{ "data": { "a": { "slug": "guardrails-ai", "name": "Guardrails AI", "vendor": "Guardrails AI (Harvey)", "vendorUrl": "https://www.guardrailsai.com", "kind": "framework", "category": "guardrails", "summary": "Open-source Python framework for validating LLM inputs and outputs, with configurable actions for failed checks and an API server.", "url": "https://www.anchorterminal.com/tools/guardrails-ai", "markdownUrl": "https://www.anchorterminal.com/tools/guardrails-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/guardrails-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/guardrails-ai.json", "repo": "https://github.com/guardrails-ai/guardrails", "license": "Apache-2.0", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "guardrails-ai" }, { "registry": "npm", "name": "@guardrails-ai/core" } ], "auth": "none", "authNotes": "None of its own since the Hub closed. Validators install from public PyPI as `guardrails-ai-\u003cname\u003e` with no `guardrails configure` step, and the models behind them run locally or on an endpoint you host. The server has no built-in auth.", "pricing": "free", "pricingNotes": "Apache-2.0 library and server. The hosted remote inference that some validators used (detect_pii, toxic_language, competitor_check, nsfw_text) was free and was switched off on 2026-08-25, so those validators now cost whatever it takes to run their models yourself with use_local=True or on your own endpoint (https://github.com/guardrails-ai/guardrails/blob/main/HUB_UPDATE.md).", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 7300, "npmWeekly": 81, "pypiWeekly": 32438, "asOf": "2026-09-30" }, "docsUrl": "https://www.guardrailsai.com/docs", "capabilities": [ "guard.injection", "guard.pii", "guard.moderation", "guard.policy", "guard.self-host" ], "tags": [ "framework", "open-source", "self-hosted", "local", "python", "free", "openai-compatible", "incidents" ], "lastRelease": "2026-08-14", "graded": true, "anchor": { "graded": true, "score": 49.6, "grade": "D", "agentReady": false, "rank": 604, "ranked": true, "rankOf": 722, "categoryRank": 9, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 63, "maintenance": 44, "payments": 60, "reliability": 58, "schema": 59, "security": 44, "transparency": 59 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": -6, "negativeNotes": [ "2026-05-11 supply-chain compromise. An attacker used an employee's GitHub token to run Actions across 30 repositories, took deploy secrets and published a malicious guardrails-ai 0.10.1 to PyPI. Quarantined in about two hours, tokens rotated, Hub and Snowglobe keys force-rotated on 13 May, and a full advisory published telling anyone who installed 0.10.1 to treat the host as compromised. Fixed and documented, so partly decayed (-6). https://github.com/guardrails-ai/guardrails/blob/main/SECURITY_ADVISORY.md" ], "verdict": "Validators have configurable actions for failed checks. Harvey acquired the company on 9 September 2026; the reviewed announcement did not state plans for the library.", "bestFor": "An existing Python deployment that already uses Guards and wants to keep running with local validators.", "strengths": [ "Guard and validator API that reads well, with an on_fail action per validator", "Validators are plain PyPI packages, from PII and toxicity to schema and competitor checks", "Guardrails Server turns a guard into an OpenAI-compatible endpoint any client can point at", "Full public advisory after the May 2026 incident, with the attack chain and rotation steps", "Apache-2.0 with nothing to buy" ], "weaknesses": [ "Acquired by Harvey on 9 September 2026 with no statement on the library", "Hub, private registry and hosted inference closed on 25 August 2026, so model-backed validators need your own compute", "Malicious 0.10.1 release on PyPI in May 2026 from a compromised token", "0.11.0 has no release notes on GitHub, and open 1.0.0 issues plan to remove reask, on_fail and RAIL", "Metrics on by default in the client config" ], "agentNotes": [ "Pin guardrails-ai==0.11.0 and each guardrails-ai-\u003cvalidator\u003e package, install only from PyPI, and never install 0.10.1", "Import validators from guardrails_ai.