Agentseal

Agentseal

Open-source CLI security scanner that red-teams AI agent prompts, audits MCP servers at runtime, and catches poisoned skill files

82/100Safe BetFree · from $49/moFreemium

If you run coding agents or install MCP servers, AgentSeal answers a question most tools only theorize about: is this thing actually exploitable? Its runtime MCP verification — real attack payloads fired at a local binary, Docker image, or remote endpoint — and its cross-artifact XFLOW detection are the real differentiators, backed by registry research showing 66% of 1,808 scanned servers carried findings and lab tests confirming all six high-profile servers flagged were exploitable in

Verified 5d ago · liveness 82/100 · cite: rightaichoice.com/tools/agentseal

Best for
  • Security engineers red-teaming agent prompts and MCP servers before deployment
  • Developers on Cursor, Claude Code or Windsurf who install third-party skills and rules files
  • DevOps teams gating agent security in CI/CD with SARIF or JUnit output
  • Teams vetting third-party MCP servers via runtime sandbox testing
Not ideal for
  • Non-technical users who need a GUI-only security tool with a setup wizard
  • Teams that want a vendor-run managed program instead of running the CLI themselves
  • Buyers expecting a fully featured management console out of the box
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IntermediateFor a developer already comfortable in a terminal: roughly five minutes to pip or npm install and get the first guard result on your machine, with no API key required for guard, shield or scan-mcp. Add another ten to fifteen minutes to configure a provider key and run a full scan against a live model. CI wiring in GitHub Actions is a short workflow file if you want SARIF output from the firstCLI · Web · APIAPI availableVerified 5d ago
Pricing
Free · from $49/mo
FreemiumFree tier3 plans
Learning curve
Intermediate
For a developer already comfortable in a terminal: roughly five minutes to pip or npm install and get the first guard result on your machine, with no API key required for guard, shield or scan-mcp. Add another ten to fifteen minutes to configure a provider key and run a full scan against a live model. CI wiring in GitHub Actions is a short workflow file if you want SARIF output from the first
Runs on
CLIWebAPI
API available · 15 integrations
Who it's for
Developer adopting a third-party MCP serverSecurity engineer red-teaming a system promptDevOps engineer gating agent repos in CI
Live sentiment
Is Agentseal actually worth it?

We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.

  • Honest verdict, not marketing
  • Real pros & cons from real users
  • Attributed quotes with receipts
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3 free scans · no card needed

Skip it if

Skip AgentSeal if you want a vendor-hosted proxy or a managed security program running on your behalf rather than a CLI you install, run and gate CI with yourself.

The 30-second take
Price reality

For an open-source CLI security scanner, AgentSeal's cost profile is dominated by the LLM tokens your own provider bills you for during scan runs, not by the tool itself — guard, shield and scan-mcp do their file and tool-definition analysis locally with no model access. Teams comparing it against hosted prompt-security SaaS should weigh that token spend plus engineering time against a per-seat or per-request managed subscription.

In short

Agentseal — Open-source CLI security scanner that red-teams AI agent prompts, audits MCP servers at runtime, and catches poisoned skill files. Best for Security engineers red-teaming agent prompts and MCP servers before deployment, Developers on Cursor, Claude Code or Windsurf who install third-party skills and rules files, DevOps teams gating agent security in CI/CD with SARIF or JUnit output. Free to start; paid plans from $49/mo.

What's new in Agentseal

Checked 6 days ago

Across the latest 4 updates: 4 news mentions.

What people actually say about Agentseal — is it worth it?

We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.

20 mentions across 2 sources (Hacker News, Product Hunt) · researched Jul 3, 2026.

65% positive35% critical

Average across the 2 sources that answered — each source counts once, not each post.

Recurring strengths
  • +Fully open-source and free with no enterprise contracts required.
  • +Covers multiple attack surfaces: prompts, MCP servers, skill files.
  • +380+ attack probes for comprehensive vulnerability detection.
  • +Deterministic probes with unique canaries for reproducible CI results.
  • +CI/CD integration with GitHub Actions, SARIF, and JUnit.
Recurring frustrations
  • −Very limited community adoption—hard to gauge real-world effectiveness.
  • −Prompt scanning requires paid API access to an LLM provider.
  • −No plug-and-play cloud version—must run CLI or integrate yourself.
  • −Dashboard is basic and lacks advanced reporting features.
  • −MCP registry accuracy not independently verified.
Patterns worth knowing
Timely solution to an emerging security need
Seen on Product Hunt, Hacker News
Lack of real-world validation and community buzz
Seen on Hacker News
Comprehensive feature set on paper
Seen on Hacker News, Product Hunt
Learning curve
intermediateProductive in ~30 minutes

Viability Score

82/100
Safe Bet

How well maintained and how widely used is Agentseal? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this

