Collected molecules will appear here. Add from search or explore.
A benchmarking framework designed to evaluate LLM-generated code simultaneously for functional correctness and security vulnerabilities based on the Common Weakness Enumeration (CWE).
Defensibility
stars
34
forks
6
CWEval addresses a critical intersection in AI development—ensuring that code which works is also secure. However, with only 34 stars and zero velocity over 500+ days, the project lacks any meaningful community traction or 'data gravity.' It functions essentially as a set of evaluation scripts and prompts that can be easily replicated. Frontier labs (OpenAI, Meta, Anthropic) are heavily invested in this space for safety alignment; Meta's CyberSecEval and HuggingFace's BigCode benchmarks are already the de facto standards for this type of analysis. The moat is non-existent because the value lies in the dataset of test cases, which is small here compared to industry-led efforts. GitHub (Microsoft) is also natively integrating security scanning (CodeQL) into Copilot, making external evaluation tools like this less relevant for developers.
TECH STACK
INTEGRATION
cli_tool
READINESS