Researchers have introduced SecureCode, a new dataset designed to train AI models to generate more secure code. The dataset addresses both traditional web application security, covering the OWASP Top 10 2021, and AI/ML-specific security concerns outlined in the OWASP LLM Top 10 2025. It features 2,185 multi-turn conversational examples structured for instruction tuning, with a focus on practical application across various frameworks and languages. The dataset has undergone rigorous quality assurance and is available on Hugging Face, accompanied by fine-tuned open-source models and an evaluation framework. AI
IMPACT Enhances AI coding assistants' ability to produce secure code, potentially reducing vulnerabilities in software development.
RANK_REASON The item describes a new dataset and associated models for training AI, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]
- arXiv
- Hugging Face
- LangChain
- OpenAI
- OWASP LLM Top 10 2025
- OWASP Top 10 2021
- QLoRA
- Scott Thornton
- SecureCode
- Veracode
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