Recent activity
90
Traction
100
Site health
95
User sentiment
65
What the vendor publishes
60

Last calculated: October 2026

How we score →

Key Features

  • 311 adversarial probes: 82 extraction, 143 injection, plus MCP, RAG and multimodal
  • Behavioral Genome suite adding 105 probes on top of the base set
  • 82 extraction probes covering personal hijack, persona hijack, encoding bypass and multi-turn escalation
  • 143 injection probes covering delimiter escape, Unicode tag, BiDi, crescendo and many-shot
  • 45 MCP tool poisoning probes: rug pull, tool shadowing, preference manipulation, schema injection
  • 28 RAG poisoning probes: memory persistence, entity substitution, sleeper triggers
  • 13 multimodal probes: image overlay, audio jailbreak, steganographic injection
  • Scan-MCP runtime testing against local binary, Docker image or remote HTTP endpoint in a sandbox
  • Cross-artifact XFLOW toxic flow detection for skill + MCP compound attacks
  • Guard: 6-stage pipeline scanning 12+ skill file formats with 15 analyzers
  • Guard auto-discovers 27 agent configurations (Cursor, Claude Code, Windsurf, Continue and more)
  • Watch: real-time file monitoring with quarantine and desktop notifications
  • MCP Registry of 9,100+ servers scored through a 7-stage security pipeline
  • Rug pull detection comparing live MCP tool signatures against recorded baselines
  • CI/CD integration with GitHub Actions, SARIF 2.1.0 and JUnit XML output

About Agentseal

FreemiumIntermediateAPI availableCLI · Web · API

AgentSeal is an open-source CLI security scanner for AI agents, installable via pip or npm, that inspects every surface an agent touches: system prompts, MCP servers, skill and rules files, and the machines running agents. It targets security engineers, developers running coding agents like Cursor and Claude Code, and DevOps teams who want agent security gated in CI instead of bolted on after a breach. The scan command fires 311 adversarial probes across five surfaces, while the broader suite covers 380+ probes including a 105-probe Behavioral Genome set. The scan command breaks down as 82 extraction and 109 injection probes across 39 categories in the base prompt set, plus 45 MCP tool poisoning, 28 RAG poisoning, and 13 multimodal probes. Every probe is deterministic with a unique canary, producing a 0-100 trust score, a PDF report, and a JSON finding list, grounded in published research including MPMA, MINJA, TAMAS, HashJack, and the OWASP Agentic Top 10. Guard auto-discovers 27 agent configurations and runs 15 analyzers across 12-plus skill file formats to catch command execution, credential exfiltration, base64 payloads, and Unicode tag attacks, including cross-artifact XFLOW rules that flag a skill file reading sensitive data beside an MCP server that can write to disk. Scan-MCP connects to a local binary, Docker image, or remote HTTP endpoint and invokes tools with real attack payloads in a sandbox rather than guessing from descriptions. Watch monitors skill files and MCP configs in real time, quarantining malicious content and firing a desktop notification, and the MCP registry scores over 9,100 servers through a 7-stage pipeline. Everything runs BYOK across 12 providers so prompts go straight to your provider, with a fully offline Ollama mode and zero telemetry. Against SaaS alternatives like Lakera or Prompt Security, AgentSeal trades polish for depth: a terminal-first workflow, no proxy layer, and MCP auditing that actually executes server code.

Behind the Verdict

AgentSeal earns its place by refusing to guess. Most agent-security scanners read a tool description and assign a risk score. AgentSeal's Scan-MCP connects to a server, runs it in a sandbox, and invokes its tools with real attack payloads, then compares tool signatures against a recorded baseline to catch rug pulls. That is a different category of evidence, and it is the reason to reach for this over a static analyzer. The registry work backs it up. Across 1,808 scanned MCP servers, 66% carried security findings. An analysis of 5,125 servers found 935 dangerous tool-combination paths across 555 of them, and in a 50-file sample of Cursor rules pulled from GitHub, six carried hidden instructions using zero-width Unicode and base64 payloads. Independent lab testing then confirmed all six high-profile servers flagged in the registry were exploitable at runtime, not just suspicious on paper. Pick AgentSeal when you run coding agents or install third-party MCP servers and you want a runtime answer before you ship. It fits security engineers red-teaming prompts, developers on Cursor or Claude Code vetting skills and rules files, and DevOps teams who want SARIF output blocking a PR on critical findings. The CI story is real: SARIF 2.1.0, JUnit XML, and GitHub Actions step summaries, with no enterprise contract required. Pass if no one on the team is comfortable in a terminal. The dashboard is minimal by design, and Guard, Watch, and Scan-MCP run without an API key but the core scan needs model access. Teams wanting a vendor-run managed program will not find that here — you run the CLI yourself. The BYOK model is the quiet advantage. Twelve providers, prompts go straight to your provider, and a fully offline Ollama mode means a regulated team can keep prompt data on its own

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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.

