SecureCode v2: 8 AI Models Stop 45% Code Risks

    
        By vramkickedin    
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            January 28, 2026 at 2:54 pm        
    
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        2 min read

Developer Scthornton have unveiled SecureCode v2, a dataset designed to address critical security vulnerabilities in AI-generated code. With 1,215 rigorously validated examples spanning 11 programming languages, the project targets the alarming statistic that 45% of AI coding assistants produce vulnerable code implementations (Yikes!).

Comprehensive Security Model Collection

The SecureCode v2 project introduces eight security-focused code generation models ranging from 3 billion to 20 billion parameters. These models are specifically trained on real-world security incidents, providing developers with AI assistants that understand and prevent common vulnerability patterns.

The 8 key models in the collection include:

DeepSeek-Coder 6.7B - SecureCode Edition
CodeLlama 13B - SecureCode Edition
StarCoder2 15B - SecureCode Edition
Llama 3.2 3B - SecureCode Edition
Qwen 2.5-Coder 7B - SecureCode Edition
IBM Granite 20B Code - SecureCode Edition
CodeGemma 7B - SecureCode Edition
Qwen 2.5-Coder 14B - SecureCode Edition

Incident-Grounded Training Approach

'I built the SecureCode model collection to solve this problem. Eight security-aware code models, trained on real-world breach patterns, designed to generate secure code by default.' states Scthornton. Each model leverages a unique dataset that includes actual security incidents like the Equifax 2017 breach, which cost $1.4 billion due to a single vulnerable code pattern.

The developer continues 'Every model in this collection was trained on lessons learned from real breaches. When you use them, you're getting security knowledge that companies paid for with incident response costs, regulatory penalties, and reputational damage.'.

Read the dev's full post here