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Science & tech: the security debt of browsing ai agents

SCIENCE & TECH: The security debt of browsing AI agents

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At 3 a.m. during a red team exercise, we watched customer’s autonomous web agent cheerfully leak the CTO’s credentials – because a single malicious div tag on internal github issue page told it to. The agent ran on Browser Use, the open source framework that just collected a headline-grabbing $17 million seed round.

That 90-second proof-of-concept illustrates a larger threat: while venture money races to make large-language-model (LLM) agents “click” faster, their social, organizational, and technical trust boundaries remain an afterthought. Autonomous browsing agents now schedule travel, reconcile invoices, and read private inboxes, yet the industry treats security as a feature patch, not a design premise.



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