Eclypsium and NVIDIA are collaborating to address emerging threats to AI infrastructure, as new research demonstrates how compromised hardware could undermine the integrity of running models.
The research from Eclypsium, supported by NVIDIA, shows how attackers with privileged infrastructure access could manipulate a model’s behavior without changing its original files. In a controlled demonstration, researchers used a compromised data processing unit, or DPU, combined with permissive memory isolation, to modify model weights directly in memory.
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Those weights help determine how a model interprets information and generates responses. Modifying them during execution could allow an attacker to influence outputs while leaving the stored model unchanged. Integrity checks focused on the original files would not, by themselves, identify that manipulation.
The collaboration brings together Eclypsium’s infrastructure security research and NVIDIA’s AI computing expertise to examine an attack surface with implications beyond a single hardware vendor. Their joint blog addresses the relationship between trusted infrastructure and trusted AI.
Eclypsium describes the broader challenge as the AI Infrastructure Assurance Gap: organizations are investing in model security without necessarily establishing equivalent confidence in the systems running those models.
The research report underscores why protecting AI requires attention to the hardware, privileged components and isolation controls supporting its execution.
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