Secure Code Generation

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Overview

The field asks whether code-generating models can produce programs that work as intended and resist vulnerabilities such as injection, insecure defaults, and memory-safety flaws. Researchers evaluate both properties with CWE-based benchmarks, executable security and functional tests, and static or dynamic analysis across languages and settings from small functions to repositories and infrastructure code. Common approaches include security-aware prompting, fine-tuning and reward-based training, retrieval and tool-guided repair, multi-agent workflows, and inference-time steering of model representations. A central tension is that functional success or knowledge of secure coding does not guarantee secure outputs; results can vary with prompts and context, and methods must reduce vulnerabilities without breaking functionality or relying on unrealistic tests.

Latest papers

CardsList

48 papers10 papers in the last four weeks, against 1 the four weeks before. 0.1% of all new papers.

  1. Enhancing Reliability in LLM-Based Secure Code Generation

    May 22, 2026Mohammed F. Kharma, Mohammad Alkhanafseh, Ahmed Sabbah +1LLM EvaluationCoT Reasoning

    the Department of Computer Science, Birzeit University, Ramallah, Palestine · the Department of Computer Science, University of Central Florida, Orlando, FL 32816 USA

  2. An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods

    May 22, 2026Mohammed Kharma, Ahmed Sabbah, Mohammad Alkhanafseh +2LLM PromptingLLM Security

    Department of Computer Science, Birzeit University, Birzeit, Palestine · King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia · University of Central Florida, Orlando, FL, USA

  3. Security of LLM-generated Code: A Comparative Analysis

    May 21, 2026Srivathsan G Morkonda, Mahmoud Selim, Hala AssalSoftware SecurityLLM Security

    Carleton University, Ottawa, ON, Canada

  4. Constrained Code Generation with Discrete Diffusion

    May 16, 2026Lize Shao, Michael Cardei, Zichen Xie +2Constrained Generative ModelingConstrained Decoding

    University of Virginia

  5. SecureForge: Finding and Preventing Vulnerabilities in LLM-Generated Code via Prompt Optimization

    May 8, 2026Houjun Liu, Lisa Einstein, John Yang +5LLM AuditingPrompt Optimization

    Stanford University

  6. A Quasi-Experimental Developer Study of Security Training in LLM-Assisted Web Application Development

    Apr 20, 2026Mohammed Kharma, Ahmed Sabbah, Radi Jarrar +3Software SecuritySecure Code Generation

    ♡Birzeit University · ♦University of Central Florida

  7. AIRA: AI-Induced Risk Audit: A Structured Inspection Framework for AI-Generated Code

    Apr 19, 2026William M. ParrisLLM AuditingStatic Code Analysis

    BDB Labs | Jurisprudential AI Governance Initiative

  8. Surgical Repair of Insecure Code Generation in LLMs

    Apr 17, 2026Gustavo Sandoval, Brendan Dolan-Gavitt, Siddharth GargMechanistic InterpretabilitySecure Code Generation

    Tandon School of Engineering New York University · XBOW

  9. DeepGuard: Secure Code Generation via Multi-Layer Semantic Aggregation

    Apr 10, 2026Li Huang, Zhongxin Liu, Yifan Wu +6Secure Code GenerationLLM Code Generation

    Chongqing University · The State Key Laboratory of Blockchain and Data Security, Zhejiang University · Peking University

  10. SecPI: Secure Code Generation with Reasoning Models via Security Reasoning Internalization

    Apr 4, 2026Hao Wang, Niels Mündler, Mark Vero +3Secure Code GenerationLLM Code Generation

    University of California, Berkeley · ETH Zurich

  11. VibeGuard: A Security Gate Framework for AI-Generated Code

    Apr 1, 2026Ying XieSecure Code GenerationSoftware Supply Chain Security

    Kennesaw State University

  12. Security-by-Design for LLM-Based Code Generation: Leveraging Internal Representations for Concept-Driven Steering Mechanisms

    Mar 11, 2026Maximilian Wendlinger, Daniel Kowatsch, Konstantin Böttinger +1Secure Code GenerationCode Language Models

    Cognitive Security Technologies Fraunhofer Institute for Applied and Integrated Security Garching near Munich, Germany

  13. Inference-Time Safety For Code LLMs Via Retrieval-Augmented Revision

    Mar 2, 2026Manisha Mukherjee, Vincent J. HellendoornLLM SafetySecure Code Generation

    Carnegie Mellon University, Pittsburgh, PA, USA

  14. Learning to Generate Secure Code via Token-Level Rewards

    Feb 26, 2026Jiazheng Quan, Xiaodong Li, Bin Wang +5Secure Code GenerationRL for Code Generation

    Fuyao University of Science and Technology · Xiamen University · Peking University +1

  15. SecCodeBench-V2 Technical Report

    Feb 17, 2026Longfei Chen, Ji Zhao, Lanxiao Cui +24Secure Code GenerationCode Generation Benchmarks

    TSINGHUA UNIVERSITY, BEIJING, CHINA · ALIBABA GROUP, HANGZHOU, CHINA

  16. HardSecBench: Benchmarking the Security Awareness of LLMs for Hardware Code Generation

    Jan 20, 2026Qirui Chen, Jingxian Shuai, Shuangwu Chen +8LLM SecuritySecure Code Generation

    University of Science and Technology of China, China · Xi’an Jiaotong University, China · Nanjing University, China +1

  17. SecureCode: A Production-Grade Multi-Turn Dataset for Training Security-Aware Code Generation Models

    Dec 20, 2025Scott ThorntonSoftware SecurityLLM Security

  18. Toward Secure Code Generation: Bridging Correctness and Security via Task-Adaptive Vulnerability Modeling and Execution-Based Benchmarking

    Jul 2, 2024Jiexin Wang, Liuwen Cao, Xitong Luo +6Execution-Guided Code GenerationAgentic Code Generation

    South China University of Technology, Guangzhou, China · University of Innsbruck, Innsbruck, Austria