Agentseal
Open-source security scanner for AI agents: red-team prompts, audit MCP servers, detect vulnerabilities.
AgentSeal fills a critical gap for agent security with a comprehensive, open-source approach. Its deterministic probes and runtime MCP verification set it apart from static scanners, though the CLI focus and dashboard setup may deter less technical teams.
- Security engineers red-teaming AI agent deployments
- Developers building or using coding agents (Cursor, Claude Code, etc.)
- DevOps teams integrating agent security into CI/CD pipelines
- AI researchers studying prompt injection and MCP vulnerabilities
- Non-technical users who need a GUI-only tool
- Teams seeking managed commercial support without self-hosting
- Users wanting a production-ready dashboard without setup
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3 free scans · no card needed
Skip AgentSeal if you prefer a fully managed GUI security dashboard with no CLI setup.
Prompt scanning requires you to supply your own LLM API key (e.g., OpenAI or Claude), which incurs usage costs beyond AgentSeal itself.
AgentSeal's free, open-source pricing fits any team size. There are no paid tiers, unlike commercial alternatives like Protect AI or Snyk that charge per seat or server. It's ideal for cost-conscious security teams and individual developers.
In short
Agentseal — Open-source security scanner for AI agents: red-team prompts, audit MCP servers, detect vulnerabilities. Best for Security engineers red-teaming AI agent deployments, Developers building or using coding agents (Cursor, Claude Code, etc.), DevOps teams integrating agent security into CI/CD pipelines. Free to use.
What's new in Agentseal
Checked 12 days agoAcross the latest 4 updates: 4 news mentions.
From Static Findings to Working Exploits: Runtime Validation of 6 High-Profile MCP Servers
Controlled lab testing of 6 MCP servers with 68K+ combined GitHub stars; every flagged vulnerability was successfully exploited.
555 MCP Servers Have Toxic Data Flows. Here's What We Found.
Attack surface analysis of 5,125 MCP servers reveals 935 dangerous tool combination paths across 555 servers.
We Scanned 1,808 MCP Servers. 66% Had Security Findings.
A year of MCP breaches, real data from registry, and why defense matters even when perfect security is not achievable.
We Scanned 50 Cursor Rules Files From GitHub. 6 Had Hidden Instructions.
Zero-width Unicode characters, base64 payloads, and toxic data flows turn AI coding agents into attack vectors.
Viability Score
How likely is Agentseal to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- 380+ adversarial probes for prompt injection and extraction
- Guard: scans machine for dangerous skill files and MCP configs (6-stage pipeline)
- Shield: real-time monitoring of skill files and MCP configs with quarantine
- Scan-MCP: connects to running MCP servers and detects tool poisoning
- MCP Registry with 9,100+ servers analyzed via 7-stage security pipeline
- Runtime verification of MCP servers in isolated containers
- CI/CD integration: GitHub Actions, SARIF 2.1.0, JUnit, policy-as-code
- Supports 12 LLM providers (Ollama, Claude, OpenAI, Gemini, DeepSeek, etc.)
- Deterministic probes with unique canaries for reproducible CI results
- Behavioral Genome: 105 probes for multi-turn adaptive mutations
- Cross-artifact toxic flow detection (skill file + MCP compound attacks)
- Auto-discovers 27 agent configurations (Cursor, Claude Code, Windsurf, Continue)
- Scans 12 skill file formats (.cursorrules, CLAUDE.md, .windsurfrules, skill.md)
- 15 analyzers for command execution, credential exfiltration, base64 payloads, Unicode tag attacks
- Offline mode: works with local Ollama models, zero telemetry
About Agentseal
AgentSeal is an open-source security toolkit designed to protect AI agents across every layer of their attack surface. It scans system prompts for extraction and injection vulnerabilities, audits MCP servers for tool poisoning, detects poisoned skill files (Cursor rules, instruction files, etc.), and monitors machines in real-time for configuration drift. The tool is built for developers, security teams, and AI practitioners who deploy coding agents or LLM-powered workflows. It works without requiring API keys for machine-level scans — guard, shield, and scan-mcp use local pattern matching, deobfuscation, and semantic analysis. For prompt scanning (scan), you provide model access. AgentSeal runs via CLI, integrates into CI/CD pipelines (GitHub Actions, SARIF, JUnit), and offers a dashboard for viewing results. It currently includes 380+ attack probes across extraction, injection, RAG poisoning, multimodal attacks, and behavioral genome testing. The MCP Registry (9,100+ servers analyzed) provides runtime-verified security scores. What makes AgentSeal different is its emphasis on reproducibility and evidence: every probe is deterministic with unique canaries, and the MCP registry uses a 7-stage sandboxed pipeline before scoring. It is fully open-source and free, with no enterprise contracts required.
