Secure Code Generation

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3 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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AuraForge: Scaling Security Supervision for Training Coding Agents
Oct 1, 2026Danqing Wang, Songwen Zhao, Harsh Sharma +4AI Coding Agents Software Security
Carnegie Mellon University · University of California, Los Angeles · ScOp Venture Capital.
JevVibe: Efficient Classification-Guided Secure Code Generation
Sep 28, 2026Arshak Rezvani, Sasha Behrouzi, Ahmad-Reza SadeghiAutomated Program Repair Software Vulnerability Detection
Technical University of Darmstadt, Germany
CS-Guard: Benchmarking LLM Guardrails for Code Generation Security
Sep 9, 2026Jinyang Li, Mingyu Guo, Hung X. NguyenLLM Guardrails Adversarial Attacks on LLMs
Adelaide University Adelaide, Australia
Interpreting and Steering for Safe and Correct Code Generation
Aug 30, 2026Hao Yan, Ziyu YaoMechanistic Interpretability LLM Security
Department of Computer Science George Mason University, Fairfax, VA
MACGen: Toward Functionally Correct and Secure Code Generation via Multi-Agent Collaboration
Aug 26, 2026Miseon Yu, Jaehoon Choi, Younghan Lee +1Code Generation Secure Code Generation
Seoul National University · Seoul, Republic of Korea · Sungshin Women’s University
Security-First Evaluation of Text-to-Terraform: Benchmarking LLMs and SLMs for Secure IaC Generation
Aug 2, 2026Francis Luis Santos Vargas, Rodrigo Brandão Mansilha, Diego KreutzLLM Evaluation Code Generation
AI Horizon Labs, PPGES, Universidade Federal do Pampa (UNIPAMPA), Alegrete, Brazil
EduPluginBench: Executable Assurance for AI-Generated Educational Plugins
Aug 1, 2026Nizam KadirSoftware Security Runtime Assurance
Singapore University of Technology and Design, Science, Mathematics and Technology, Singapore, Singapore
SecDrift: Measuring Sector-Conditioned Security Drift in AI-Generated Code
Jul 28, 2026Narayanaswami Natraj Bharadwaj, Dhivya ChandramouleeswaranCybersecurity LLM Security
Independent Researcher USA
The Illusion of Secure LLM Code: Closing the Security Gap via Iterative Reprompting
Jul 26, 2026Ishpuneet Singh, Shreyas Mahajan, Gurjot Singh +1LLM Prompting Cybersecurity
Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, India · David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Canada
Poster: Rethinking Security in LLM Code Generation through Real-World Risk Scenarios
Jul 25, 2026Lixun Ma, Ruolong Ma, Bei Wang +4LLM Safety Benchmarks LLM Security
Zhejiang University, Hangzhou, China · University College London, London, United Kingdom · Artificial Intelligence Institute, CAICT, Beijing, China +1
Tool-Guided Retrieval-Augmented Repair for Securing LLM-Generated C Code
Jul 21, 2026Vidyut Sriram, Saatvik Pradhan, Suman SahaAutomated Program Repair Code Generation
The Pennsylvania State University
Functional and Secure Code Generation with Task Vectors
Jul 8, 2026Felix Wang, Anudeep Das, Mei Nagappan +1Code Generation LLM Safety Alignment
University of Waterloo, Waterloo, ON, Canada · KTH Royal Institute of Technology, Stockholm, Sweden
An Empirical Study of Security Calibration in Large Language Models for Code
Jun 30, 2026Mohammed Latif Siddiq, Md. Nafiu Rahman, Joanna C. S. SantosLLM Security Language Model Calibration
University of Notre Dame Notre Dame, IN, USA · Brac University Dhaka, Bangladesh
SoK: AI Secure Code Generation: Progress, Pitfalls, and Paths Forward
Jun 23, 2026Rupam Patir, Keyan Guo, Haipeng Cai +1AI Coding Agents Code Generation Evaluation
University at Buffalo, SUNY
Secure Coding Drift in LLM-Assisted Post-Quantum Cryptography Development: A Gamified Fix
Jun 17, 2026R. D. N. Shakya, C. P. Wijesiriwardana, S. M. Vidanagamachchi +1LLMs for Cybersecurity Secure Code Generation
University of Moratuwa Sri-Lanka, Moratuwa · University of Ruhuna Sri-Lanka, Matara · RMIT University Australia, Melbourne
SPARK: Security Knowledge Priming and Representation-Guided Knowledge Activation for LLM-based Secure Code Generation
Jun 15, 2026Xiaoyun Xu, Lichao Wu, Jona te Lintelo +2Knowledge Augmentation for Language Models LLM Security
Radboud University · University of Bristol · University of Zagreb
Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs
Jun 2, 2026Wenqi Chen, Ziyan Zhang, Bin Wang +3RL for Code Generation LLM Self-Correction
University of Electronic Science and Technology of China, Chengdu, China · Peking University, Beijing, China · University of Science and Technology of China, Hefei, China +2
Minimal Prompt Perturbations Lead to Code Vulnerabilities: Prompt Fragility and Hidden-State Signals in Coding LLMs
May 28, 2026Alexander Sternfeld, Andrei Kucharavy, Ljiljana DolamicPrompt Sensitivity Adversarial Attacks on LLMs
IEM, HES-SO, Le Foyer, Techno-Pôle 1, Sierre, Switzerland · Cyber-Defence Campus, armasuisse Science and Technology, Thun, Switzerland
Enhancing Reliability in LLM-Based Secure Code Generation
May 22, 2026Mohammed F. Kharma, Mohammad Alkhanafseh, Ahmed Sabbah +1LLM Evaluation CoT Reasoning
the Department of Computer Science, Birzeit University, Ramallah, Palestine · the Department of Computer Science, University of Central Florida, Orlando, FL 32816 USA
An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods
May 22, 2026Mohammed Kharma, Ahmed Sabbah, Mohammad Alkhanafseh +2LLM Prompting LLM 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
Security of LLM-generated Code: A Comparative Analysis
May 21, 2026Srivathsan G Morkonda, Mahmoud Selim, Hala AssalSoftware Security LLM Security
Carleton University, Ottawa, ON, Canada
Constrained Code Generation with Discrete Diffusion
May 16, 2026Lize Shao, Michael Cardei, Zichen Xie +2Constrained Generative Modeling Constrained Decoding
University of Virginia
SecureForge: Finding and Preventing Vulnerabilities in LLM-Generated Code via Prompt Optimization
May 8, 2026Houjun Liu, Lisa Einstein, John Yang +5LLM Auditing Prompt Optimization
Stanford University
A Quasi-Experimental Developer Study of Security Training in LLM-Assisted Web Application Development
Apr 20, 2026Mohammed Kharma, Ahmed Sabbah, Radi Jarrar +3Software Security Secure Code Generation
♡Birzeit University · ♦University of Central Florida
AIRA: AI-Induced Risk Audit: A Structured Inspection Framework for AI-Generated Code
Apr 19, 2026William M. ParrisLLM Auditing Static Code Analysis
BDB Labs | Jurisprudential AI Governance Initiative
Surgical Repair of Insecure Code Generation in LLMs
Apr 17, 2026Gustavo Sandoval, Brendan Dolan-Gavitt, Siddharth GargMechanistic Interpretability Secure Code Generation
Tandon School of Engineering New York University · XBOW
HardSecBench: Benchmarking the Security Awareness of LLMs for Hardware Code Generation
Jan 20, 2026Qirui Chen, Jingxian Shuai, Shuangwu Chen +8LLM Security Secure Code Generation
University of Science and Technology of China, China · Xi’an Jiaotong University, China · Nanjing University, China +1
SecureCode: A Production-Grade Multi-Turn Dataset for Training Security-Aware Code Generation Models
Dec 20, 2025Scott ThorntonSoftware Security LLM Security
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 Generation Agentic Code Generation
South China University of Technology, Guangzhou, China · University of Innsbruck, Innsbruck, Austria

