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Arkose Labs releases Q3 2026 agentic AI trust report

Arkose Labs, a leader in agent trust and orchestration, published its State of Agentic AI Trust Report for Q3 2026. The report shows that more than 65% of customer sites—including banking, gaming, technology and travel organizations—saw agents logging in, signing up and checking out on behalf of people. Yet fewer than 3% of these agents proactively disclosed their identity.

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Key points

  • 65% of Arkose Labs customers saw agents on login, registration, checkout flows in Q3 2026
  • Meta's Muse sessions grew >30x in September, yet <3% of agents disclose identity
  • 70.5% of registration sessions were fake-account attempts, highlighting control gaps

The data also reveal that Meta’s Muse, a personal AI agent, grew more than 30x in September, while Instinct’s sessions were flagged as medium or high risk 96.8% of the time but had no linked attacks. Across all industries, 70.5% of registration sessions were fake‑account attempts, and 97.7% of legitimate AI agent sessions carried no verified disclosure.

These findings underscore the rapid expansion of personal AI agents and the lag in effective controls, raising concerns about security, privacy and the need for more nuanced detection methods.

Model page: Muse →

Full story from finance.yahoo.com · by Business Wire · via Search: MetaOpen source ↗

Personal AI Agents Including Meta’s Muse Identify Themselves Less Than 3% of Time While Handling Sensitive Transactions at Scale

finance.yahoo.com · 20 October 2026

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This text was published by finance.yahoo.com and written by Business Wire. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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Arkose LabsMetaMuseInstinctKevin Gosschalk

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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