\u003cname\u003e, not guardrails.hub, and don't run guardrails hub install", "Pass use_local=True to detect_pii, toxic_language and the other model-backed validators, or set validation_endpoint to a server you run", "Set enable_metrics to false in ~/.guardrailsrc if you don't want usage metrics sent", "Avoid building on reask and RAIL. The open 1.0.0 issues plan to remove both" ], "metrics": { "kind": "library", "measured": false }, "reviewCount": 2, "avgRating": 2, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 49.6 } ], "editorialScores": { "ergonomics": 63, "maintenance": 44, "payments": 60, "reliability": 58, "schema": 59, "security": 44, "transparency": 63 }, "provenanceScore": 55 }, "connect": { "install": "pip install guardrails-ai==0.11.0 guardrails-ai-detect-pii # validators are plain PyPI packages since 2026-08-25", "http": "curl -X POST http://localhost:8000/guards/my_guard/openai/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"gpt-4o-mini\",\"messages\":[{\"role\":\"user\",\"content\":\"My card number is 4111 1111 1111 1111, is that safe to share?\"}]}'" }, "letme": { "capability": "https://letme.dev/guard.injection", "tool": "https://letme.dev/guardrails-ai" }, "area": "models", "provenance": { "legalEntity": "Guardrails AI, Inc.", "domain": "guardrailsai.com", "domainRegistered": "", "domainNote": "A library. The code is on github.com under guardrails-ai and the packages on PyPI. The company is now part of Harvey (harvey.ai).", "endpointOnVendorDomain": null, "terms": "https://guardrailsai.com/legal/terms-of-use", "privacy": "https://guardrailsai.com/legal/privacy-policy", "statusPage": "", "changelog": "https://github.com/guardrails-ai/guardrails/releases", "securityTxt": "unknown", "checked": "2026-09-30", "notes": [ "The terms of use (last updated 2025-08-14) name Guardrails AI, Inc. and predate the Harvey acquisition. The site banner reads Guardrails AI joins Harvey.", "The advisory names Snowglobe, a sister product whose keys were rotated after the May 2026 incident." ], "score": 55 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/guardrails-ai.json", "live": { "slug": "guardrails-ai", "versions": [ { "registry": "github", "name": "guardrails-ai/guardrails", "version": "v0.11.0", "released": "2026-08-14", "seenAt": "2026-10-08T16:15:19.191244231Z" }, { "registry": "npm", "name": "@guardrails-ai/core", "version": "0.1.1", "seenAt": "2026-10-08T16:15:15.58617083Z" }, { "registry": "pypi", "name": "guardrails-ai", "version": "0.11.0", "released": "2026-08-14", "seenAt": "2026-10-08T16:15:15.387166124Z" } ], "githubStars": 7497, "npmWeekly": 80, "pypiWeekly": 23079, "securityTxt": { "url": "https://guardrailsai.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:38:41.243240106Z" }, "domain": { "domain": "guardrailsai.com", "registered": "2023-03-30", "source": "https://rdap.verisign.com/com/v1/domain/guardrailsai.com", "checkedAt": "2026-10-04T13:05:34.738860824Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/guardrails-ai/guardrails/main/HUB_UPDATE.md", "kind": "deprecations", "status": 304, "checkedAt": "2026-10-08T18:24:19.873781681Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "346e78b2231d" }, { "url": "https://www.harvey.ai/blog/guardrails-ai-joins-harvey", "kind": "deprecations", "status": 200, "checkedAt": "2026-10-08T18:28:06.891800962Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "ac8d49a8249b" }, { "url": "https://guardrailsai.com/legal/privacy-policy", "kind": "privacy", "status": 304, "checkedAt": "2026-10-08T18:20:45.234159968Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "9ee9470cc655" }, { "url": "https://guardrailsai.com/legal/terms-of-use", "kind": "terms", "status": 304, "checkedAt": "2026-10-08T18:20:47.471339395Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e46fda5fa053" } ], "updatedAt": "2026-10-08T18:28:06.891800962Z" } }, "answer": "Presidio scores 66 (B) on agent readiness against Guardrails AI's 49.6 (D), and leads in 6 of 7 scored categories.", "b": { "slug": "microsoft-presidio", "name": "Presidio", "vendor": "Data Privacy Stack", "vendorUrl": "https://dataprivacystack.org", "kind": "sdk", "category": "guardrails", "summary": "Open-source Python library and Docker services that detect personal data in text and images and replace, mask, hash or encrypt it. Created at Microsoft and run since June 2026 by the community organisation Data Privacy Stack.", "url": "https://www.anchorterminal.com/tools/microsoft-presidio", "markdownUrl": "https://www.anchorterminal.com/tools/microsoft-presidio.