cpaczek/any-buddy
quality grade C, 55 out of 100Hack Claude Code to get any buddy you want
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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Guardrails, PII redaction, prompt-injection defense, interpretability and offensive/defensive AI security.
Signals: ai-safety, ai-security, guardrails, prompt-injection, jailbreak, llm-security, interpretability, explainable-ai
381 results
Hack Claude Code to get any buddy you want
Humanizer 的汉化版本,Claude Code Skills,旨在消除文本中 AI 生成的痕迹。
The free build of Claude Code. All telemetry removed, security-prompt guardrails stripped, all experimental features enabled.
2026.3.31 claude code 意外把包含源码的文件上传到 npm 仓库,版本号是 2.1.88,其中 cli.js.map 文件有 57MB 的体积,claude code 的源码在该文件的 sourcesContent 字段里面,解压还原后有 70w 行代码
Hacky repo to see what the Copilot extension sends to the server
Microsoft Security Copilot is a generative AI-powered security solution that helps increase the efficiency and capabilities of defenders to improve security outcomes at machine speed and scale, while remaining compliant to responsible AI principles
腾讯云智能渗透黑客松 Official repository of Tencent Cloud Intelligent Penetration Hackathon. Showcasing top open-source projects of LLM-based autonomous penetration agents, including multi-agent collaboration, automated penetration, AI-driven offensive security, and intelligent attack-defense solutions.
Behavioral guardrails for Claude Code, distilled from Andrej Karpathy's field notes on where LLMs go wrong when they write software.
A comprehensive security checklist for MCP-based AI tools. Built by SlowMist to safeguard LLM plugin ecosystems.
AI Code Security Anti-Patterns distilled from 150+ sources to help LLMs generate safer code.
[NeurIPS D&B '25] The one-stop repository for LLM unlearning
awesome papers in LLM interpretability
Dromedary: towards helpful, ethical and reliable LLMs.
Papers and resources related to the security and privacy of LLMs 🤖
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A powerful tool for automated LLM fuzzing. It is designed to help developers and security researchers identify and mitigate potential jailbreaks in their LLM APIs.
New ways of breaking app-integrated LLMs
Set of tools to assess and improve LLM security.
[ICLR 2025] FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models
A resource repository for machine unlearning in large language models
Universal and Transferable Attacks on Aligned Language Models
A Platform for Secure Analytics and Machine Learning
Hack AI/ML applications — CTF challenges for model attacks, LLMs and AI Agent exploitation.
Explain & debug any blackbox machine learning model with a single line of code.
24,523 repositories in the index in total.