Showing 4 open source projects for "source code static anala"

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  • 1
    AICGSecEval

    AICGSecEval

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

    AICGSecEval is an open-source benchmark framework designed to evaluate the security of code generated by artificial intelligence systems. 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.
    Downloads: 0 This Week
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  • 2
    Strix

    Strix

    Open-source AI hackers to find and fix your app’s vulnerabilities

    Strix is an open source agent-driven security platform that uses autonomous AI agents to identify, investigate, and validate vulnerabilities in software applications. The system is designed to mimic the behavior of real attackers by executing dynamic testing and verifying findings through proof-of-concept exploitation. Unlike traditional vulnerability scanners that rely heavily on static analysis, Strix agents actively run code, probe systems, and attempt exploitation to confirm whether vulnerabilities are genuinely exploitable. ...
    Downloads: 27 This Week
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  • 3
    Hollama

    Hollama

    A minimal LLM chat app that runs entirely in your browser

    Hollama is a lightweight open-source chat application designed to run entirely within the browser while interacting with large language model servers. The project provides a minimal but powerful user interface for communicating with local or remote LLMs, including servers powered by Ollama or OpenAI-compatible APIs. Because the application runs as a static web interface, it does not require complex backend infrastructure and can be easily deployed or self-hosted.
    Downloads: 8 This Week
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  • 4
    Agentic RAG for Dummies

    Agentic RAG for Dummies

    A modular Agentic RAG built with LangGraph

    Agentic RAG for Dummies is an educational repository that demonstrates how to build retrieval-augmented generation systems combined with autonomous AI agents. The project explains the principles behind agentic retrieval pipelines where language models can dynamically decide when to retrieve information, analyze results, and plan further actions. Instead of relying on static retrieval pipelines, the system shows how agents can orchestrate retrieval, reasoning, and tool usage in a more...
    Downloads: 7 This Week
    Last Update:
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