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Summary
A Sept. 17 arXiv paper proposes a unified framework assessing AI agents across eight trustworthiness dimensions with trajectory analysis, safety overrides and regulatory mappings. As enterprise agent use surges 327%, current benchmarks fall short.
The new approach aims to close the gap between lab scores and production reality.
KazaSec's take
AI-related security incidents are a genuinely new category — prompt injection, model manipulation, and data leakage through an LLM integration don't map cleanly onto traditional application security testing, and are worth assessing deliberately rather than assuming existing controls already cover them.
Coverage details
We've archived 54 other articles touching the same topic (agentic ai, evaluation framework, agenticai) — see the full security news archive.
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