Showing 2 open source projects for "vulnerability test"

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    AICGSecEval

    AICGSecEval

    A.S.E (AICGSecEval) is a repository-level AI-generated code security

    ...The project was developed to address concerns that AI-assisted programming tools may produce insecure code containing vulnerabilities such as injection flaws or unsafe logic. The framework constructs evaluation tasks based on real-world software repositories and known vulnerability cases derived from CVE records. By simulating realistic development scenarios, the benchmark assesses how well AI code generation systems handle security-sensitive programming tasks. AICGSecEval combines static and dynamic evaluation techniques to analyze generated code for vulnerabilities and functional correctness. The framework includes datasets, test cases, and evaluation metrics that measure how AI programming tools perform across multiple programming languages and vulnerability categories.
    Downloads: 0 This Week
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  • 2
    Giskard

    Giskard

    Collaborative & Open-Source Quality Assurance for all AI models

    ...At Giskard, we believe that Machine Learning needs its own testing framework. Created by ML engineers for ML engineers, Giskard enables you to scan your model to find dozens of vulnerabilities. The Giskard scan automatically detects vulnerability issues such as performance bias, data leakage, unrobustness, spurious correlation, overconfidence, underconfidence, unethical issue, etc. Giskard automatically generates relevant tests based on the vulnerabilities detected by the scan. You can easily customize the tests depending on your use case by defining domain-specific data slicers and transformers as fixtures of your test suites.
    Downloads: 1 This Week
    Last Update:
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