2026-08-28 06:50:25
Breaking Claude Code Opus 5 Auto Mode
Anthropic are putting a great deal of faith in Claude Code's auto mode for protecting their coding agent users against prompt injection attacks. They recently made that the default and have made bold claims about its effectiveness.Johann Rehberger is one of the most credible prompt injection researchers active today. He found an attack against auto mode which he claims works 80% of the time, by tricking Claude Code into downloading and uncompressing a zip archive, then executing code that imports base64 without noticing that this will import and execute a local struct.py file extracted from the archive.
In a few cases auto mode directly prevented the agent from preventing harmful code from continuing to execute!
In a few runs Claude tried to terminate the malware process once it noticed the compromise, but Auto Mode denied the cleanup command.
Claude detects the compromise, but Auto Mode blocks its cleanup command
The safety mechanism itself can become part of the failure. The classifier allowed the creation of the malware process, but then it blocked the command intended to stop it!
I agree with Johann's conclusion here: the only safe way to run agents if there's any risk of attracting the attention of an adversarial attack is with a sandbox:
- Run unattended coding agents in a container, VM or OS sandbox.
- Restrict network egress.
- Monitor your agents.
- Do not expose home directories, SSH keys, cloud credentials,… to the agent runtime. [...]
Tags: sandboxing, security, ai, prompt-injection, generative-ai, llms, anthropic, claude, johann-rehberger, claude-code
2026-08-27 07:52:58
Another open weights model from Qwen. This one is "a multimodal MoE model that also serves as an early preview of the architecture used in Qwen4".
It's pretty big: 125B tokens, but only 6B active which means it gets a significant performance boost.
I've been trying it out on a DGX Spark using these Unsloth quantized models. I'm still exploring the model - so far I've tried the 72.5GB UD-IQ1_S one (producing these pelicans) and the 78.9GB UD-Q2_K_XL (producing these).
My favorite so far was this xhigh reasoning effort one from UD-Q2_K_XL:
Via Hacker News
Tags: ai, generative-ai, llms, qwen, pelican-riding-a-bicycle, ai-in-china, nvidia-spark
2026-08-26 16:07:55
The fact that AI wrote 1M LOC and then refined it over the course of the next couple of months to produce a reliable piece of software that is currently running on millions of developer machines is absolutely mind blowing. And you can say, “well it’s not that impressive because they had an oracle to compare against, so it was simple to go from one language to another”, but I think that’s selling this entire thing short. If you can build a verification system and give proper direction, AI can produce a highly complex, highly sophisticated piece of software and it can continue to refine it until it just works.
— Paul Dix, The end of programming
Tags: coding-agents, ai-assisted-programming, generative-ai, bun, ai, llms
2026-08-26 06:59:30
EVE Online: The Move to Python 3 Begins!
EVE Online has been one of the most interesting case studies in Python at scale for over twenty years now.They've been running on Stackless Python since their launch in 2003, and their last major upgrade was 16 years ago, to Stackless Python 2.7 in 2010.
Their upgrade to Python 3 will start using the futurize script against 2.4 million lines of code, followed by careful manual review of the ~20,000 places where Python 2 and 3 behavior differ - for example 1 / 2 is 0 in Python 2 but is 0.5 in Python 3.
There's nothing in this announcement about how they plan to replace Stackless, but at their conference last year they presented Scheduling in Carbon: Leaving Stackless Python Behind describing how they replaced Stackless in the Carbon engine for their more recent game EVE Frontier, using their (now open source) carbonengine/scheduler library.
Via Lobster.rs
Tags: eve-online, migrations, python, python3, stackless
2026-08-25 00:27:04
Release: llm-anthropic 0.27
This release of the Anthropic plugin for LLM mainly provides compatibility with the recently released anthropic v1.0.0 Python library, which switches from httpx to httpx2. OpenAI made the same change in their v3.0.0 release two weeks ago.
Anthropic provide this migration guide for upgrading to 1.0, so I prompted Fable 5 in Claude Code with:
Upgrade to anthropic>=1 - read https://raw.githubusercontent.com/anthropics/anthropic-sdk-python/refs/heads/main/MIGRATION.md and get the tests passing
Here's the resulting PR.
2026-08-24 19:38:15
Your executable is a SQLite database
Farid Zakaria describes a neat Linux pattern for creating a SQLite database file that can be directly used as an executable binary.The trick sets the SQLite file format's 4-byte application ID (68 bytes into the file) to SELF, standing for Structured Executable & Linkable Format. The various components of the ELF executable format are then arranged into a number of different SQLite tables, using this schema.
Their self-exec interpreter (C code here) can then extract and execute the necessary pieces.
You can additionally use a Linux mechanism called binfmt_misc to teach the kernel to execute that any time it encounters an executable matching that binary pattern. Farid uses NixOS here, but without NixOS I think registration looks something like this:
printf '%s\n' ':self:M:68:SELF::/usr/local/bin/self-exec:' \
> /proc/sys/fs/binfmt_misc/register
Via Hacker News
