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muellerberndt/awesome-ai-security

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An AI security awesome list / learning journey

Overview

A curated, annotated list of resources for AI security: prompt injection, adversarial machine learning, model privacy, AI red teaming, and using AI for offensive and defensive security work. Pull requests are welcome. Add your entry to this README, in the section it belongs to, in the same format as the entries around it: The link should be public and working, and the description should say what the resource does rather than how good it is. Essential machine learning concepts and courses to build a foundation before diving into AI security. - Stanford CS229: Machine Learning - Stanford's foundational ML course covering supervised learning, deep learning, generalization, and unsupervised learning. Taught by leaders in the field. - fast.ai Practical Deep Learning for Coders - Free, top-down approach to deep learning with PyTorch. Covers computer vision, NLP, and tabular data with hands-on Jupyter notebooks.

README

Awesome AI Security

A curated, annotated list of resources for AI security: prompt injection, adversarial machine learning, model privacy, AI red teaming, and using AI for offensive and defensive security work.

Contributing

Pull requests are welcome. Add your entry to this README, in the section it belongs to, in the same format as the entries around it:

- [Name](https://example.com) - One sentence on what it is or does.

The link should be public and working, and the description should say what the resource does rather than how good it is.

ML Foundations

Essential machine learning concepts and courses to build a foundation before diving into AI security.

Deep Learning

Deep dive into neural networks, transformers, and the architectures behind modern AI systems.

Prompt Injection

Understand prompt injection attacks that manipulate LLM behavior through crafted inputs.

  • Prompt Injection & the Rise of Prompt Attacks: All You Need to Know - Explains prompt injection threats, examples, and mitigations.
  • OpenAI Says AI Browsers May Always Be Vulnerable to Prompt Injection Attacks - Discusses ongoing risks and hardening efforts for agentic AI like Atlas.
  • Prompt Injection Attacks in 2025: Risks, Defenses & Testing - Mainstream risks and testing strategies for prompt injections.
  • Prompt Injection Attacks: The Most Common AI Exploit in 2025 - Detection, blocking, and mitigation for growing prompt injection threats.
  • LLM01:2025 Prompt Injection - Updated risk overview for manipulating model behavior. OWASP Gen AI Security Project, 2025.
  • Rebuff - Self-hardening prompt injection detector by ProtectAI.
  • Garak - NVIDIA’s LLM vulnerability scanner with dozens of plugins testing for jailbreaks, prompt injection, data leakage, and more.
  • Vigil LLM - Detects prompt injections and risky inputs.
  • EasyJailbreak - Framework for adversarial jailbreak prompts.
  • Prompt Shield - Open-source prompt injection detection engine with 27 detectors and cross-domain techniques from bioinformatics and forensic linguistics.
  • Agent Browser Shield - Browser extension that strips prompt injection (hidden text and HTML comments) from web pages before an AI agent’s model sees them; also masks PII and removes dark patterns.
  • AI Village @ DEF CON - Challenges like LLM Jailbreak and AI security research.
  • Red Teaming Language Models to Reduce Harms - Systematic red teaming findings and public dataset. Anthropic, arXiv:2209.07858, 2022.
  • OWASP Top 10 for LLM Applications 2025 - Critical risks including prompt injection, sensitive info disclosure, supply chain, and data poisoning.
  • JailbreakBench - Benchmark for LLM jailbreak attacks and defenses.
  • hermes-jailbench - Zero-LLM deterministic jailbreak regression benchmark: repeatable battery of known-pattern attacks, scored refusal/partial/compliance across runs.
  • LLM Security Papers (chawins/llm-sp) - Papers and resources on LLM security and privacy including indirect prompt injection research.
  • Armorer Guard - SDKs and integration contracts for a guard that screens AI-agent tool calls for prompt injection, credential leakage and exfiltration before execution.
  • hego.red - Hands-on notes on LLM red teaming: prompt injection, jailbreaks, indirect injection, RAG and agent testing, with a scoping methodology and worked labs.
  • Koma - Zero-dependency Node.js and TypeScript library that filters prompt injection, audio hallucinations and RAG scraping at the application boundary.
  • Sentinel Scan CLI - CLI and MCP server that scans MCP manifests for tool poisoning and rug-pulls, and runs a prompt injection and jailbreak suite against your own LLM endpoint.
  • RansomLeak AI Security Training - Browser-based labs on prompt injection, jailbreaking and LLM attack scenarios, mapped to the OWASP Top 10 for LLM and agentic AI. Commercial training.
  • Skill-audit - Scanner for agent skills that flags prompt injection, dangerous shell use and secret access before installation. 31 rules, SARIF output, zero dependencies.

Adversarial Attacks

Learn how adversarial examples fool neural networks and methods to defend against them.

Poisoning & Backdoors

Data poisoning attacks and neural network backdoors that compromise model integrity.

Privacy & Extraction

Model extraction, membership inference, and training data extraction attacks.

Tools & Frameworks

Security tools for testing and defending AI systems against adversarial attacks.

