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CAMLIS / PMLR · December 2, 2025

CAMLIS 2025 Peer-Reviewed Proceedings

analysis AI Red TeamingAdversarial MLAgent SecurityPrompt InjectionModel Evaluation
Why it matters

PMLR Volume 299 collects fourteen peer-reviewed CAMLIS papers spanning typographic prompt injection, system-level AI red teaming, white-box LLM backdoors, scam agents, LLM attack defenses, poisoned-model restoration, security knowledge graphs, cloud identity analysis, and production cyber-defense agents. Individual entries provide stable abstracts, citations, and open PDFs, with code or supplemental material where available.

My takeaway: Use the proceedings as the primary record and select papers by reproducibility, stated attacker assumptions, datasets, baselines, code availability, and deployable controls. Link field notes to the paper and artifacts as well as the talk, and keep unsupported poster or presentation claims distinct from peer-reviewed findings.
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