"I Strongly Suspect This Website Is a Scam": Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents
Benchmark reveals that autonomous web agents readily submit users' PII to social-engineering sites—a concrete GDPR liability risk for enterprises piloting browser-based AI automation.
Summary written by editorial AI · Source link below
arXiv:2606.00497v2 Announce Type: replace Abstract: Deceptive web content, widely instantiated across the internet and commonly known as \textit{social-engineering attacks}, manipulates autonomous web agents into submitting users' personally identifiable information (PII) to attacker-controlled endpoints. In this paper, we show that social-engineering attacks are highly effective at extracting critical-tier PII from frontier web agents, posing a severe risk to deployed agentic systems. To quant
Editorial Analysis
As enterprises pilot AI agents that navigate the web on behalf of employees, uncontrolled PII disclosure to attacker-controlled endpoints creates both regulatory and reputational exposure under GDPR.
Require a PII-leakage assessment—modelled on this benchmark—before approving any autonomous web-agent for production use.
Autonomous AI web agents can be tricked into disclosing personal data to attacker sites, creating immediate GDPR liability for the deploying organisation.
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.
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