> Attackers targeted a wide variety of repositories, many of which had PyPI tokens stored as GitHub secrets, modifying their workflows to send those tokens to external servers. While the attackers successfully exfiltrated some tokens, they do not appear to have used them on PyPI.
It's wild to me that people entrust a third-party CI system with API secrets, and then also entrust that same system to run "actions" provided by other third parties.
Incident report of a recent attack campaign targeting GitHub Actions workflows to exfiltrate PyPI tokens, our response, and steps to protect your projects.
While Python being more widely used than JS, it's interesting the majority of attacks and breaches come from NPM. The consensus seems to be that Python offering a standard library greatly reduces the attack surface over JS. I tend to agree with this, a decently large Flask python app I am working on has 15 entries in requirements.txt (many of which being Flask plugins).
The large attack surface with npm is partly because of all the transitive dependencies used, which means that even if you only pull in a dozen packages directly, you're also using hundreds of other packages. Running `pip freeze` will list a lot of transitive dependencies as well, but I'm sure it'll be less than an equivalent JS project.
> Attackers targeted a wide variety of repositories, many of which had PyPI tokens stored as GitHub secrets, modifying their workflows to send those tokens to external servers. While the attackers successfully exfiltrated some tokens, they do not appear to have used them on PyPI.
It's wild to me that people entrust a third-party CI system with API secrets, and then also entrust that same system to run "actions" provided by other third parties.
Incident report of a recent attack campaign targeting GitHub Actions workflows to exfiltrate PyPI tokens, our response, and steps to protect your projects.
While Python being more widely used than JS, it's interesting the majority of attacks and breaches come from NPM. The consensus seems to be that Python offering a standard library greatly reduces the attack surface over JS. I tend to agree with this, a decently large Flask python app I am working on has 15 entries in requirements.txt (many of which being Flask plugins).
The large attack surface with npm is partly because of all the transitive dependencies used, which means that even if you only pull in a dozen packages directly, you're also using hundreds of other packages. Running `pip freeze` will list a lot of transitive dependencies as well, but I'm sure it'll be less than an equivalent JS project.