How we took malware advisories beyond npm

A compromised package can steal credentials the moment you install it, and until recently, GitHub could only flag those in npm. Not anymore. This is the story of how the supply chain engineering team behind Dependabot expanded malware advisories to eight ecosystems by building on OpenSSF’s shared malicious packages data. Here’s where things stand: earlier this year, Dependabot started flagging malware in your npm dependencies . Great news if you write JavaScript. Now we’re bringing that same functionality to PyPI. We’ve enhanced the GitHub Advisory Database to ingest malware reports from OpenSSF’s malicious-packages repository , which means malware advisories and the Dependabot alerts they power cover all eight major package ecosystems: npm, PyPI, Maven, RubyGems, NuGet, Go, crates.io, and PHP Composer. I lead the Dependabot team in GitHub’s supply chain security organization, and in this post, I’ll show you how this pipeline works. From one ecosystem to eight The Advisory Database has imported vulnerability data from external sources for years. RubySec for gems, RustSec for crates, PyPA for Python. Each one is an importer that reads a public advisory repo and maps records into our database. Malware was the odd one out: it flowed through a separate, internal, npm-only path, built around GitHub’s own detection of malicious npm packages. Expanding the existing detection from one to eight supported ecosystems would have taken us years. Meanwhile, OpenSSF has already solved the aggregation problem for everybody. Their malicious-packages repo launched in 2023, with over 15,000 reports in OSV format. Since then, it has grown every day, fed by community submissions and automated detection sources across the industry: typosquats, dependency-confusion packages, account takeovers, malicious prebuilt binaries. It’s public, it’s structured, and it covers any ecosystem the OSV schema supports. So, the design nearly wrote itself. Rather than building eight unique detection system