AI safety
32 posts
Panic on a schedule
What the 2019 GPT-2 release panic predicted about GPT-4-era AI anxieties, and the misuse pattern that has repeated with every model since.
EY Canada's 2026 report cited papers that don't exist
EY Canada published a cybersecurity report with mostly hallucinated citations. Here's what that means for how you should read threat intelligence.
YouTube built a checkbox, not a detector
YouTube's automatic AI-generated video label is a disclosure system, not a detector. Here's what it actually does for cybersecurity and what it doesn't.
Forge guardrails took an 8B model from 53% to 99%
A Show HN post says Forge guardrails took an 8B model from 53% to 99% on agentic tasks. Here's what that means for security and reliability.
March 2019 changed who reads binaries
Free disassemblers and decompilers changed who can audit binaries. The defender, attacker, and AI safety implications are now playing out in practice.
The watermark proves almost nothing useful
OpenAI's adoption of Google's SynthID watermark is a useful but partial signal. Here's what it actually means for forensics and security teams.
A few bytes spill onto the next heap chunk
Technical writeup of CVE-2026-42945, the NGINX rewrite module heap overflow, plus what it means for LLM deployments sitting behind the proxy.
Mid-2024: a drunk LLM found a ksmbd kernel bug
How researchers used degraded LLM prompts to find a remote OOB write in the Linux kernel's ksmbd module, and what it means for kernel security.