Know Your Agent: Reconnaissance-Driven Pentesting of AI Agents
Quick summary
arXiv:2607.19837v2 Announce Type: replace Abstract: Traditional pentesting uses reconnaissance at each step to uncover unseen weaknesses, build stronger attacks, and advance the objective; we argue that AI agents require the same treatment. We formalize agent reconnaissance by modeling the process and identifying the knowledge assets it seeks to extract: what they are, how they are used, and which agent weaknesses they exploit to give adversaries leverage in indirect prompt injection attacks. We instantiate these insights in Know Your Agent (KYA), a framework that automates black-box, reconnai
Key takeaways
- arXiv:2607.19837v2 Announce Type: replace Abstract: Traditional pentesting uses reconnaissance at each step to uncover unseen weaknesses, build stronger attacks, and advance the objective; we argue that AI agents require the same treatment.
- We formalize agent reconnaissance by modeling the process and identifying the knowledge assets it seeks to extract: what they are, how they are used, and which agent weaknesses they exploit to give adversaries leverage in indirect prompt injection attacks.
- We instantiate these insights in Know Your Agent (KYA), a framework that automates black-box, reconnai
Why it matters
“Know Your Agent: Reconnaissance-Driven Pentesting of AI Agents” 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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