Many Repairs, One Direction: Steering Code Models Toward Safer Cryptographic API Use

Tianhe Lu, Sakuna Harinda Jayasundara, Eric Spero, Ewan Tempero, Robert Biddle, Giovanni Russello · 2026 · arXiv

DOI: 10.48550/arXiv.2610.25133 · open-access PDF

Abstract

Cryptographic API misuse in large language model-generated code can compromise software security. While many existing approaches improve code security by modifying model parameters or inputs, how representation changes associated with different cryptographic API repairs can support a shared intervention for safer code generation remains underexplored. To investigate this, we construct 48,000 matched program pairs across four programming languages and ten cryptographic API misuse categories. Each pair changes a specified API decision while preserving the programming task. Subtracting the misuse

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