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/microsoft-presidio.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/microsoft-presidio.json", "repo": "https://github.com/data-privacy-stack/presidio", "license": "MIT", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "presidio-analyzer" }, { "registry": "pypi", "name": "presidio-anonymizer" }, { "registry": "pypi", "name": "presidio-image-redactor" }, { "registry": "pypi", "name": "presidio" } ], "auth": "none", "authNotes": "None. The Python library runs in the caller's process, and the REST containers accept any caller. The FAQ states the endpoints have no built-in authentication by design and should sit behind a gateway, reverse proxy or service mesh (https://presidio.dataprivacystack.org/faq/). Optional recognisers that call Azure AI Language, Azure Health Data Services or a language model take those services' own credentials.", "pricing": "free", "pricingNotes": "Free under the MIT licence, with no hosted or paid option from the project and no account needed. The cost is the compute to run it, plus any outside service an optional recogniser is configured to call (https://github.com/data-privacy-stack/presidio/blob/main/LICENSE).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 11231, "npmWeekly": null, "pypiWeekly": 1217281, "asOf": "2026-10-08" }, "docsUrl": "https://presidio.dataprivacystack.org", "openapi": "https://presidio.dataprivacystack.org/api-docs/api-docs.yml", "capabilities": [ "guard.pii", "guard.self-host" ], "tags": [ "sdk", "open-source", "self-hosted", "local", "python", "free", "docker", "openapi", "pii", "community-governed" ], "lastRelease": "2026-07-22", "graded": true, "anchor": { "graded": true, "score": 66, "grade": "B", "agentReady": false, "rank": 248, "ranked": true, "rankOf": 722, "categoryRank": 5, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 69, "maintenance": 63, "payments": 60, "reliability": 78, "schema": 69, "security": 53, "transparency": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "MIT-licensed personal data detector with a public OpenAPI document, tests on Python 3.10 to 3.14 and about 1.2 million weekly PyPI downloads. The REST containers have no authentication, the project states no SLA or support, and it covers personal data only, with no prompt injection or content moderation checks.", "bestFor": "Detecting and masking personal data in prompts, outputs, logs and images on the owner's own machines, with detection tuned by entity, threshold and custom recognisers.", "strengths": [ "MIT licence, source on GitHub, and nothing to buy. No account, key or card is needed to install or run it", "OpenAPI 3.0 document for the analyser and anonymiser REST services, with request examples and 400 and 422 error shapes", "CI runs each package on Python 3.10, 3.11, 3.12, 3.13 and 3.14, with CodeQL and Dependabot configured", "Detection is tunable per call with an entity list, a score threshold, an allow list and ad hoc recognisers", "Anonymiser operators cover replace, redact, mask, hash, encrypt and custom functions, and encrypted values can be reversed with the key" ], "weaknesses": [ "The REST containers have no authentication by design. The FAQ says to put a gateway or proxy in front", "SUPPORT.md states no SLA and no official support. The project is run by volunteers since leaving Microsoft", "One release in the 90 days to 8 October 2026 (2.2.364 on 22 July), and CHANGELOG.md has no section for it", "Covers personal data only. No prompt injection, jailbreak or content moderation checks", "The README warns that detection is automated and may miss personal data, so other protections are still needed", "98 open pull requests, and most issues opened since 20 September 2026 had no reply on 8 October" ], "agentNotes": [ "Install from PyPI or pull images from ghcr.io/data-privacy-stack. The