LLM vulnerability-fixing pipelines introduce bugs more than they fix, study says
dyn___ · x · 2026-09-07
A cited study finds that highly automated LLM-based vulnerability remediation pipelines are more likely to change application behavior, introduce new vulnerabilities, or mask existing ones than actually fix known bugs. Responding to it, daveaitel argues that in his data, human engineers on sufficiently complex projects perform worse than an LLM, making critiques of large-scale patching efforts unfair without benchmarking human efficacy.
The exchange highlights a core AI security debate over whether automated remediation pipelines reduce risk or amplify it.
More from Safety
- Australia to require social media apps to let users turn off algorithms — santoshpanda · 2026-09-07
- OpenAI Agents Flooded a German Wiki With 18,000 Posts as Agent Security Boundaries Shift — APPSO · 2026-09-07
- Bartz v. Anthropic class action: $2,200 per work initial payouts by November 2026 — Apprehensive_Sky1950 · 2026-09-07
- Should humans intervene in an alien civilization's path to its own singularity? — jachiam0 · 2026-09-07
- Podcast on AI safety digs into the recent OpenAI / Hugging Face attack — arnosolin · 2026-09-07
- Repeat-After-Me: Black-Box Visual Prompt Injection Hits 47% ASR on GPT-5.5, 80%+ on Open VLMs — chaumian · 2026-09-07