Find, fix and prevent vulnerabilities in your code.

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when including two parameters ending with - in a single segment, which causes inefficient backtracking when parsing the string into a regular expression. The resulting poor performance can lead to denial of service.

Note:

This vulnerability is similar to the path-to-regexp ReDoS Vulnerability

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 find-my-way to version 8.2.2, 9.0.1 or higher.

References

• Blog Post
• GitHub Commit
• GitHub Commit
• Red Hat Bugzilla Bug

Overview

apollo-server-core is a core module of the Apollo community GraphQL Server.

Affected versions of this package are vulnerable to Information Exposure in the request handling process. An attacker can infer sensitive information about server responses by issuing specially crafted authenticated GraphQL queries across origins using a browser with a specific CORS implementation bug, allowing them to analyze response times and deduce facts such as whether fields return null or the approximate number of list entries returned from fields.

Note:

This is only exploitable if the server relies on cookies or HTTP Basic Auth for authentication and the attack is performed from a browser affected by the CORS bug.

Workaround

This vulnerability can be mitigated by blocking any HTTP request with a Content-Type header containing message/ from reaching the server, for example by adding middleware or a proxy rule to reject such requests.

Remediation

A fix was pushed into the master branch but not yet published.

References

• GitHub Advisory
• GitHub Commit
• GitHub Release

Overview

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) via the cookie name, path, or domain, which can be used to set unexpected values to other cookie fields.

Workaround

Users who are not able to upgrade to the fixed version should avoid passing untrusted or arbitrary values for the cookie fields and ensure they are set by the application instead of user input.

Details

Cross-site scripting (or XSS) is a code vulnerability that occurs when an attacker “injects” a malicious script into an otherwise trusted website. The injected script gets downloaded and executed by the end user’s browser when the user interacts with the compromised website.

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 cookie to version 0.7.0 or higher.

References

• GitHub Commit
• GitHub PR
• Red Hat Bugzilla Bug

Overview

fastify is an overhead web framework, for Node.js.

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling via the sendWebStream function. An attacker can cause excessive memory consumption by sending a slow or non-reading client request, leading to unbounded buffering and severe performance degradation or process crashes.

Note: Only applications that return a ReadableStream (or Response with a Web Stream body) via reply.send() are impacted

Workaround

This vulnerability can be mitigated by avoiding Fastify Web Streams in responses and instead using Node.js streams or buffered payloads.

Remediation

Upgrade fastify to version 5.7.3 or higher.

References

• GitHub Advisory
• GitHub Commit

Overview

fastify is an overhead web framework, for Node.js.

Affected versions of this package are vulnerable to Use of Less Trusted Source in the request.protocol and request.host getters. An attacker can manipulate the perceived protocol and host by sending crafted X-Forwarded-Proto and X-Forwarded-Host headers after bypassing the proxy and connecting directly to the application port, potentially impacting security decisions such as HTTPS enforcement, secure cookie flags, CSRF origin checks, URL construction, or host-based routing.

Note: This is only exploitable if the application uses the trustProxy option with a restrictive trust function and relies on request.protocol or request.host for security decisions, and the attacker is able to connect directly to the application, bypassing the proxy.

Remediation

Upgrade fastify to version 5.8.3 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Release
• Red Hat Bugzilla Bug
• Vendor Advisory