LLM Security Guard for Code
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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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Citing papers per year: 2024: 3; 2025: 8; 2026: 4.
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- 2024When LLMs Meet Cybersecurity: A Systematic Literature Reviewcited by 70
- 2025Correctness Assessment of Code Generated by Large Language Models Using Internal Representationscited by 17
- 2024Evaluating Software Development Agents: Patch Patterns, Code Quality, and Issue Complexity in Real-World GitHub Scenarioscited by 16
- 2025Large Language Models (LLMs) for Source Code Analysis: applications, models and datasetscited by 15
- 2025Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injectioncited by 15
- 2025Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT Modelscited by 12
- 2024FATS: A Prompt Injection Attack Utilizing Feign Security Agents with Deceptive Few-shots Learningcited by 4
- 2025SCGAgent: Recreating the Benefits of Reasoning Models for Secure Code Generation with Agentic Workflowscited by 4
- 2025SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deploymentcited by 2
- 2026PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelinescited by 2
- 2025Repairing vulnerabilities without invisible hands. A differentiated replication study on LLMscited by 1
- 2026Feedback-based Automated Verification in Vibe Coding of CAS Adaptation Built on Constraint Logiccited by 1
3 more
- 2025Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verificationcited by 0
- 2026From Data Leak to Secret Misses: The Impact of Data Leakage on Secret Detection Modelscited by 0
- 2026From Adoption to Deployment: A Qualitative Study on AI Integration in Software Development Practicecited by 0
- 2026From Adoption to Deployment: A Qualitative Study on AI Integration in Software Development Practice18 Jul 2026
- 2026PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelines11 May 2026
- 2026Feedback-based Automated Verification in Vibe Coding of CAS Adaptation Built on Constraint Logic20 Feb 2026
- 2026From Data Leak to Secret Misses: The Impact of Data Leakage on Secret Detection Models30 Jan 2026
- 2025Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verification31 Oct 2025
- 2025Repairing vulnerabilities without invisible hands. A differentiated replication study on LLMs28 Jul 2025
- 2025SCGAgent: Recreating the Benefits of Reasoning Models for Secure Code Generation with Agentic Workflows8 Jun 2025
- 2025Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection23 Apr 2025
- 2025Large Language Models (LLMs) for Source Code Analysis: applications, models and datasets21 Mar 2025
- 2025Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT Models9 Feb 2025
- 2025SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deployment31 Jan 2025
- 2025Correctness Assessment of Code Generated by Large Language Models Using Internal Representations22 Jan 2025
3 more
- 2024Evaluating Software Development Agents: Patch Patterns, Code Quality, and Issue Complexity in Real-World GitHub Scenarios16 Oct 2024
- 2024FATS: A Prompt Injection Attack Utilizing Feign Security Agents with Deceptive Few-shots Learning11 Oct 2024
- 2024When LLMs Meet Cybersecurity: A Systematic Literature Review6 May 2024
- 2024Evaluating Software Development Agents: Patch Patterns, Code Quality, and Issue Complexity in Real-World GitHub Scenarioscited by 16
- 2024FATS: A Prompt Injection Attack Utilizing Feign Security Agents with Deceptive Few-shots Learningcited by 4
- 2025SCGAgent: Recreating the Benefits of Reasoning Models for Secure Code Generation with Agentic Workflowscited by 4
- 2026PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelinescited by 2
- 2026PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelines11 May 2026
- 2025SCGAgent: Recreating the Benefits of Reasoning Models for Secure Code Generation with Agentic Workflows8 Jun 2025
- 2024Evaluating Software Development Agents: Patch Patterns, Code Quality, and Issue Complexity in Real-World GitHub Scenarios16 Oct 2024
- 2024FATS: A Prompt Injection Attack Utilizing Feign Security Agents with Deceptive Few-shots Learning11 Oct 2024
- 2024When LLMs Meet Cybersecurity: A Systematic Literature Reviewcited by 70
- 2025Correctness Assessment of Code Generated by Large Language Models Using Internal Representationscited by 17
- 2025Large Language Models (LLMs) for Source Code Analysis: applications, models and datasetscited by 15
- 2025SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deploymentcited by 2
- 2025Repairing vulnerabilities without invisible hands. A differentiated replication study on LLMscited by 1
- 2026Feedback-based Automated Verification in Vibe Coding of CAS Adaptation Built on Constraint Logiccited by 1
- 2026From Data Leak to Secret Misses: The Impact of Data Leakage on Secret Detection Modelscited by 0
- 2026From Adoption to Deployment: A Qualitative Study on AI Integration in Software Development Practicecited by 0
- 2026From Adoption to Deployment: A Qualitative Study on AI Integration in Software Development Practice18 Jul 2026
- 2026Feedback-based Automated Verification in Vibe Coding of CAS Adaptation Built on Constraint Logic20 Feb 2026
- 2026From Data Leak to Secret Misses: The Impact of Data Leakage on Secret Detection Models30 Jan 2026
- 2025Repairing vulnerabilities without invisible hands. A differentiated replication study on LLMs28 Jul 2025
- 2025Large Language Models (LLMs) for Source Code Analysis: applications, models and datasets21 Mar 2025
- 2025SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deployment31 Jan 2025
- 2025Correctness Assessment of Code Generated by Large Language Models Using Internal Representations22 Jan 2025
- 2024When LLMs Meet Cybersecurity: A Systematic Literature Review6 May 2024