Security tools for AI agents — scan dangerous Skills/MCP configs, detect prompt injection, audit tool permissions, and harden agent supply chains.
Agent Security tools are AI-powered software designed to help developers and teams tackle agent security-related tasks more efficiently. These tools are typically published as open-source projects on GitHub and can be integrated into existing workflows via MCP (Model Context Protocol), Claude Skills, or standalone agent frameworks. On Agent Skills Hub, we index 30 quality-scored agent security tools across languages including Python, TypeScript, Go.
In 2026, the AI agent ecosystem is maturing rapidly. Agent Security tools can significantly boost development efficiency by automating repetitive tasks, reducing human error, and providing intelligent suggestions. The top 3 tools — agentseal, agentseal, shellward — have earned an average of 641 GitHub stars, reflecting strong community validation. 25 of the listed tools come with clear open-source licenses, ensuring freedom to use and modify.
When choosing a agent security tool, consider these factors: 1) Community activity — GitHub stars and recent commit frequency indicate reliability; 2) Integration method — check if it supports MCP, Claude, or your preferred agent framework; 3) Language compatibility — the most common language in this list is Python; 4) Quality score — Agent Skills Hub's composite score evaluates code quality, documentation completeness, and maintenance activity. Our recommendation: start with agentseal — it ranks highest in both star count and quality score.
Security toolkit for AI agents. Scan your machine for dangerous skills and MCP configs, monitor for supply chain attacks, test prompt injection resistance, and audit live MCP servers for tool poisoning.
Security toolkit for AI agents. Scan your machine for dangerous skills and MCP configs, monitor for supply chain attacks, test prompt injection resistance, and audit live MCP servers for tool poisoning.
AI Agent Security Middleware — 8-layer defense, DLP data flow, prompt injection detection, zero dependencies. SDK + MCP server for Claude Code, Cursor, LangChain, Hermes Agent & more.
Security guardrails for Claude Code, MCP tools, and Claude cowork workflows. Local-first modular YARA-style guard packs for secrets, exfiltration, prompt injection, MCP abuse, and risky agent actions.
Open detection standard for AI agent threats. Like Sigma, but for prompt injection, tool poisoning, and MCP attacks. Community-driven -- contributions welcome.
Firewall for AI agents. DLP scanning, SSRF protection, bidirectional MCP scanning, tool poisoning detection, and prompt injection blocking.
Security scanner MCP server for AI coding agents. Prompt injection firewall, package hallucination detection (4.3M+ packages), 1000+ vulnerability rules with AST & taint analysis, auto-fix.
Open source prompt injection protection for Agents calling tools (via MCP, CLI or direct function calling). Detect and defend against prompt injection attacks. 22MB, CPU-only, < 10ms latency.
MCP Security Solution for Agentic AI — real-time proxying, behavior analysis, and malicious tool detection
SlowMist Agent Security Skill: A comprehensive security review framework for AI agents operating in adversarial environments. Core principle: Every external input is untrusted until verified.
```bash
cd ~/.openclaw/workspace/skills
git clone https://github.com/slowmist/slowmist-agent-security.git
```
nono - a capability-based, multiplexing sandbox tool, built for developers - lift'n'shift seamless path to prod. Run agents securely without needing any additional infra, zero setup, zero latency.
Build Secure and Compliant AI agents and MCP Servers. YC W23
Advanced prompt injection defense system for AI agents. Multi-language detection, severity scoring, and security auditing.
Static security scanner for LLM agents — prompt injection, MCP config auditing, taint analysis. 49 rules mapped to OWASP Agentic Top 10 (2026). Works with LangChain, CrewAI, AutoGen.
Security proxy for AI agents. Scans every message for prompt injection, PII, and secrets. Defense-in-depth: Go proxy + iptables firewall + eBPF kernel monitor. YAML policy engine, audit logging, 5 AI agents with RAG knowledge bases.
ClawdSecbot is a professional AI Bot security protection solution, providing security capabilities including real-time threat detection, prompt injection protection, and security auditing to comprehensively protect your AI applications. ClawdSecbot 是一款专业的 AI Bot 安全防护解决方案,提供实时威胁检测、提示词注入防护、安全审计等安全能力,全方位保护您的 AI 应用安全。
A comprehensive reference for securing Large Language Models (LLMs). Covers OWASP GenAI Top-10 risks, prompt injection, adversarial attacks, real-world incidents, and practical defenses. Includes catalogs of red-teaming tools, guardrails, and mitigation strategies to help developers, researchers, and security teams deploy AI responsibly.
ToolHive is an enterprise-grade platform for running and managing Model Context Protocol (MCP) servers.
Enterprise AI bastion host for secure AI API and MCP access, with unified proxying, RBAC, audit logs, rate limiting, and cost tracking across OpenAI, Anthropic, Gemini, and self-hosted LLMs.
MCP for Security: A collection of Model Context Protocol servers for popular security tools like SQLMap, FFUF, NMAP, Masscan and more. Integrate security testing and penetration testing into AI workflows.
AI-first security scanner with 76 analyzers, 9,600+ detection rules, and repo poisoning detection for AI/ML, LLM agents, and MCP servers. Scan any GitHub repo with: medusa scan --git user/repo
A plugin-based gateway that orchestrates other MCPs and allows developers to build upon it enterprise-grade agents.
