting this vulnerability results in crashing the node process or in the application crash.

Note: This library is not maintained, and currently, there is no fix for this issue. To overcome this vulnerability, several dependent packages have eliminated the use of this library.

To trigger the memory leak, an attacker would need to have the ability to execute or influence the asynchronous operations that use the inflight module within the application. This typically requires access to the internal workings of the server or application, which is not commonly exposed to remote users. Therefore, “Attack vector” is marked as “Local”.

PoC

const inflight = require('inflight');

function testInflight() {
  let i = 0;
  function scheduleNext() {
    let key = `key-${i++}`;
    const callback = () => {
    };
    for (let j = 0; j < 1000000; j++) {
      inflight(key, callback);
    }

    setImmediate(scheduleNext);
  }


  if (i % 100 === 0) {
    console.log(process.memoryUsage());
  }

  scheduleNext();
}

testInflight();

Remediation

There is no fixed version for inflight.

References

• GitHub Issue
• GitHub PR

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Server-Side Request Forgery (SSRF). An attacker is able to bypass a proxy by providing a URL that responds with a redirect to a restricted host or IP address.

Remediation

Upgrade axios to version 0.21.1 or higher.

References

• GitHub Commit
• GitHub Issue
• GitHub Security Advisory
• NPM Advisory

Overview

node-fetch is a light-weight module that brings window.fetch to node.js

Affected versions of this package are vulnerable to Denial of Service. Node Fetch did not honor the size option after following a redirect, which means that when a content size was over the limit, a FetchError would never get thrown and the process would end without failure.

Remediation

Upgrade node-fetch to version 2.6.1, 3.0.0-beta.9 or higher.

References

• GitHub Advisory
• GitHub Commit

Overview

yargs-parser is a mighty option parser used by yargs.

Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype using a __proto__ payload.

Our research team checked several attack vectors to verify this vulnerability:

1. It could be used for privilege escalation.
2. The library could be used to parse user input received from different sources:
   • terminal emulators
   • system calls from other code bases
   • CLI RPC servers

PoC by Snyk

const parser = require("yargs-parser");
console.log(parser('--foo.__proto__.bar baz'));
console.log(({}).bar);

Details

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

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

• Unsafe Object recursive merge

• Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

• Application server

• Web server

• Web browser

How to prevent

1. Freeze the prototype— use Object.freeze (Object.prototype).

2. Require schema validation of JSON input.

3. Avoid using unsafe recursive merge functions.

4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

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

Remediation

Upgrade yargs-parser to version 5.0.1, 13.1.2, 15.0.1, 18.1.1 or higher.

References

• Command Injection PoC
• GitHub Fix Commit
• Snyk Research Blog

Overview

yup is a Dead simple Object schema validation

Affected versions of this package are vulnerable to Prototype Pollution via the .SetLocale function.

PoC

let yup = require('yup');
const payload = JSON.parse('{"__proto__":{"polluted":"Yes! Its Polluted"}}');
yup.setLocale(payload);
console.log({}.polluted)

Details

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

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

• Unsafe Object recursive merge

• Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

• Application server

• Web server

• Web browser

How to prevent

1. Freeze the prototype— use Object.freeze (Object.prototype).

2. Require schema validation of JSON input.

3. Avoid using unsafe recursive merge functions.

4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

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

Remediation

Upgrade yup to version 0.30.0 or higher.

References

• GitHub Commit
• GitHub PR

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). An attacker can deplete system resources by providing a manipulated string as input to the format method, causing the regular expression to exhibit a time complexity of O(n^2). This makes the server to become unable to provide normal service due to the excessive cost and time wasted in processing vulnerable regular expressions.

PoC

const axios = require('axios');

console.time('t1');
axios.defaults.baseURL = '/'.repeat(10000) + 'a/';
axios.get('/a').then(()=>{}).catch(()=>{});
console.timeEnd('t1');

console.time('t2');
axios.defaults.baseURL = '/'.repeat(100000) + 'a/';
axios.get('/a').then(()=>{}).catch(()=>{});
console.timeEnd('t2');


/* stdout
t1: 60.826ms
t2: 5.826s
*/

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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 axios to version 1.6.3 or higher.