Oct 1, 2026, cs.CRJ/K move · Enter open · S save

AuraForge: Scaling Security Supervision for Training Coding Agents

Danqing Wang, Songwen Zhao, Harsh Sharma, Jierui Wang+3

Carnegie Mellon University · University of California, Los Angeles · ScOp Venture Capital.

AI Coding Agents Software Security AI Agent Security Secure Code Generation Automated Test Generation

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Coding agents are now proficient enough to generate complex software applications from a single prompt. As their capabilities have grown, human oversight has increasingly shifted from line-by-line code review toward hands-off evaluation of outcomes. However, recent studies have shown that such a transition exposes a critical risk: functional correctness alone does not guarantee a secure implementation. Despite growing attention to code security, training safer coding agents remains challenging because reliable security supervision is difficult to obtain at scale from real-world repositories. We introduce AuraForge to synthesize and validate executable security tests for training secure coding agents. Our approach combines attack-oriented test synthesis, language-extensible task construction, and safeguards against reward hacking. Using AuraForge, we construct AuraGym, a multi-language and multi-CWE executable training gym: 679 executable feature-implementation tasks from 344 real-world repositories across Python, JavaScript, and TypeScript, covering 177 CWE categories. On the subset with human-written security tests, AuraForge produces about 3 times as many test cases on average and reduces the false-positive rate by 83.23%, allowing alternative secure implementations to receive correct supervision. Training Qwen3.5-4B with synthesized security tests gains larger improvements than human-written security tests (average 19.7 FuncPass and 6.2 SecPass vs. 14.9 FuncPass and 4.4 SecPass) on three languages. These results demonstrate that AuraForge provides more diverse and reliable security supervision to train secure coding agents.

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