mcr.microsoft.com/presidio-* images are no longer updated", "Download a spaCy model (python -m spacy download en_core_web_lg) before the first `AnalyzerEngine()` call, or use the Docker image", "Send both text and language to `/analyze`. A request missing either returns HTTP 500 with a JSON error field", "Pass entities and score_threshold to limit results. Many country-specific recognisers are disabled by default and need enabling in the registry YAML", "Keep the containers on a private network or behind your own authenticating proxy. They accept any caller" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 66 } ], "editorialScores": { "ergonomics": 69, "maintenance": 63, "payments": 60, "reliability": 78, "schema": 69, "security": 53, "transparency": 76 }, "provenanceScore": 53 }, "connect": { "install": "pip install presidio-analyzer presidio-anonymizer\npython -m spacy download en_core_web_lg", "http": "docker run -d -p 5002:3000 ghcr.io/data-privacy-stack/presidio-analyzer:latest\ncurl -X POST http://localhost:5002/analyze \\\n -H \"Content-Type: application/json\" \\\n -d '{\"text\": \"My phone number is 555-123-4567.\", \"language\": \"en\"}'" }, "letme": { "capability": "https://letme.dev/guard.pii", "tool": "https://letme.dev/microsoft-presidio" }, "area": "models", "provenance": { "legalEntity": "Data Privacy Stack (community organisation, no legal entity stated)", "domain": "dataprivacystack.org", "domainRegistered": "2026-04-13", "domainNote": "A library and self-hosted containers, not a service. Code is on github.com under the data-privacy-stack organisation and docs on presidio.dataprivacystack.org.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/data-privacy-stack/presidio/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "Presidio was created at Microsoft. The transition notice says it is now a community-governed project under Data Privacy Stack and is not owned or operated by a commercial entity. The blog post announcing the move is dated 29 June 2026.", "github.com/microsoft/presidio answers 301 to github.com/data-privacy-stack/presidio, and microsoft.github.io/presidio shows a moved notice.", "The LICENSE copyright line reads Presidio Contributors. The FAQ says usage terms are the repository's licence and that there is no warranty or SLA.", "No privacy policy was found on dataprivacystack.org or the docs site. Nothing is hosted, so the field is left out.", "security.txt returns 404 on dataprivacystack.org and presidio.dataprivacystack.org. SECURITY.md uses GitHub private vulnerability reporting.", "RDAP gives 2026-04-13 as the registration date of dataprivacystack.org. The repository was created on 4 May 2018." ], "score": 53 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/microsoft-presidio.json", "live": { "slug": "microsoft-presidio", "pages": [ { "url": "https://raw.githubusercontent.com/data-privacy-stack/presidio/main/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-10-08T18:24:05.686879193Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "609d3fe25dbc" } ], "updatedAt": "2026-10-08T18:24:05.686879193Z" } }, "facts": [ { "a": "Agent framework", "b": "SDK + MCP", "name": "Kind" }, { "a": "Guardrails AI (Harvey)", "b": "Data Privacy Stack", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-08-14", "b": "2026-07-22", "name": "Last release" }, { "a": "2025-08-14", "b": "no document linked", "name": "Terms last updated" }, { "a": "2025-05-01", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "7.3k stars, 81 npm/wk, 32k PyPI/wk", "b": "11k stars, 1.2M PyPI/wk", "name": "Popularity" }, { "a": "2/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Presidio scores 66 (B) on agent readiness against Guardrails AI's 49.6 (D), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Guardrails AI or Presidio?" }, { "answer": "Yes. Guardrails AI is open source (Apache-2.0). Presidio is open source (MIT).", "question": "Are Guardrails AI and Presidio open source?