DVLAA (Damn Vulnerable LLM and Agent Application) is a local LLM and Agent security range for OWASP LLM Top 10 and Agent security training.
🛡 The reference playbook for pentesting AI chatbots & LLM-powered apps in one place. Ready-to-use payloads covering the full OWASP LLM Top 10 plus frontier vectors (MCP · RAG · A2A · computer-use · voice)
🛡️ 大模型攻防渗透测试靶场 · 提示注入CTF / OWASP LLM Top10 / 脆弱Agent / 资料聚合。目标模型可切换：DeepSeek直连、OpenRouter中转站(国产+国外十余款小模型)、本地Ollama(DeepSeek-R1 8B离线)。一键本地部署。
Türkçe yapay zeka güvenliği kaynakları — prompt injection, jailbreak, red teaming, guardrail, ajan/MCP ve RAG güvenliği. Her kaynağın yanında neden listelendiğini anlatan Türkçe açıklama; ölü linkler CI ile taranıyor. · Turkish AI/LLM security resource list
A credential is not authorisation. ACP moves the authorise/refuse decision for AI agent actions outside the model, where prompt injection cannot reach it. Specification, Dafny proofs, and a reference implementation — every claim replays locally.
Agentic multi-agent framework for autonomous LLM vulnerability discovery: CVSSv4.0 scoring, 8-framework compliance mapping, SARIF output. OWASP LLM Top 10 (2025).
AISentinel · 大模型安全评测与 AI 内容鉴别平台：红队评测 → 运行时护栏 → 内容标识核验（三态判定）→ 合规自查
AWS-native AI Security Posture Management for AI agents (Observe • Govern • Defend). Discovery, OWASP/NIST/MITRE posture rules, runtime detection & Bedrock Guardrails enforcement, and AIDR integrations (Security Hub, GuardDuty) — open source, in-account, extensible.
🛡️ Open-source AI security scanner & LLM red-teaming platform. Test LLM APIs, chatbots, agents, MCP servers & RAG for prompt injection, jailbreaks, data leaks & unsafe tool use — with OWASP LLM Top 10 mapping and plain-English, audit-ready reports.
OWASP Top 10 for LLM Applications × MITRE ATLAS — a cross-version reference (2025 → 2026). Bilingual EN/TR.
模盾 ModelShield · AI大模型与智能体安全体检平台 | 自动化红队评测 + 中文攻击语料库 + 白话体检报告
AISRF, the AI Security & Research Framework: every LLM request from your apps and agents becomes a ticket a human approves before it reaches the backend. Analyzers, guardrails (Rebuff, LLM Guard, NeMo, Lakera), red teaming (garak, promptfoo, PyRIT), source code review, reports, MCP server.
Living aggregated LLM red-team corpus + cross-framework taxonomy (OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act, ISO 42001, KISA). CC-BY-4.0 (data) + MIT (code). Quarterly refresh.
Generate adversarial prompts and evaluate an offline detector for LLM red-team experiments.
Self-contained LLM red-team lab: deliberately-vulnerable app + garak/promptfoo/PyRIT harness mapped to OWASP LLM Top 10 (lab-only).
Laboratorio experimental del TFM «Evaluación de la Ciberseguridad en Entornos de IA Generativa» (UCM): un banco ficticio con asistente LLM, 108 fixtures de ataque OWASP, defensas deterministas y un LLM-SOC que audita qué componente decidió qué y por qué.
Notarize, govern, and audit AI agents — cryptographic seal, runtime guard, EU AI Act docs, AI-BOM, adversarial fuzzer
LLM Attack Surface Framework — the Nikto for OWASP LLM Top 10. Systematic offensive testing for AI features in modern web applications.
OWASP Top 10 for LLMs, Agents and MCP in plain English - attack walkthroughs, real-world examples and defensive playbooks.
面向中文场景的开源 LLM 红队测试工具 | An open-source red team toolkit for LLM applications, covering prompt injection, jailbreak and info leakage attacks, with OpenAI/Dify/MCP adapters and LLM-as-Judge automated evaluation. Aligned with OWASP LLM Top 10 and NSFOCUS threat matrix.
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