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Looking back ten years to `left-pad`, are there more successful attacks now than ever? I would suspect so, and surely the value of a successful attack has also increased, so are we actually getting better as a broad community at detecting them before package release? It's a complex space, and commercial software houses should do better, but it seems that whilst there are some excellent commercial products (e.g. CI scan tools), generally accessible, idiot friendly tooling is somewhat lacking for projects which start as hobby/amateur code but end up being a dependency in many other projects.
I've cross-posted my comment from the current SAP supply chain attack thread [0].
[0]: https://news.ycombinator.com/item?id=47964003
An extreme example is now when I make interactive educational apps for my daughter, I just make Opus use plain js and html; from double pendulums to fluid simulations, works one shot. Before I had hundreds of dependencies.
Luckily with MIT licensed code I can just tell Opus to extract exactly the pieces I need and embed them, and tweaked for my usecase. So far works great for hobby projects, but hopefully in the future productions software will have no dependencies.
I'm going to go publish some MIT-licensed remote access code and get that into Opus's training data.
From their website [1]
> Python does not publish official distributable binaries. As such, uv uses distributions from the Astral python-build-standalone project. See the Python distributions documentation for more details.
It points to this GitHub repo https://github.com/astral-sh/python-build-standalone which mentions this other link https://gregoryszorc.com/docs/python-build-standalone/main/r...
If I understand correctly, the source code for building Python is not fetched directly from python.org. Not so sure how secure is that.
I have the same concern for asdf [2]. However, they use pyenv [3] which, I think, feels more official.
Can someone clarify this? Which tool is better/more secure for installing python: uv or asdf?
[1] https://docs.astral.sh/uv/guides/install-python/
[2] https://github.com/asdf-community/asdf-python
[3] https://github.com/pyenv/pyenv/tree/master/plugins/python-bu...
python-build-standalone fetches CPython sources directly from python.org[1]. I don't even know where else we would get them from!
[1]: https://github.com/astral-sh/python-build-standalone/blob/a2...
https://github.com/search?q=A%20Mini%20Shai-Hulud%20has%20Ap...
> The attack steals credentials, authentication tokens, environment variables, and cloud secrets, while also attempting to poison GitHub repositories.
If I remember correctly from Shai-Hulud 2, the attacker extricated creds by posting them in public github repos with minor easily reversible encryption. I believe it was double b64 last time.
I'm assuming the logic there is that every security researcher and company is going to pull and scan those creds for their stuff and their clients' stuff. So the attacker is just 1 of N people downloading it. As opposed to trying to send it to their own machine directly.
You say you rely on CC to suggest software to install from the internet, and then you install it.
I haven't heard anyone suggest CC or any LLM as a "filter" for "is this package safe right now", and it seems like a very bad heuristic to me, not only, but also for the reason you gave.
For example, at that time, one way to distribute machine learning models was via Python pickles. Which are executable objects with no restriction built in. Models in this format could do anything on a computer where the model was imported. Such an early 'wild-west' ecosystem can definitely make security compromises easier and resulting supply chain attacks more common.
In the meantime, please use 2.6.1 until we publish 2.6.4.
For more details: https://github.com/Lightning-AI/pytorch-lightning/security/a...
I can see trying to steal crypto, but what do they do if they get some AWS credentials? Try to run some crypto mining instances? Try to use your account for other types of crimes? Or is it mainly trying to steal data and then ask for ransoms?
"deependujha hi @thebaptiste, thanks for inquiring. Release of 2.6.2 is blocked due to some internal reasons. Will notify once release is made. "
I'd hate it if they knew of the problem that long ago and didn't warn until now. If someone has more info and can clarify I'd be thankful.
https://github.com/Lightning-AI/pytorch-lightning/issues/216...
FYI, pip added cooldowns in 26.1:
To use:https://github.com/Lightning-AI/pytorch-lightning/security/a...
With the new generation of yolo NPM scripters, they simply don't evaluate the risks. They will even fight back telling you that it's the way of doing things.
In reality, it's the warning we learnt back then, that's the result of be mindlessly importing third dependencies without thinking.
In other words, the risks were always there, the new "modern way", let's put it that way, doesn't put the effort anymore.
This is why I have been building, for my own usecases, a new language + compiler + vm that is completely source based. The compiler does not understand linking. You must vendor every single dependency you use, including the standard library, so that it makes its way into the bytecode. The register VM itself is a few thousand lines of freestanding C. Any competent programmer can audit it over a weekend.
v1 deliberately keeps FFI (outside of a bounded set of linux syscalls) outside the current spec as libc has the habit of infecting everything it touches and I want to keep Vm0 freestanding. The last time I compiled the VM, it produced a 70KB binary and supported a loader with structural verification, the entire instruction set using a threaded interpreter, a simple Cheney+MS GC, concurrency via an Erlang-style M:N scheduler working on a single thread, and 20-odd marshaled functions.
Most software in the world does not need anything more than this. Everyone acts as if they are building the next Google.
Think twice before looking at a package and most importantly, always pin your dependencies.