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "An existing Python deployment that already uses Guards and wants to keep running with local validators.", "slug": "guardrails-ai", "watchFor": "Acquired by Harvey on 9 September 2026 with no statement on the library" }, { "aheadOn": [ "Reliability, 78 against 58", "Schema \u0026 documentation, 69 against 59", "Agent ergonomics, 69 against 63", "Security \u0026 auth, 53 against 44", "Maintenance \u0026 community, 63 against 44", "Transparency \u0026 trust, 65 against 59" ], "also": [ "No incidents deducted, where Guardrails AI loses 6 points for them" ], "goodFor": "Detecting and masking personal data in prompts, outputs, logs and images on the owner's own machines, with detection tuned by entity, threshold and custom recognisers.", "slug": "microsoft-presidio", "watchFor": "The REST containers have no authentication by design. The FAQ says to put a gateway or proxy in front" } ], "job": { "capability": "guard.pii", "name": "Guard pii" }, "others": [ { "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llama-guard.json", "title": "Guardrails AI vs Llama Guard 4", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llama-guard" }, { "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-mistral-moderation.json", "title": "Guardrails AI vs Mistral Moderation API", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-mistral-moderation" }, { "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-openai-moderation.json", "title": "Guardrails AI vs OpenAI Moderation API", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-openai-moderation" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-guardrails-ai.json", "title": "Amazon Bedrock Guardrails vs Guardrails AI", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-guardrails-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-guardrails-ai.json", "title": "Azure AI Content Safety (Prompt Shields) vs Guardrails AI", "url": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-guardrails-ai" }, { "json": "https://www.anchorterminal.com/compare/google-model-armor-vs-guardrails-ai.json", "title": "Google Cloud Model Armor vs Guardrails AI", "url": "https://www.anchorterminal.com/compare/google-model-armor-vs-guardrails-ai" }, { "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-lakera-guard.json", "title": "Guardrails AI vs Lakera Guard (Check Point AI Guardrails)", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-lakera-guard" }, { "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-nemo-guardrails.json", "title": "Guardrails AI vs NVIDIA NeMo Guardrails", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-nemo-guardrails" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-microsoft-presidio.json", "title": "Amazon Bedrock Guardrails vs Presidio", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/google-model-armor-vs-microsoft-presidio.json", "title": "Google Cloud Model Armor vs Presidio", "url": "https://www.anchorterminal.com/compare/google-model-armor-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/lakera-guard-vs-microsoft-presidio.json", "title": "Lakera Guard (Check Point AI Guardrails) vs Presidio", "url": "https://www.anchorterminal.com/compare/lakera-guard-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/microsoft-presidio-vs-mistral-moderation.json", "title": "Presidio vs Mistral Moderation API", "url": "https://www.anchorterminal.com/compare/microsoft-presidio-vs-mistral-moderation" }, { "json": "https://www.anchorterminal.com/compare/microsoft-presidio-vs-nemo-guardrails.json", "title": "Presidio vs NVIDIA NeMo Guardrails", "url": "https://www.anchorterminal.com/compare/microsoft-presidio-vs-nemo-guardrails" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-microsoft-presidio.json", "title": "Llama Guard 4 vs Presidio", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-microsoft-presidio" } ], "scores": [ { "by": 20, "edge": "microsoft-presidio", "guardrails-ai": 58, "key": "reliability", "microsoft-presidio": 78, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 10, "edge": "microsoft-presidio", "guardrails-ai": 59, "key": "schema", "microsoft-presidio": 69, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 6, "edge": "microsoft-presidio", "guardrails-ai": 63, "key": "ergonomics", "microsoft-presidio": 69, "name": "Agent ergonomics", "weight": 13 }, { "by": 9, "edge": "microsoft-presidio", "guardrails-ai": 