References

• GitHub Commit
• GitHub Issue
• GitHub PR

Overview

Affected versions of this package are vulnerable to Information Exposure by leaking the cookie header to a third party site in the process of fetching a remote URL with the cookie in the request body. If the response contains a location header, it will follow the redirect to another URL of a potentially malicious actor, to which the cookie would be exposed.

Remediation

Upgrade follow-redirects to version 1.14.7 or higher.

References

• GitHub Commit

Overview

highlight.js is a syntax highlighter written in JavaScript. It works in the browser as well as on the server. It works with pretty much any markup, doesn’t depend on any framework, and has automatic language detection.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via Exponential and Polynomial catastrophic backtracking in multiple language highlighting.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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 highlight.js to version 10.4.1 or higher.

References

• GitHub Commit

Overview

redis is an A high performance Redis client.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). When a client is in monitoring mode, monitor_regex, which is used to detected monitor messages` could cause exponential backtracking on some strings, 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:

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

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

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

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 redis to version 3.1.1 or higher.

References

• GitHub Commit
• GitHub Release

Overview

Affected versions of this package are vulnerable to Prototype Pollution due to allowing an external attacker to edit or add new properties to an object. This is possible because the application does not properly validate incoming JSON keys, thus allowing the __proto__ property to be edited.

PoC

var parseString = require('xml2js').parseString;

let normal_user_request    = "<role>admin</role>";
let malicious_user_request = "<__proto__><role>admin</role></__proto__>";

const update_user = (userProp) => {
    // A user cannot alter his role. This way we prevent privilege escalations.
    parseString(userProp, function (err, user) {
        if(user.hasOwnProperty("role") && user?.role.toLowerCase() === "admin") {
            console.log("Unauthorized Action");
        } else {
            console.log(user?.role[0]);
        }
    });
}

update_user(normal_user_request);
update_user(malicious_user_request);

Details

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

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

• Unsafe Object recursive merge

• Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

• Application server

• Web server

• Web browser

How to prevent

1. Freeze the prototype— use Object.freeze (Object.prototype).

2. Require schema validation of JSON input.

3. Avoid using unsafe recursive merge functions.

4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

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

Remediation

Upgrade xml2js to version 0.5.0 or higher.

References

• GitHub Commit
• GitHub Issue
• GitHub PR
• GitHub PR
• GitHub PR
• PoC

Overview

mem is an optimization used to speed up consecutive function calls by caching the result of calls with identical input.

Affected versions of this package are vulnerable to Denial of Service (DoS). Old results were deleted from the cache and could cause a memory leak.

details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

Upgrade mem to version 4.0.0 or higher.

References

• GitHub Commit

• GitHub Issue

Overview

ioredis is a Redis client for Node.js.

Affected versions of this package are vulnerable to Prototype Pollution. The reply transformer which is applied does not check for special field names. This only impacts applications that are directly allowing user-provided field names.

PoC

// Redis server running on localhost
const Redis = require("ioredis");
const client = new Redis();

async function f1() {
        await client.hset('test_key', ['__proto__', 'hello']);
        console.log('hget:', await client.hget('test_key', '__proto__')); // "hello"
        console.log('hgetall:', await client.hgetall('test_key')); // does not include __proto__: hello
}

f1();

Details

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

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

• Unsafe Object recursive merge

• Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

• Application server

• Web server

• Web browser

How to prevent

1. Freeze the prototype— use Object.freeze (Object.prototype).

2. Require schema validation of JSON input.

3. Avoid using unsafe recursive merge functions.

4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

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

Remediation

Upgrade ioredis to version 4.27.8 or higher.

References

• GitHub Commit
• GitHub Issue