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CWE-1434 - Insecure Setting of Generative AI/ML Model Inference Parameters

  • Abstraction:Base
  • Structure:Simple
  • Status:Draft
  • Release Date:2025-09-09
  • Latest Modification Date:2025-09-09

Weakness Name

Insecure Setting of Generative AI/ML Model Inference Parameters

Description

The product has a component that relies on a generative AI/ML model configured with inference parameters that produce an unacceptably high rate of erroneous or unexpected outputs.

Generative AI/ML models, such as those used for text generation, image synthesis, and other creative tasks, rely on inference parameters that control model behavior, such as temperature, Top P, and Top K. These parameters affect the model's internal decision-making processes, learning rate, and probability distributions. Incorrect settings can lead to unusual behavior such as text "hallucinations," unrealistic images, or failure to converge during training. The impact of such misconfigurations can compromise the integrity of the application. If the results are used in security-critical operations or decisions, then this could violate the intended security policy, i.e., introduce a vulnerability.

Common Consequences

Scope: Integrity, Other

Impact: Varies by Context, Unexpected State

Notes: The product can generate inaccurate, misleading, or nonsensical information.

Scope: Other

Impact: Alter Execution Logic, Unexpected State, Varies by Context

Notes: If outputs are used in critical decision-making processes, errors could be propagated to other systems or components.

Related Weaknesses

CWE-440Expected Behavior Violation

CWE-665Improper InitializationMedium

CWE-684Incorrect Provision of Specified Functionality

CWE-691Insufficient Control Flow Management