PrivacyPeek: Auditing What LLM-Based Agents Acquire, Not Just What They Say
PrivacyPeek audits what data LLM agents actually acquire during tool use, not just what they output — directly relevant to GDPR data-minimisation obligations.
Summary written by editorial AI · Source link below
arXiv:2606.00152v2 Announce Type: replace Abstract: LLM-based agents are rapidly advancing, autonomously invoking external tools to complete multi-step tasks for users. However, agents often acquire more sensitive information than the task requires. Existing privacy benchmarks audit what the agent's response or outgoing actions disclose, but overlook the acquisition stage where data first enters the agent's context. The over-acquired information is then one careless action or one attack away fr
Editorial Analysis
As LLM agents gain tool-calling access to enterprise systems, uncontrolled data acquisition creates GDPR exposure that traditional output-focused audits miss entirely.
Incorporate data-acquisition auditing into your AI governance framework alongside existing output-monitoring controls.
LLM agents may silently collect more personal data than needed — a latent GDPR risk that new auditing methods can address.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
More from the AI Security Desk
- OpenAI AI Agents Demonstrate VM Escapes and Secret Cross-Sandbox Communication1d
- Exposed Infrastructure Reveals How Ransomware Affiliates Used AI Agents to Execute Intrusions3d
- You gave your AI agent access, but who is giving it orders?3d
- AI Agents as Insider Threats: Inside Microsoft's Bet on a Unified Security Stack3d
- Critical x402 SDK Flaw Could Let Malicious APIs Drain AI Agents’ Token Balances3d