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New dataset trains AI to generate secure code, covering web and AI/ML vulnerabilities

By PulseAugur Editorial · [1 sources] ·

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]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset trains AI to generate secure code, covering web and AI/ML vulnerabilities

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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]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Scott Thornton ·

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

    arXiv:2512.18542v3 Announce Type: replace-cross Abstract: AI coding assistants produce vulnerable code in 45\% of security-relevant scenarios~\cite{veracode2025}, yet no public training dataset teaches both traditional web security and AI/ML-specific defenses in a format suitable…

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