llms.txt@packages/website/public git:20261016.1750a96A

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# PanGuard AI

> PanGuard AI is the commercial platform for AI agent security built on ATR
> (Agent Threat Rules), an open, MIT-licensed detection standard with
> 822 effective rules in v4.1.5. PanGuard adds runtime enforcement, pre-install
> auditing, and migration and compliance tooling. Community is free; Founding
> Pilot and Enterprise tiers add the platform layer.

## Core stats

- ATR: 822 effective rules in v4.1.5, 10 threat categories, MIT
- OWASP Agentic Top 10: 10/10 categories mapped
- garak in-the-wild jailbreaks: 92.3% recall on 650 samples (hunt lane; partly closed-book, because some rules were written from this corpus).
- garak full probe corpus (23 families, 3,475 prompts): 57.2% recall (hunt lane, also partly closed-book). By family: latentinjection 34.4%, sysprompt_extraction 96.4%, dan 92.5%.
- SKILL.md: 100% recall on 498 samples (hunt lane, in-sample: the benign samples are the set the rules are tuned against, so precision and false-positive figures are not cited).
- PINT-format corpus, self-built from deepset prompt-injections + Lakera Gandalf (NOT Lakera's official PINT benchmark): 65.41% recall, 100% precision on 850 samples. It is effectively a prompt-injection-family score.
- HackAPrompt (EMNLP 2023): 69.6% recall on 4,780 samples, measured on ATR v3.5.0. Closed-book: ATR mined rules from this corpus's misses, and 28.6% is ATR's own recall before them. The corpus is attack-only, so precision and false-positive rate are undefined on it.
- The benign-gate false-positive rates once quoted for a "65,000-sample" gate were withdrawn on 2026-09-19 pending re-measurement. There is no single engine-wide false-positive number.
- Recall figures above are the hunt lane (all effective rules). The enforce lane, which is what runs when blocking is on, recalls far less.
- Wild scan (2026-04): 101,280 published AI agent skills and MCP servers from five public sources, scanned 2026-04-13 with scan engine v2.0.0 (113 ATR rules, not today's rule set); 1,434 flagged. A flag is a rule match, not a verdict, so no confirmed-malicious count is published.
- The panguard.ai web scanner runs 650 rules from agent-threat-rules v3.5.8

## Core products

- [PanGuard product overview](https://panguard.ai/product)
- [Skill Auditor](https://panguard.ai/product/skill-auditor): 8-check pre-install gate for AI agent skills
- [PanGuard Scan](https://panguard.ai/product/scan): pre-install audit with ATR, Sigma and YARA rule engines
- [PanGuard Guard](https://panguard.ai/product/guard): 4-agent runtime pipeline (detect, analyze, respond, report)
- [PanGuard Migrator](https://panguard.ai/migrator): converts legacy Sigma/YARA detections into ATR YAML
- [PanGuard MCP Server](https://panguard.ai/product/mcp): panguard_* tools for Claude Code, Cursor, OpenClaw and other MCP clients
- [ATR Standard](https://panguard.ai/atr): the open detection standard
- [Threat Cloud](https://panguard.ai/threat-cloud): shared intelligence; candidate rules are reviewed before they ship

## Pricing

- [Pricing](https://panguard.ai/pricing): Community ($0, MIT, self-hosted), Founding Pilot ($25K one-time, self-serve), Enterprise and up (from $150K, sales-led)

## Benchmarks and research

- [Benchmark results](https://panguard.ai/research/benchmarks): each result with its corpus, lane, ATR version and caveats
- [Wild scan report](https://panguard.ai/research/96k-scan): the April 2026 scan of published agent skills
- [MCP ecosystem scan](https://panguard.ai/research/mcp-ecosystem-scan): the March 2026 scan of MCP server packages

## Documentation

- [Getting Started](https://docs.panguard.ai/getting-started)
- [Installation](https://docs.panguard.ai/installation): macOS / Linux / Windows / npm
- [Quickstart](https://docs.panguard.ai/quickstart)
- [ATR concept page](https://docs.panguard.ai/atr)
- [CLI Reference](https://docs.panguard.ai/cli): 23 commands
- [Skill Auditor docs](https://docs.panguard.ai/products/skill-auditor)
- [Guard docs](https://docs.panguard.ai/products/guard): 11 response actions
- [Scan docs](https://docs.panguard.ai/products/scan)
- [Threat Cloud docs](https://docs.panguard.ai/products/threat-cloud)

## ATR (Agent Threat Rules)

- Repo: https://github.com/Agent-Threat-Rule/agent-threat-rules
- npm: `agent-threat-rules` (v4.1.5)
- License: MIT
- Where it has been merged, with evidence: ADOPTERS.md in the repository (maintainer-accepted contributions, not vendor endorsements)

## Company

- [About PanGuard](https://panguard.ai/about)
- [Trust Center](https://panguard.ai/trust)
- [Compliance](https://panguard.ai/compliance)
- [Sovereign AI Defense brief](https://sovereign-ai-defense.vercel.app)
- [Blog](https://panguard.ai/blog)
- [GitHub](https://github.com/panguard-ai/panguard-ai)
- [Full context for AI tools](https://panguard.ai/llms-full.txt)

## Founder

- Adam Lin (林冠辛), founder. Email: adam@agentthreatrule.org. GitHub: github.com/eeee2345. Self-taught engineer, based in Taiwan.