Showing 8 open source projects for "security platform"

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  • 1
    Strix

    Strix

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

    ...The platform is intended for developers and security teams that need rapid security assessments without the overhead of manual penetration testing engagements. Strix can orchestrate multiple cooperating agents that divide investigation tasks and collaboratively analyze complex applications or infrastructure.
    Downloads: 4 This Week
    Last Update:
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  • 2
    TONL

    TONL

    TONL (Token-Optimized Notation Language)

    TONL is a cutting-edge data platform built around a production-ready serialization format designed to be both compact and powerful, combining human readability with performance features that make it suitable for large-scale applications and AI workflows. It provides a serialization format that significantly reduces token usage compared with traditional JSON, which can result in lower costs and more efficient prompt size utilization in LLM-driven systems. TONL isn’t just a format — it...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Floneum

    Floneum

    Instant, controllable, local pre-trained AI models in Rust

    ...Floneum supports a plugin architecture that allows external components to extend the platform while maintaining isolation and security. Many plugins can be written in different programming languages and compiled to WebAssembly modules, allowing them to run safely within the system. The platform is implemented primarily in Rust and emphasizes performance, modularity, and local execution.
    Downloads: 0 This Week
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  • 4
    csghub-server

    csghub-server

    csghub-server is the backend server for CSGHub

    ...Built primarily in the Go programming language, the system enables organizations to run model inference, training, and fine-tuning tasks within a unified platform. It integrates capabilities similar to model repositories like Hugging Face while allowing enterprises to host and manage their AI assets internally for security and compliance purposes.
    Downloads: 0 This Week
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  • 5
    chatd

    chatd

    Chat with your documents using local AI

    chatd is an open-source desktop application that allows users to interact with their documents through a locally running large language model. The software focuses on privacy and security by ensuring that all document processing and inference occur entirely on the user’s computer without sending data to external cloud services. It includes a built-in integration with the Ollama runtime, which provides a cross-platform environment for running large language models locally. The application typically runs models such as Mistral-7B and allows users to load and analyze documents while asking questions in natural language. ...
    Downloads: 0 This Week
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  • 6
    SmythOS

    SmythOS

    Cloud-native runtime for agentic AI

    SmythOS SRE (Smyth Runtime Environment) is an open-source runtime and development platform designed for building and operating production-grade AI agents. It provides a foundational infrastructure layer that functions similarly to an operating system for agentic AI systems, managing resources such as language models, storage, vector databases, and caching through a unified interface. Developers can use the runtime to create, deploy, and orchestrate intelligent agents across local machines,...
    Downloads: 0 This Week
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  • 7
    Superagent

    Superagent

    Superagent protects your AI applications

    ...The platform also scans code repositories to detect AI-specific attack vectors like repo poisoning. Superagent is designed for low-latency production environments and works with any major LLM provider. It enables teams to prove compliance with modern AI security and regulatory standards.
    Downloads: 0 This Week
    Last Update:
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  • 8
    Beelzebub

    Beelzebub

    A secure low code honeypot framework

    ...Honeypots are systems intentionally exposed to attackers in order to capture malicious behavior, and Beelzebub enhances this concept by incorporating artificial intelligence and virtualization techniques. The platform allows organizations and researchers to deploy decoy services that mimic real infrastructure while recording attacker interactions. By using AI models to simulate realistic system behavior, the honeypot becomes harder for attackers to identify, increasing the likelihood that malicious activity can be observed and analyzed. The framework is designed with a low-code configuration approach so security teams can easily deploy honeypots for multiple services and ports.
    Downloads: 1 This Week
    Last Update:
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