Best Security Tools

This TypeScript library provides a comprehensive framework for implementing an OAuth 2.1 provider directly within Cloudflare Workers. It automates token management and request authentication, allowing developers to focus on building their API logic and UI. The framework is highly flexible, supporting custom handlers, dynamic client registration, and secure storage using Cloudflare KV.

little-rat is a Chrome extension designed to monitor and optionally block network requests made by other browser extensions. Users must enable specific browser flags to ensure the tool can effectively intercept traffic from other installed extensions. The project is open-source and provides a manual installation process for users to manage their browser's extension activity.

AI-Infra-Guard is a professional AI red teaming security assessment platform developed by Tencent Zhuque Lab, designed to provide comprehensive AI security risk self-inspection solutions for enterprises and individuals. The platform integrates core functions such as AI infrastructure vulnerability scanning, Agent workflow security assessment, MCP server scanning, and jailbreak testing. Users can deploy it quickly via Docker and utilize its modern Web interface and robust API to achieve efficient security detection and management.

This Claude Code skill automates the decompilation of Android APK, XAPK, JAR, and AAR files using powerful tools like jadx and Fernflower. It enables developers to extract HTTP APIs, Retrofit endpoints, and authentication patterns directly from obfuscated application code. The tool also provides comprehensive call flow analysis to help users document and reproduce app functionality without original source code.

vArmor is a cloud-native container sandbox system that utilizes AppArmor, BPF, and Seccomp technologies to enhance security within Kubernetes clusters. It helps organizations strengthen container isolation, reduce kernel attack surfaces, and mitigate risks from potential exploits or lateral movement. The system provides flexible enforcement models and built-in rules to simplify the hardening of containerized workloads.

Decepticon is an autonomous hacking agent designed to automate professional red team operations through a structured, kill-chain-based approach. The platform enforces strict rules of engagement and operational planning to ensure that all security testing remains regulated and auditable. By utilizing isolated sandbox environments and interactive shell sessions, it enables realistic adversary emulation while maintaining a clear separation between management and operational networks.

AI-Infra-Guard is a professional AI red teaming security assessment platform developed by Tencent Zhuque Lab, designed to provide comprehensive AI security risk self-inspection solutions for enterprises and individuals. The platform integrates core functions such as AI infrastructure vulnerability scanning, Agent workflow security assessment, MCP server scanning, and jailbreak testing. Users can deploy it quickly via Docker and utilize its modern Web interface and robust API to achieve efficient security detection and management.

SNI-Spoofing is a tool designed to bypass Deep Packet Inspection systems. It functions by performing specific manipulations on IP and TCP headers. The project aims to provide users with methods to circumvent network restrictions through these technical adjustments.

Shannon is an autonomous, white-box AI pentesting framework that analyzes source code to identify and exploit vulnerabilities in web applications and APIs. It bridges the security gap between manual penetration tests by enabling on-demand, automated testing that can be integrated into every build or release. The tool provides actionable, reproducible proof-of-concept exploits for confirmed vulnerabilities while ignoring non-exploitable findings.

This project reverse-engineers Google's SynthID AI watermarking system using spectral analysis and signal processing techniques without requiring access to proprietary encoders. It provides a robust detector with 90% accuracy and a V3 multi-resolution spectral bypass capable of significantly reducing watermark energy while maintaining high image quality. The system utilizes a multi-resolution spectral codebook to identify and surgically remove watermarks across various image resolutions.