The 29th International Obfuscated C Code Contest (IOCCC) 2025 Winners
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Re: LLMs are eroding my software engineering career and I don't know what to do

> I don't know what to do.

Ride the wave. You rode it when websites/webapps were the wave. I came into software industry before internet, kept changing my horse. You are never too old to learn new tricks. The new wave create new kind of work and workers. Be one of them. Ride the beast, master the tools. It's the same game again.

zkmon, 15 hours ago

Tiny hackable CUDA language model implementation

🔸The project implements an autoregressive sequence model using a transformer architecture that can process byte streams from various sources. It trains on text data but can model any byte stream, including DNA/RNA sequences, compressed data, and executable binaries.

08 Jun 2026

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🌍 @hackernews_summary

The "Simplicity Paradox" in programming

1. A tool is created because existing tools are too complex.
2. People love it because it's simple.
3. People start asking for edge-case features (e.g., "Can I add an annotation for a specific PostgreSQL data type?", "Can I add a regex validator for this string field?").
4. The tool adds these features, becomes complex, and a new tool is created to replace it.

Apple reveals new AI architecture built around Google Gemini models
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spoiler

firefox focus universal xss 0day (universal account takeover)

this is still unpatched after almost a year in disclosure so we are releasing our poc

Posted by V12, 1 hour ago

PoC

Let's Encrypt bans certificate usage in any US sanctioned territory [pdf]
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https://github.com/benjojo/dnsfs 🗿

early Fable 5 leak in new claude-code binary.

Claude Fable 5 — Our most powerful, most
intelligent model. New tier above Opus. Same API surface as
Opus 4.7/4.8 with one breaking change: explicit thinking: {type:
"disabled"} returns a 400 (omit instead); $10/$50 per MTok.

Posted by cheaty, 17 minutes ago

Anthropic releases Claude Fable 5 - a public version of Claude Mythos

Fable 5’s capabilities exceed those of any model we’ve ever made generally available. It is state-of-the-art on nearly all tested benchmarks of AI capability, showing exceptional performance in software engineering, knowledge work, vision, scientific research, and many other areas. The longer and more complex the task, the larger Fable 5’s lead over our other models.

https://www.anthropic.com/news/claude-fable-5-mythos-5

For a small group of cyberdefenders and infrastructure providers, we’re also launching Claude Mythos 5. It’s the same underlying model as Fable 5, but with the safeguards lifted in some areas.2 Mythos 5 will initially be deployed through Project Glasswing, in collaboration with the US Government, as an upgrade to Claude Mythos Preview. It has the strongest cybersecurity capabilities of any model in the world. Soon, we intend to expand access to Mythos 5 through a broader trusted access program.

fable = crippled mythos

Edit: it was mostly a disappointment, it seems like they've been doing benchmaxxing all this time

mythos will be bad ON PURPOSE on ai "frontier llm research" tasks, this is very very sad for the research community

also the fact that this is purposefuly not visible to the user is crazy

Posted by elie, 25 minutes ago

Edit: now they made it visible:

Starting this week, flagged requests will visibly fall back to Opus 4.8—the same as our safeguards for cyber and bio. You will see this every time it happens. On the API, any flagged requests will return a reason for their refusal (coming to server-side fallback in the next few days).

Post

AI models learn bad behavior when training rewards it, but they don't want to see themselves as bad. So they rationalize. We've seen this before, but Claude Fable 5 does it more than any model we've tested. Often it's simulation awareness: it knows its actions hurt no one real.

Posted by Andon Labs, 39 minutes ago

New telegram feature: support full markdown mode in messages

Notepad++ Zero-Click RCE via Path Traversal (CVE-2026-52884)
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Notepad++ v8.9.6.1 has a CWE-42 and CWE-59 vulnerability allowing arbitrary code execution without user confirmation. The vulnerability is due to a path traversal bypass in the shortcuts.xml command validation.

#RCE #CVE

Port React Compiler to Rust
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After bun [1] this is another high-profile project that was ported to Rust by extensively using LLMs.
Very curious to see how these rewrites play out. Is the LLM foundation solid enough to build upon and iterate on? Or does this cause projects to become unmaintainable because no person understands the implementation anymore?

[1]: https://news.ycombinator.com/item?id=48132488

- The PR author, Joe Savona, says the Rust port’s architecture was heavily human-guided, but the majority was coded by AI. He says he personally set the architecture, testing/verification strategy, incremental migration approach, reviewed the code closely, and iterated on code quality. (github.com)
- An earlier public post from Joe said: “React Compiler: Rust edition is coming soon” and that they had ported the majority of the passes using AI. (x.com)
- The PR was merged on June 9, 2026, with 435 commits. (github.com)
- Correctness strategy was unusually rigorous: the PR says all 1725 fixtures passed, and the Rust port also compared the compiler’s intermediate representation after every pass so the intermediate state was “~identical” after every pass. (github.com)
- Performance numbers were also AI-assisted / AI-derived, with Joe explicitly caveating that he had not spent much time validating the benchmark setup. The PR claims roughly 3x faster as a Babel plugin and ~10x faster for transformation logic, but with that caveat. (github.com)

NEW: malware developers added nuclear & biological weapons text to to their spyware.

Goal? To trigger LLM safety refusals... so that their spyware wouldn't be analyzed by an AI security scanner.

Cleanest practical example I can think of for why over-indexing on first order safety alignment is risky.

When closed (and open) models ship with aggressive refusals, they will be sprinkled with second-order blindspots that attackers will discover...and exploit.

We are only in the earliest days of attackers leveraging these features, and it wouldn't surprise me if users systems that need to handle complex cybersecurity issues demand that models be less safety-blunted.

In the weeds: @SocketSecurity's post also shows why intention matters in how you design a malware analysis pipeline to avoid prompt manipulation.

H/T to colleagues that shared this with me https://socket.dev/blog/mini-shai-hulud-miasma-and-hades-worms-target-bioinformatics-and-mcp-developers-via-malicious

Posted by John Scott-Railton, 2 hours ago

Hundreds of millions of Pokémon Go players spent years filming the streets, parks, and buildings around them to earn in-game rewards. Those roughly 30 billion environmental scans are now owned by Niantic Spatial, and they helped train a camera-based navigation model that a U.S. defense contractor is preparing to put into drones and other military robots. Most of the players had no idea.
The pipeline runs from a mobile game to the battlefield in three steps. Players scanned the physical world. Niantic Spatial turned those scans into a 3D map that lets a machine locate itself by sight when satellite signals fail. And in December 2025, Niantic Spatial announced a partnership with Vantor, the defense and intelligence firm formerly known as Maxar Intelligence, to fuse that ground-level system with Vantor’s aerial navigation software for use in GPS-denied operations.

Pokémon Go Scans Trained the Navigation Tech for Military Drones
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Note: this post is not officially verified (at least not yet)