Coveralls version 3.0.14 introduces a subtle yet crucial upgrade compared to its predecessor, version 3.0.13. Both versions serve the core function of processing code coverage data in JSON-cov format from standard input and transmitting it to the Coveralls.io service, enabling developers to easily track and improve their code coverage metrics. The primary difference lies within the dependencies. Version 3.0.14 upgrades the "request" dependency from version 2.88.0 to 2.88.2. "Jshint" is upgraded from version 2.10.3 to 2.11.0, and "mocha" package is upgraded from 6.2.2 to 6.2.3. This update within "request" likely resolves minor bugs or security vulnerabilities present in the older version, ensuring more reliable and secure data transmission. Developers leveraging coveralls should note this patch as it minimizes potential risks associated with outdated request libraries. Additionally, these versions share a common set of dependencies, including "js-yaml", "lcov-parse", "log-driver", and "minimist", which are fundamental for parsing coverage reports and managing command-line arguments. The "devDependencies" also indicate the tools used for development and testing, such as "nyc" for coverage reporting, "should" for assertions, "shx" for shell commands, and "sinon-restore" for test spies. The release date suggests active maintenance, reassuring users of the library's continued support and relevance in modern development workflows. In conclusion, opting for version 3.0.14 provides a marginally enhanced and secure experience for continuous integration and code coverage reporting.
All the vulnerabilities related to the version 3.0.14 of the package
Server-Side Request Forgery in Request
The request package through 2.88.2 for Node.js and the @cypress/request package prior to 3.0.0 allow a bypass of SSRF mitigations via an attacker-controller server that does a cross-protocol redirect (HTTP to HTTPS, or HTTPS to HTTP).
NOTE: The request package is no longer supported by the maintainer.
form-data uses unsafe random function in form-data for choosing boundary
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:
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.
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 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).
For an application to be vulnerable, it must:
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)If an application is vulnerable, this allows an attacker to make arbitrary requests to internal systems.
tough-cookie Prototype Pollution vulnerability
Versions of the package tough-cookie before 4.1.3 are vulnerable to Prototype Pollution due to improper handling of Cookies when using CookieJar in rejectPublicSuffixes=false mode. This issue arises from the manner in which the objects are initialized.