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AI Risk

Memory and Storage

"Similar to conventional programs, hardware infrastructures can also introduce threats to LLMs. Memory-related vulnerabilities, such as rowhammer attacks [160], can be leveraged to manipulate the parameters of LLMs, giving rise to attacks such as the Deephammer attack [167], [168]."

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AI Risk2. Privacy & Security2.2 > AI system security vulnerabilities and attacks1 - Pre-deployment

Record summary

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Techniques3Attack methods connected to this risk.
Mitigations1Defenses that may help with related attacks.
Domain2. Privacy & SecurityThe broad risk area this belongs to.

Risk profile

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Domain2. Privacy & Security
Subdomain2.2 > AI system security vulnerabilities and attacks
Entity1 - Human
Intent1 - Intentional
Timing1 - Pre-deployment
CategoryHardware Vulnerabilities
SubcategoryMemory and Storage

Related techniques

Attack methods connected to this risk.

Suggested mitigations

Defenses that may help with related attacks.

Memory Hardening

ML Model EngineeringDeployment+1 more
LifecycleML Model Engineering + 2 moreCategoryTechnical - ML

Source

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