src_fb50be84b835134c75
- Source-provided label
- Not reported
- Evidence class
- mentioned in report
- Confidence
- Not reported
- Observed
- Oct 07, 2026 04:00 UTC
- Retrieved
- Oct 08, 2026 03:43 UTC
Efficient Auditing of Adversarial AI Agent Behavior from Agent Traces
arXiv:2610.07256v1 Announce Type: new Abstract: AI agents powered by large language models (LLMs) can perform complex tasks but may harm the systems they operate in, either intentionally or unintentionally. Existing agent monitoring approaches rely on rule-based guardrails or LLM-based trace auditing. However, rule-based guardrails can be bypassed through obfuscation and may miss harmful actions b
Reference details
- Source category
- Research & news
- Report title
Efficient Auditing of Adversarial AI Agent Behavior from Agent Traces- First reported
- Oct 07, 2026 04:00 UTC
- Last reported
- Oct 07, 2026 04:00 UTC
- Catalog updated
- Oct 08, 2026 03:43 UTC
- Record ID
1c61f38fd3ca6f7856ff9f16165e9fe25b9a20e04c0b239ce128743e50b8a964
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