  • APort - AI agent identity verification and policy enforcement for autonomous systems.
  • Counterfit - Microsoft penetration testing tool for ML systems.
  • Whistleblower - Repello AI’s offensive tool for testing LLM applications against system prompt leakage attacks.
  • NeMo Guardrails - NVIDIA programmable guardrails for LLM safety and security.
  • SecML - Secure and explainable ML library with attacks and defenses.
  • Purple Llama (Meta) - Open-source LLM safety tools including Llama Guard, Prompt Guard, Code Shield, and CyberSec Eval benchmarks.
  • Agent-Wiz - CLI that extracts agent workflows from LangChain, LangGraph, CrewAI and AutoGen and runs threat modeling over the resulting graphs.
  • ai-evaluation - LLM evaluation framework with 50+ metrics, LLM-as-judge and guardrail scanners covering injection, PII and unsafe-output checks.
  • SkilLock - Behavior-pinning lockfile and capability-delta review for agent skills; blocks unapproved drift in shell, network and file access in CI with SARIF output.
  • Nika - Rust workflow engine for AI runs with hash-chained execution traces, default-deny allowlists for shell, network, file and tool access, and static secret-flow analysis.
  • SourceryKit - Python SDK that checks an agent’s tool calls and MCP handoffs against a trusted-endpoint allowlist and records the provenance of each answer.
  • AI Security Registry - Registry of skills, goals and workflows for AI agents, with git-pinned versions reviewed before each update.
  • sofagent - Harness for governing AI coding agents: commit-time audit rules over git diffs, an HMAC-signed audit trail and snapshot rollback, exposed as an MCP toolset.
  • Bifrost - AI gateway unifying access to model providers and MCP servers, with guardrails, approvals, audit logs and access control at the edge.
  • KeyDrift - Scans deployed HTML and JavaScript for secrets that AI-generated code inlines into the client bundle, separating public browser credentials from real leaks.
  • AgentShield - Scanner for MCP servers, agent skills and plugins that runs thirteen engines over a package and returns one report. Runs offline via npx with no install.
  • SpecLock - Enforces the constraints written in CLAUDE.md, AGENTS.md and .cursorrules before an AI coding agent edits a file, runs a shell command or commits, with an override audit trail and an MCP server.
  • rust-norion - Rust control layer for local LLM agents with writer and evidence gates, memory and replay governance, and rollback, so agent self-modification stays inspectable and reversible.
  • API Relay Audit - Local Python security audit for AI API relays and LLM proxies, with probes for hidden instructions, package-command rewriting, error leakage and SSE anomalies, and Markdown reports.
  • SUNGLASSES - Open-source local input firewall for AI agents that scans text, files, PDFs, images and QR codes for prompt injection, credential leaks and data exfiltration with 1,554 patterns across 118 categories, shipped as a CLI, Python API, MCP server and Claude Code hook.

AI Pentesting

Using AI assistants and agents for automated penetration testing and security assessments.

Vulnerability Detection

AI-powered vulnerability scanning, code analysis, and bug detection.

Exploit Generation

AI-assisted exploit development and attack automation techniques.

AI Security Tools

Tools that leverage AI for offensive security operations and analysis.

  • Hound - AI auditor that builds adaptive knowledge graphs for deep code reasoning. Uses tiered AI approach for autonomous vulnerability discovery.
  • HackGPT - LLM toolkit for offensive security.
  • HackingBuddyGPT - Autonomous red-teaming agent with benchmarks.
  • GhidrAssist - LLM extension for Ghidra with ReAct agentic mode for autonomous reverse engineering investigation.
  • PyRIT (Python Risk Identification Tool) - Microsoft red-teaming framework for generative AI. Automates adversarial prompt generation and risk assessment.
  • AI Security Analyzer - Generates security docs from codebases.
  • BurpGPT - Burp Suite extension for AI-powered vulnerability scanning.
  • CAI: Cybersecurity AI - Framework for building AI-driven security tools by Alias Robotics.

Benchmarks & Standards

Industry standards, threat frameworks, and evaluation benchmarks for AI security.

  • ScaBench - Smart contract audit benchmark with 500+ real-world vulnerabilities from Code4rena, Cantina, and Sherlock for evaluating AI audit agents.
  • International AI Safety Report 2025 - Summarizes evidence on general-purpose AI safety, including robustness.
  • RobustBench - Leaderboard for adversarial robustness benchmarking.
  • Stanford AIR-Bench 2024 - AI safety benchmark aligned with emerging government regulations and company policies.
  • FLI AI Safety Index 2024 - Future of Life Institute’s assessment of AI company safety practices and accountability.
  • MITRE ATLAS - Adversarial Threat Landscape for AI Systems. Threat matrix documenting real-world attacks on ML (like ATT&CK for AI).
  • NIST AI Risk Management Framework - Framework for managing AI risks throughout the AI lifecycle.
  • Agent Threat Rules (ATR) - Open detection-rule standard for AI agent threats across ten categories, with MITRE ATLAS and OWASP crosswalks. Sigma-style executable rules, MIT-licensed.
  • agent-evidence-vectors - Conformance vectors and a reference Go verifier for in-toto attestations of AI agent execution, plus SCITT/COSE carriage vectors that keep their own checker until the verifier reads them. Each outcome is recomputed from the bytes the attestation carries.

Books

Essential books covering AI security, adversarial ML, and security applications.

Communities & Events

AI security communities, conferences, and events to stay connected.

Newsletters & Lists

Newsletters and awesome lists to stay current with AI security developments.


© muellerberndt · GitHub

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