notes VS packj

It's (partially) a fundamental problem with Python and most other programming languages. The majority of libraries don't need more authority than doing (some) computation, yet any Python script can access anything and everything by default.

https://en.wikipedia.org/wiki/Capability-based_security is the solution for this, yet Python will probably never be capable of this kind of internal encapsulation, it's too much of a fundamental change - and even if some sort of sandboxing ability is accomplished, creating separate/recursive sandboxes (needed when importing more, separate libraries) will probably require another interpreter instance (as with WebAssembly).

I hope current and future language designers will take this into account, and construct their compilers, virtual machines and interpreters accordingly. Python was created before the internet as we know it now existed, so perhaps its lack of security mechanisms shouldn't be surprising. But it and any new developments that fail to consider this aspect of computation will be fundamentally flawed from the beginning.

https://github.com/void4/notes/issues/41

Not if done correctly. Have a look at this link: https://github.com/void4/notes/issues/41

There is no issue with just limiting resources (unless there is unpredictable overhead). It doesn't have to be hardware resources either, it could be abstract/higher level resources like interpreter steps or managed memory slices.

I'm creating a series of VMs to show that this is possible, like rarVM, the recursively sandboxable virtual machine: https://esolangs.org/wiki/RarVM

Showcase: https://www.youtube.com/watch?v=MBymOp6bTII

When calling a function you can specify how many interpreter steps it can run until it aborts (and optionally gives you a continuation so you can "refill" and resume it later).

Stackless Python can do this too, but unfortunately due to the reasons discussed above will never be a safe language, this specific mechanism works only in trusted environments since the called function has the ambient authority to increase its own resource limits: https://stackless.readthedocs.io/en/2.7-slp/library/stackles...

Another approach would be to have a counter (or several) that limit the number of instruction steps, like the Stackless Python programming language (https://stackless.readthedocs.io/en/latest/library/stackless...) or the KeyKOS operating system (https://github.com/void4/notes/issues/41) did

Ann Hardy programmed one of the first mainframe operating systems, and certainly the most secure one: KeyKOS

There are syntactic and semantic aspects. Personally, I think algebraic effect systems and capability security seem to be very worthwhile areas of research because they provide abilities and guarantees that just aren't possible with currently popular languages due to their architecture.

This might be of interest to you: "Why KeyKOS is fascinating" - https://github.com/void4/notes/issues/41

Creator of Packj [1] here. How do you envision sandboxing/security policies will be specified? Per-lib policies when you've hundreds of dependencies will become overwhelming. Having built an eBPF-based sandbox [2], I anticipate that accuracy will be another challenge here: too restrictive will block functionality, too permissive defeats the purpose.

1. https://github.com/ossillate-inc/packj flags malicious/risky NPM/PyPI/RubyGems/Rust/Maven/PHP packages by carrying out static+dynamic+metadata analysis.

Cool project. How do you feel about projects like OpenSSF scorecards or even the checks that socket.dev do today on these packages to help determine risk?

https://github.com/ossillate-inc/packj/blob/main/.packj.yaml

Secondly, what about impersonation where attackers imitate a popular package and its respective metadata?

I built Packj [1] sandboxing for securing “pip/NPM install”. It uses strace for sandboxing and blocks access to sensitive files and limits traffic to known-good IP addresses.

1. https://github.com/ossillate-inc/packj

Great work! This provenance check is going to be very valuable for enforcing supply-chain security. We are working on adding support to check for provenance in Packj.

1. https://github.com/ossillate-inc/packj flags risky/malicious NPM/PyPI/Ruby dependencies

Cool project. Would love to integrate this in Packj [1] as one of the open-source SAST scanners. Will DM you.

1. https://github.com/ossillate-inc/packj flags malicious/risky open-source dependencies.

Very cool! I've built something similar, but for packages: https://github.com/ossillate-inc/packj Would love to talk.

Working on a marketplace (based on Packj [1]) to allow open-source developers to make money by selling "assured" software artifacts.

1. Packj https://github.com/ossillate-inc/packj flags malicious and other "risky" open-source dependencies in your software supply chain.

I’ve created Packj sandbox [1] for “safe installation” of PyPI/NPM/Rubygems packages

1. https://github.com/ossillate-inc/packj

It DOES NOT require a VM/Container; uses strace. It shows you a preview of file system changes that installation will make and can also block arbitrary network communication during installation (uses an allow-list).

Great to see a developer-friendly tool around OSV! Packj [1] uses OSV APIs to report vulnerable PyPI/NPM/Rubygems packages. Disclaimer: I built it.

1. https://github.com/ossillate-inc/packj flags malicious/risky packages.