‘Model weights need the same level of scrutiny as code’: Microsoft researchers find AI agents can be backdoored by editing just a few neurons





  • Researchers demonstrated a “sleeper agent” AI attack by modifying a handful of dormant neurons inside an LLM
  • The backdoor remains hidden until a specific trigger appears, then executes attacker-defined actions
  • Defenders are urged to verify model integrity, audit weights, and tightly restrict AI agent permissions

It sounds like an idea for a sequel to The Manchurian Candidate: a seemingly ordinary AI agent has been secretly programmed to turn evil, carrying out his master’s nefarious task only when a specific trigger activates his conditioning.

Microsoft researcher Dimitris Papailiopoulos demonstrated an attack called Lazarus, which turns an otherwise helpful AI model into a sleeper agent just waiting for the right moment to strike. The attack involves modifying just a handful of neurons inside a large language model (LLM), through which he planted a backdoor that remains dormant until a specific trigger appears.

https://cdn.mos.cms.futurecdn.net/NNZdcW7Ku4FXu2CdGfdqvf-1920-80.jpg



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Sead Fadilpašić

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