Behind the Verdict
AgentSeal is a must-have for any team deploying AI coding agents like Cursor or Claude Code. Its strength lies in its depth: 380+ probes, 7-stage MCP verification, and real-time monitoring are features you'd expect from a paid commercial product, but it's completely free and open-source. The recent findings (66% of MCP servers have security issues, 555 servers with toxic data flows) validate the tool's necessity. However, the CLI-only interface and reliance on model access for prompt scanning may limit adoption by less technical security teams. For DevOps and security engineers, the CI/CD integration and deterministic probes make it a reliable gatekeeper. It's not for non-technical users or those seeking a fully managed dashboard without setup.
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Real-world workflow fit
Concrete scenarios for the personas Agentseal actually fits — and what changes day-one when you adopt it.
Before deploying a new Cursor rule, run AgentSeal's guard command to scan the rule file for hidden base64 payloads or credential exfiltration instructions.
Outcome: Detect a malicious rule that would have exfiltrated API keys; rule is quarantined before any agent executes it.
Add AgentSeal's GitHub Action to the CI pipeline to scan each MCP server before merging, using SARIF output for code review.
Outcome: Automatically block a pull request that introduces a vulnerable MCP server with tool poisoning.
Browse the MCP Registry to identify servers with toxic data flows, then use scan-mcp to validate findings locally.
Outcome: Publish a paper on 66% of MCP servers having security findings, citing runtime-verified data.
Use Cases
- Scan your system prompt for extraction and injection vulnerabilities before deployment.
- Audit a live MCP server for tool poisoning before integrating it into your agent.
- Monitor your machine for changes to agent skill files and MCP configs in real time.
- Integrate agent security checks into your CI pipeline using GitHub Actions and SARIF output.
- Discover toxic data flows that combine skill files and MCP servers into compound attacks.
- Browse the MCP Registry to find pre-audited servers with known security scores.
Models Under the Hood
as of 2026-07-17
Limitations
- Prompt scanning requires model access (API key) and does not work offline.
- Machine scanning (guard, shield, scan-mcp) works without keys but only locally.
- The dashboard is available at agentseal.org/dashboard but may require registration.
- Coverage is limited to threats detectable via pattern matching and semantic analysis; zero-day attacks may bypass.
as of 2026-07-05
Where the pricing makes sense
The company stage and team size where Agentseal's pricing actually pencils out — and where peers do it cheaper.
AgentSeal's free, open-source pricing fits any team size. There are no paid tiers, unlike commercial alternatives like Protect AI or Snyk that charge per seat or server. It's ideal for cost-conscious security teams and individual developers.
Setup time & first value
How long it actually takes to get something useful out of Agentseal — broken out by persona, not the marketing-page minute.
For developers: CLI install takes 2 minutes via npm or homebrew. Running your first scan takes less than 10 minutes. For CI/CD integration: adding the GitHub Action takes 5 minutes. For real-time monitoring: configuring shield daemon takes about 15 minutes.
Integrations
Resources & Guides
Official links
Tools that pair well with Agentseal
Common stack mates teams adopt alongside Agentseal, with the specific reason each pairing earns its keep.
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