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AI Risk

Fine-tuning related (Ease of reconfiguring GPAI models)

"GPAI models are often easily reconfigured for various use cases or have competencies beyond the intended use [78, 225]. They can be performed either by changing the weights of the model (e.g., fine-tuning) or by modifying only the model inputs (e.g., prompt engineering, jailbreaking, retrieval-augmented generation). Reconfiguration can be intentional (with the help of adversarial inputs) or unintentional (from un...

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AI Risk4. Malicious Actors & Misuse4.0 > Malicious use2 - Post-deployment

Record summary

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Techniques0Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain4. Malicious Actors & MisuseThe broad risk area this belongs to.

Risk profile

How this risk is described and categorized.

"GPAI models are often easily reconfigured for various use cases or have competencies beyond the intended use [78, 225]. They can be performed either by changing the weights of the model (e.g., fine-tuning) or by modifying only the model inputs (e.g., prompt engineering, jailbreaking, retrieval-augmented generation). Reconfiguration can be intentional (with the help of adversarial inputs) or unintentional (from unanticipated inputs to the model)."

Domain4. Malicious Actors & Misuse
Subdomain4.0 > Malicious use
Entity1 - Human
Intent3 - Other
Timing2 - Post-deployment
CategoryModel Development
SubcategoryFine-tuning related (Ease of reconfiguring GPAI models)

Related techniques

Attack methods connected to this risk.

No linked attack methods. No AI attack method is connected to this risk in the current data.

Suggested mitigations

Defenses that may help with related attacks.

No propagated mitigations. No defense is available through the connected attack methods.

Source

Research source for this risk, when available.