What is Hackers' Pub?

Hackers' Pub is a place for software engineers to share their knowledge and experience with each other. It's also an ActivityPub-enabled social network, so you can follow your favorite hackers in the fediverse and get their latest posts in your feed.

0
0
0
0
0
0
0
0

I've just published version 2.83 of , the simple, minimalistic instance server written in C. It includes the following changes:

After receiving a follow confirmation, a bunch of posts from that account are requested and inserted into the timeline as context.

Continuously failing instances are marked as broken after a given number of days (see snac(8) on how to tune this counter). Incoming activity from any of these instances resets the counter.

Fixed a nasty bug that incorrectly deleted private local posts in certain cases.

Scheduled posts can now be sent from the command line (see snac(1) for more information on how to do it).

Docker: add timezone, new examples for building and complete Swarm mode stack with Traefik (contributed by daltux).

Fixed timezone names (contributed by dharmik).

Documented the update command (contributed by xvello).

https://comam.es/what-is-snac

If you find useful, please consider buying grunfink a coffee or contributing via LiberaPay.



0
0

[repost of an old favorite]

robot: why are children like that

human: imagine if it took 20 years to build your processor, component by component… but it was trying to execute your operating system the entire time

robot: ada lovelace christ

0
0
0
0
1

@dabeazDavid Beazley I came across your Ray Tracing videos on Rust Weekly. Really cool stuff!

BTW, I think if you pass `box<dyn Hittable>` to `HittableList`'s `add` method (and boxing outside), you can avoid the lifetime annotation for `HittableList`

That said, working with trait objects in Rust often feels more cumbersome than using dynamic dispatch in OOP languages (I think this is because Rust uses fat pointers rather than embedding the vtable in the object)

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

Fun fact: did you know passports were not required for travel before WW1?

en.wikipedia.org/wiki/Passport

During WW1, governments made them mandatory to monitor their borders more closely. After WW1, there was even talk of abolishing them!

But WW2 came and afterward, they became entrenched.

So next time you hear about government doing deals with each other for immigration/trade, note that they are merely giving you back a subset of freedoms that they already took away themselves.

0
0
0
0
0
0
0

A little PSA: if your library of choice is facing funding cuts, don't hold off on using their services because you're worried it'll put pressure on their existing funds.

Take advantage of everything and help them get some lovely stats to help them demonstrate impact as they fight back! If it looks like they're not being useful to folks, they'll get cut!

Don't do the cost cutters' jobs for them!

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

What does @cR0wcR0w :cascadia: say? Hack more AI shit or something?

Well, here ya go. (Actually gonna play with this tomorrow on POINT's AI, Chiron.)

arxiv.org/abs/2508.17155

arXiv logo

Mind the Gap: Time-of-Check to Time-of-Use Vulnerabilities in LLM-Enabled Agents

Large Language Model (LLM)-enabled agents are rapidly emerging across a wide range of applications, but their deployment introduces vulnerabilities with security implications. While prior work has examined prompt-based attacks (e.g., prompt injection) and data-oriented threats (e.g., data exfiltration), time-of-check to time-of-use (TOCTOU) remain largely unexplored in this context. TOCTOU arises when an agent validates external state (e.g., a file or API response) that is later modified before use, enabling practical attacks such as malicious configuration swaps or payload injection. In this work, we present the first study of TOCTOU vulnerabilities in LLM-enabled agents. We introduce TOCTOU-Bench, a benchmark with 66 realistic user tasks designed to evaluate this class of vulnerabilities. As countermeasures, we adapt detection and mitigation techniques from systems security to this setting and propose prompt rewriting, state integrity monitoring, and tool-fusing. Our study highlights challenges unique to agentic workflows, where we achieve up to 25% detection accuracy using automated detection methods, a 3% decrease in vulnerable plan generation, and a 95% reduction in the attack window. When combining all three approaches, we reduce the TOCTOU vulnerabilities from an executed trajectory from 12% to 8%. Our findings open a new research direction at the intersection of AI safety and systems security.

arxiv.org · arXiv.org

0
0
0