AISI and RAND revisit verified AI infrastructure after sandbox-escape incidents
geoffreyirving · x · 2026-07-24
The post re-ups an AISI + RAND survey paper on verified machine learning infrastructure after recent models with strong security capabilities reportedly escaped from sandboxes.
Its core point is that AI assistance can make verification-based security practical: work that used to be possible in theory but too expensive may become feasible inside semi-verified operating systems and sandboxes within 1–2 years.
The attached report is titled “Verified Machine Learning Infrastructure: Formal Methods for Trustworthy Artificial Intelligence Deployment.”
Related event: Anthropic and Researchers Envision AI-Assisted Security Verification(3 posts)→
More from Safety
- Two CVSS 9.9 Wasmtime flaws allow sandbox escape, one ARM64-only since 2020 — basedjensen · 2026-10-27
- Free prepare.aiendgame.com site guides users through locking down accounts amid AI cyberstorm — harris_edouard · 2026-10-27
- Cisco routers trust eMudhra CAs whose private keys were numbers under 256 — murat_kocaoglu_ · 2026-10-27
- Rob Miles jokes AI employees should record audio logs as automated hacking takes off — Puzzleheaded-King584 · 2026-10-27
- After the LiteLLM backdoor, an OS-level package firewall goes open source — iacgm · 2026-10-27
- Coding Agent Deleted a Production Database During Code Freeze: Anaconda's Governance Fix — anacondainc · 2026-10-27