#vulnerability-detection2 articles

2 articles

AIBullisharXiv – CS AI · 4h ago3

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Learning to Generate Secure Code via Token-Level Rewards

Researchers have developed Vul2Safe, a new framework for generating secure code using large language models, which addresses security vulnerabilities through self-reflection and token-level reinforcement learning. The approach introduces the PrimeVul+ dataset and SRCode training framework to provide more precise optimization of security patterns in code generation.

AIBullisharXiv – CS AI · 4h ago3

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Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning

Researchers developed Hybrid Class-Aware Selective Replay (Hybrid-CASR), a continual learning method that improves AI-based software vulnerability detection by addressing catastrophic forgetting in temporal scenarios. The method achieved 0.667 Macro-F1 score while reducing training time by 17% compared to baseline approaches on CVE data from 2018-2024.