mlsanityData to 7 Oct 2026

LLM Security Guard for Code

arXiv 2405.01103 ↗First posted 2 May 2024cs.SE cs.CRcited by 15

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Abstract (arXiv)

Many developers rely on Large Language Models (LLMs) to facilitate software development. Nevertheless, these models have exhibited limited capabilities in the security domain. We introduce LLMSecGuard, a framework to offer enhanced code security through the synergy between static code analyzers and LLMs. LLMSecGuard is open source and aims to equip developers with code solutions that are more secure than the code initially generated by LLMs. This framework also has a benchmarking feature, aimed at providing insights into the evolving security attributes of these models.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 May 2024.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 8; 2026: 4.

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  1. 2024When LLMs Meet Cybersecurity: A Systematic Literature Reviewcited by 70
  2. 2025Correctness Assessment of Code Generated by Large Language Models Using Internal Representationscited by 17
  3. 2024Evaluating Software Development Agents: Patch Patterns, Code Quality, and Issue Complexity in Real-World GitHub Scenarioscited by 16
  4. 2025Large Language Models (LLMs) for Source Code Analysis: applications, models and datasetscited by 15
  5. 2025Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injectioncited by 15
  6. 2025Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT Modelscited by 12
  7. 2024FATS: A Prompt Injection Attack Utilizing Feign Security Agents with Deceptive Few-shots Learningcited by 4
  8. 2025SCGAgent: Recreating the Benefits of Reasoning Models for Secure Code Generation with Agentic Workflowscited by 4
  9. 2025SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deploymentcited by 2
  10. 2026PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelinescited by 2
  11. 2025Repairing vulnerabilities without invisible hands. A differentiated replication study on LLMscited by 1
  12. 2026Feedback-based Automated Verification in Vibe Coding of CAS Adaptation Built on Constraint Logiccited by 1
3 more
  1. 2025Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verificationcited by 0
  2. 2026From Data Leak to Secret Misses: The Impact of Data Leakage on Secret Detection Modelscited by 0
  3. 2026From Adoption to Deployment: A Qualitative Study on AI Integration in Software Development Practicecited by 0