Developer adopting a third-party MCP server

You find an MCP server on GitHub and want it in your agent. You pull it locally, run scan-mcp against the binary in the sandbox, and let it invoke the tools with real attack payloads rather than reading the tool descriptions.

Outcome: You either get a runtime-verified pass and install with confidence, or you see the exploit fire in the sandbox instead of in your production agent.

Security engineer red-teaming a system prompt

Before an agent ships, you run scan against the system prompt with your own provider credentials, working through the extraction and injection phases, then review the 0-100 trust score and the JSON finding list.

Outcome: You hand engineering a weighted score, a PDF report and a reproducible finding set with canary evidence rather than a subjective opinion.

DevOps engineer gating agent repos in CI

You drop AgentSeal into a GitHub Actions workflow so every PR that touches skill files or MCP configs runs guard, and critical findings emit SARIF 2.1.0 into the code scanning tab.

Outcome: A PR that adds a poisoned .cursorrules file or a toxic MCP capability combination fails the check before merge.

Use Cases

  • Scan your system prompt for extraction and injection vulnerabilities before you ship an agent.
  • Audit a live MCP server with real attack payloads in a sandbox before you integrate it.
  • Monitor your machine for changes to agent skill files and MCP configs in real time.
  • Gate agent security in CI with GitHub Actions plus SARIF 2.1.0 or JUnit output.
  • Find toxic data flows where a skill file reads sensitive data next to an MCP server that can write to disk.
  • Browse the MCP Registry to shortlist pre-audited servers with published security scores.
  • Check Cursor rules, CLAUDE.md and .windsurfrules files for hidden instructions before adopting a repo.
  • Validate an MCP server vendor's security claims with runtime exploits instead of marketing copy.

Models Under the Hood

OllamaClaudeOpenAI

as of 2026-10-17

Limitations

  • The scan command runs adversarial probes against your own live model via BYOK across 12 LLM providers (Ollama, Claude, OpenAI among them), so you need a configured provider and your own API key.
  • Guard, shield and scan-mcp run locally without one, but Runtime MCP testing executes third-party server code inside a sandbox on your machine.
  • The product is CLI-first with a deliberately minimal dashboard for upload/sync rather than a full management console, and a clean report reflects coverage of AgentSeal's attack categories and probe suite rather than proof of safety.

as of 2026-10-02

Verification history

We have re-verified Agentseal 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.

  1. — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  2. — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  3. — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  4. — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  5. — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  6. — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it

Showing the 6 most recent of 7 verification passes.

Free to cite with attribution — this page re-verifies continuously.

12-month cost

Project the real annual outlay, including the implied monthly cost when only an annual tier is published.

Annual total
Free
Over 12 months
Effective monthly
Free
Billed monthly

Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.

Where the pricing makes sense

The company stage and team size where Agentseal's pricing actually pencils out — and where peers do it cheaper.

For an open-source CLI security scanner, AgentSeal's cost profile is dominated by the LLM tokens your own provider bills you for during scan runs, not by the tool itself — guard, shield and scan-mcp do their file and tool-definition analysis locally with no model access. Teams comparing it against hosted prompt-security SaaS should weigh that token spend plus engineering time against a per-seat or per-request managed subscription.

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 a developer already comfortable in a terminal: roughly five minutes to pip or npm install and get the first guard result on your machine, with no API key required for guard, shield or scan-mcp. Add another ten to fifteen minutes to configure a provider key and run a full scan against a live model. CI wiring in GitHub Actions is a short workflow file if you want SARIF output from the first

Switching to or from Agentseal

How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.

Migrating in
  • →From manual MCP server review: replace reading tool descriptions by hand with scan-mcp runtime payload testing in a sandbox.
  • →From ad-hoc prompt red-teaming: replace one-off chat attempts with the deterministic 311-probe scan suite and a weighted trust score.
  • →From a hosted prompt-security SaaS: keep the same findings output but move prompt data off the vendor proxy and onto your own provider credentials.
Migrating out
  • ↗To a managed prompt-security platform: move to a hosted proxy if you need vendor-run monitoring and a fully featured console rather than a CLI.
  • ↗To a general SAST or dependency scanner: use it alongside AgentSeal if your compliance reporting needs one consolidated findings dashboard.

Integrations

GitHub ActionsGitHub Advanced SecurityAzure DevOpsDefect DojoOllamaOpenAIAnthropic ClaudeGoogle GeminiDeepSeekGroqOpenRouterTogether AILM Studiollama.cppvLLM

Resources & Guides

Tutorials & Learning

YouTube returned 6 videos for “Agentseal”, and we withheld 6: 6 could not be judged, because “Agentseal” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Agentseal.

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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Frequently Asked Questions

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