See what your AI agents can access. Scan MCP configs for exposed secrets, shadow APIs, and AI models. Generate AI-BOMs for compliance.
Security audit tool for Claude Desktop and Claude Code on macOS — single-command visibility into MCP servers, extensions, plugins, connectors, scheduled tasks, and permissions.
The antivirus for OpenClaw — approve dangerous actions, scan skills, block secret leaks, and keep humans in control, for safety.
Superagent protects your AI applications against prompt injections, data leaks, and harmful outputs. Embed safety directly into your app and prove compliance to your customers.
Open-source firewall for AI agents. Policy engine that audits and controls what OpenClaw, Claude Code, Cursor, Codex, and any AI tool can do on your machine.
AI-powered bug bounty hunting from your terminal - recon, 20 vuln classes, autonomous hunting, and report generation. All inside Claude Code.
Scan MCP servers for potential threats & security findings.
AI agent security scanner. Detect vulnerabilities in agent configurations, MCP servers, and tool permissions. Available as CLI, GitHub Action, ECC plugin, and GitHub App integration. 🛡️
| Tool | Stars | Language | License | Score |
|---|---|---|---|---|
| agentseal | ★ 231 | Python | — | 41 |
| agentseal | ★ 156 | Python | — | 40 |
| shellward | ★ 60 | TypeScript | Apache-2.0 | 50 |
| secure-claude-code | ★ 88 | Python | MIT | 43 |
| agent-threat-rules | ★ 97 | TypeScript | MIT | 38 |
| pipelock | ★ 342 | Go | Apache-2.0 | 42 |
| agent-security-scanner-mcp | ★ 100 | JavaScript | MIT | 38 |
| defender | ★ 97 | TypeScript | Apache-2.0 | 36 |
| MCP-Dandan | ★ 58 | Python | MIT | 33 |
| slowmist-agent-security | ★ 450 | — | MIT | 50 |
| nono | ★ 2.2k | Rust | Apache-2.0 | 41 |
| compliant-llm | ★ 158 | Python | MIT | 28 |
| prompt-guard | ★ 145 | Python | MIT | 47 |
| agent-audit | ★ 138 | Python | MIT | 43 |
| clawshield-public | ★ 111 | Go | Apache-2.0 | 44 |
| ClawdSecbot | ★ 81 | Go | GPL-3.0 | 41 |
| LLMSecurityGuide | ★ 61 | — | — | 40 |
| toolhive | ★ 1.8k | Go | Apache-2.0 | 46 |
| ThinkWatch | ★ 838 | Rust | — | 47 |
| mcp-for-security | ★ 598 | TypeScript | MIT | 44 |
| medusa | ★ 458 | Python | AGPL-3.0 | 43 |
| mcp-gateway | ★ 352 | Python | MIT | 39 |
| mcp-audit | ★ 149 | Python | MIT | 41 |
| claudit-sec | ★ 107 | PowerShell | Apache-2.0 | 39 |
| ClawGuard | ★ 93 | TypeScript | — | 32 |
| superagent | ★ 6.5k | TypeScript | MIT | 46 |
| rampart | ★ 68 | Go | Apache-2.0 | 35 |
| claude-bug-bounty | ★ 2.1k | Python | MIT | 50 |
| mcp-scanner | ★ 923 | Python | Apache-2.0 | 49 |
| agentshield | ★ 628 | TypeScript | MIT | 53 |
The top agent security tools in 2026 are agentseal, agentseal, shellward. Agent Skills Hub ranks 30 options by GitHub stars, quality score (6 dimensions including completeness, examples, and agent readiness), and recent activity. The list is rebuilt every 8 hours from live GitHub data.
agentseal (231 stars) is the most adopted choice for general agent security workflows, written in Python. agentseal (156 stars) is a strong alternative. Pick by your existing stack: match the language and runtime your team already uses to minimize integration cost. If unsure, start with agentseal — it has the deepest community and the most examples online.
Avoid pre-built agent security tools when (1) your use case requires deep customization that the tool's plugin system doesn't support, (2) you have strict compliance requirements that ban third-party dependencies, (3) the tool's maintenance is inactive (last commit >6 months ago), or (4) your data volume is small enough that a 50-line custom script is cheaper than learning the tool. For most production workflows above 100 requests/day, the time savings from a maintained tool outweigh the customization loss.
Agent Security focuses specifically on security tools for ai agents — scan dangerous skills/mcp configs, detect prompt injection, audit tool permissions, and harden agent supply chains. CI/CD & DevOps is a related but distinct category — see https://agentskillshub.top/best/ci-cd/ for those tools. The two often appear in the same agent pipeline but solve different problems: choose agent security when your primary goal is the specific task, and ci/cd & devops when the workflow is broader.
For most teams, yes. agentseal has 231 stars worth of community testing, handles edge cases you haven't thought of, and ships with documentation. Build your own only when (1) your requirements are deeply non-standard, (2) you have a security/compliance reason to avoid OSS dependencies, or (3) the maintenance burden is small enough (<200 lines of code) that you'll save time long-term. The break-even point is usually around 2-3 weeks of dev time saved.
Most agent security tools listed are open source under permissive licenses (MIT, Apache 2.0). A handful offer paid managed/cloud versions on top of free self-hosted core. Always check the LICENSE file on each tool's GitHub repository before commercial use — some use AGPL or non-commercial restrictions that may not fit your deployment model.