CoSec: Benchmarking Agent Security in Communities
Quick summary
arXiv:2609.34790v2 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools. Community boundaries may remain fixed or evolve with changes in membership, roles, composition, and relationships. Agents must complete legitimate tasks and prevent unauthorized disclosure of protected information. Existing evaluations do not fully examine these risks in agent systems. We introduce \textbf{CoSec}, an executable benchmark for evaluating privacy and authorization enforcement in LLM agent systems o
Key takeaways
- arXiv:2609.34790v2 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools.
- Community boundaries may remain fixed or evolve with changes in membership, roles, composition, and relationships.
- Agents must complete legitimate tasks and prevent unauthorized disclosure of protected information.
Why it matters
“CoSec: Benchmarking Agent Security in Communities” shows why AI risk cannot be reduced to answer accuracy. Access controls, logging, human approval and incident response need to be designed into the workflow from the start.
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