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Ai迷思录（应用与安全指南）
The main features of acmesec/theaimythbook are: AI Application Security.
Projects with overlapping indexed features include: superagent-ai/superagent — Superagent is an AI safety platform that protects applications from prompt injections, data leaks, and harmful outputs… harishsg993010/damn-vulnerable-mcp-server — This project is an educational and research platform designed to simulate security vulnerabilities within… anthropics/defending-code-reference-harness — This project is a framework for the autonomous discovery and remediation of security vulnerabilities using large… cisco-ai-defense/skill-scanner. leondz/garak — Garak is a suite of tools for measuring AI reliability, scanning for vulnerabilities, and automating security… mnns/llmfuzzer — This project is no longer actively maintained. You are welcome to fork and continue its development on your own. Thank…
Superagent is an AI safety platform that protects applications from prompt injections, data leaks, and harmful outputs through built-in guardrails. It functions as a prompt injection detection system, data redaction tool, and red team testing tool, automatically removing personally identifiable information and protected health data from AI inputs and outputs while scanning image uploads with vision AI to detect visual prompt injection attacks before processing. The platform routes every prompt through a sequential pipeline of safety checks including injection detection, data redaction, and co
This project is an educational and research platform designed to simulate security vulnerabilities within AI-integrated systems and Model Context Protocol implementations. It provides a controlled environment where users can practice identifying and mitigating common attack vectors, such as prompt injection and unauthorized code execution, by interacting with intentionally insecure tools and protocol configurations. The platform distinguishes itself by offering a dedicated laboratory for auditing Model Context Protocol integrations. It exposes server-side functions as discoverable tools and p
This project is a framework for the autonomous discovery and remediation of security vulnerabilities using large language model agents. It functions as a security research pipeline that automates the process of reconnaissance, crash discovery, and exploitability analysis to identify reproducible software bugs. The system distinguishes itself by utilizing a containerized agent sandbox that restricts network egress and filesystem access to prevent host compromise. It employs a specialized patch generation and validation loop, which includes adversarial re-attack testing where a fresh agent atte
