Showing 2 open source projects for "android forensics tools"

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  • Airlock Digital - Application Control (Allowlisting) Made Simple Icon
    Airlock Digital - Application Control (Allowlisting) Made Simple

    Airlock Digital delivers an easy-to-manage and scalable application control solution to protect endpoints with confidence.

    For organizations seeking the most effective way to prevent malware and ransomware in their environments. It has been designed to provide scalable, efficient endpoint security for organizations with even the most diverse architectures and rigorous compliance requirements. Built by practitioners for the world’s largest and most secure organizations, Airlock Digital delivers precision Application Control & Allowlisting for the modern enterprise.
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  • Caller ID Reputation provides the most comprehensive view of your caller ID scores across all carriers Icon
    Caller ID Reputation provides the most comprehensive view of your caller ID scores across all carriers

    Instantly identify flagged caller IDs and decrease flags by up to 95% your first month.

    Keep your agents on the phone with increased connection rates by monitoring your phone number reputation across all major carriers and call blocking apps.
    Learn More
  • 1
    JADX-AI-MCP

    JADX-AI-MCP

    Plugin for JADX to integrate MCP server

    JADX-AI-MCP is an open-source plugin that integrates large language models into the JADX Android decompiler to assist with reverse engineering and code analysis tasks. The project connects JADX with AI assistants through the Model Context Protocol, enabling language models to interact directly with decompiled Android application code. Through this integration, AI systems can inspect classes, analyze methods, retrieve application manifests, and examine other elements of Android packages in real time. ...
    Downloads: 4 This Week
    Last Update:
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  • 2
    mllm

    mllm

    Fast Multimodal LLM on Mobile Devices

    mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies...
    Downloads: 1 This Week
    Last Update:
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