What Do They Fix? LLM-Aided Categorization of Security Patches for Critical Memory Bugs

arXiv:2509.22796 · cs.CR, cs.LG · Submitted 2025-09-26 · Read on arXiv

cs.CR, cs.LG

Submitted: 2025-09-26

Updated: 2026-09-25

Code: https://github.com/xairy/linux-kernel-exploitation

Project page: https://ii4gsp.github.io/cve-2020-27786

Terminology

• Accuracy — 56× in this paper · explained in 1 episode
• Verification — 11× in this paper · explained in 2 episodes
• Large Language Model — 10× in this paper
• Core — 6× in this paper · explained in 2 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• International Conference on Software Engineering — 4× in this paper
• Pruning — 4× in this paper · explained in 4 episodes
• Symposium on Security and Privacy — 4× in this paper
• Trace — 4× in this paper · explained in 2 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Few-Shot Learning — 3× in this paper · explained in 4 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Hallucination — 3× in this paper · explained in 3 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Automated Software Engineering — 2× in this paper
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Generalizability — 2× in this paper · explained in 6 episodes
• In-Context Learning — 2× in this paper · explained in 4 episodes
• Large Language Model (LLM) — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Common Weakness Enumeration Specification — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• International Conference on Dependable Systems and Networks — 1× in this paper
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes
• Semantic Drift — 1× in this paper · explained in 3 episodes

Sources

• Unified Pre-training for Program Understanding and Generation
• Evaluating Large Language Models Trained on Code
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
• CodeBERT: A Pre-Trained Model for Programming and Natural Languages
• GraphCodeBERT: Pre-training Code Representations with Data Flow
• BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
• An Investigation of Patch Porting Practices of the Linux Kernel Ecosystem
• Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
• Keep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT
• WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models
• A Survey of Large Language Models

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