Coveralls version 3.0.5 represents a subtle but important update to the code coverage reporting tool, building on the foundation of version 3.0.4. Both versions share the core functionality of accepting JSON-cov output via stdin and transmitting it to Coveralls.io, enabling developers to easily monitor and manage their project's test coverage. Key dependencies like growl, lcov-parse, log-driver, minimist, and request remain consistent, ensuring a stable operational environment for core tasks like notifications, LCOV data handling, logging, argument parsing, and HTTP requests. However, one important difference emerges in the js-yaml dependency. Version 3.0.5 upgrades to js-yaml version ^3.13.1, while version 3.0.4 uses ^3.11.0. This likely addresses bug fixes, performance improvements, or security vulnerabilities within the YAML parsing library, which is crucial for configuration file handling.
From a development perspective, the most noticeable change lies in the updated mocha version, moving from ^6.0.1 to ^6.1.4. This suggests enhancements or bug fixes within the testing framework that could improve test execution or reporting accuracy in version 3.0.5. The unpacked size also sees a slight increase from 78444 to 80034, implying addition of new features, library upgrades or new tests. The release date shows the more recent 3.0.5 version was released on July 12, 2019, about a month after the June 5, 2019 release of version 3.0.4. Developers incorporating Coveralls into their CI/CD pipelines should consider upgrading to version 3.0.5 to benefit from the latest improvements in its dependencies and testing framework, ultimately resulting in cleaner, more robust code coverage analysis.
All the vulnerabilities related to the version 3.0.5 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.