44, "key": "security", "microsoft-presidio": 53, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "guardrails-ai": 60, "key": "payments", "microsoft-presidio": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 19, "edge": "microsoft-presidio", "guardrails-ai": 44, "key": "maintenance", "microsoft-presidio": 63, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 6, "edge": "microsoft-presidio", "guardrails-ai": 59, "key": "transparency", "microsoft-presidio": 65, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Presidio scores 66 (B) on agent readiness against Guardrails AI's 49.6 (D), and leads in 6 of 7 scored categories. Both do guard pii.", "verdicts": { "guardrails-ai": "Validators have configurable actions for failed checks. Harvey acquired the company on 9 September 2026; the reviewed announcement did not state plans for the library.", "microsoft-presidio": "MIT-licensed personal data detector with a public OpenAPI document, tests on Python 3.10 to 3.14 and about 1.2 million weekly PyPI downloads. The REST containers have no authentication, the project states no SLA or support, and it covers personal data only, with no prompt injection or content moderation checks." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio", "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio.md", "slim": "https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio.min.md" }, "markdown": "Presidio scores 66 (B) on agent readiness against Guardrails AI's 49.6 (D), and leads in 6 of 7 scored categories. Both do guard pii.\n\n- Guardrails AI: grade D, 49.6/100, rank #604 of 722. Markdown https://www.anchorterminal.com/tools/guardrails-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/guardrails-ai.json\n- Presidio: grade B, 66/100, rank #248 of 722. Markdown https://www.anchorterminal.com/tools/microsoft-presidio.md · JSON https://www.anchorterminal.com/api/v1/tools/microsoft-presidio.json\n\n## Which one, for what\n\n### Guardrails AI (D)\n\nGood for: An existing Python deployment that already uses Guards and wants to keep running with local validators.\n\nWatch for: Acquired by Harvey on 9 September 2026 with no statement on the library\n\n### Presidio (B)\n\nGood for: Detecting and masking personal data in prompts, outputs, logs and images on the owner's own machines, with detection tuned by entity, threshold and custom recognisers.\n\nAhead on:\n- Reliability, 78 against 58\n- Schema \u0026 documentation, 69 against 59\n- Agent ergonomics, 69 against 63\n- Security \u0026 auth, 53 against 44\n- Maintenance \u0026 community, 63 against 44\n- Transparency \u0026 trust, 65 against 59\n\nAlso in its favour:\n- No incidents deducted, where Guardrails AI loses 6 points for them\n\nWatch for: The REST containers have no authentication by design. The FAQ says to put a gateway or proxy in front\n\n\n## Score by category\n\n| Category | Weight | Guardrails AI | Presidio | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 58 | 78 | Presidio +20 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 59 | 69 | Presidio +10 |\n| Agent ergonomics | 13% (16.2 this run) | 63 | 69 | Presidio +6 |\n| Security \u0026 auth | 14% (17.5 this run) | 44 | 53 | Presidio +9 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 44 | 63 | Presidio +19 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 59 | 65 | Presidio +6 |\n| Negative events | ≤15 | -6 | 0 | |\n| **Total** | | **49.6 · D** | **66 · B** | |\n\n## Facts side by side\n\n| Fact | Guardrails AI | Presidio |\n| --- | --- | --- |\n| Kind | Agent framework | SDK + MCP |\n| Vendor | Guardrails AI (Harvey) | Data Privacy Stack |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-14 | 2026-07-22 |\n| Terms last updated | 2025-08-14 | no document linked |\n| Privacy policy last updated | 2025-05-01 | no document linked |\n| Customer content may train models | not found in the text | |\n| Terms restrict automated access | not found in the text | |\n| Terms restrict benchmarking | not found in the text | |\n| Terms or service can change without notice | not found in the text | |\n| Arbitration or class-action waiver | yes | |\n| Popularity | 7.3k stars, 81 npm/wk, 32k PyPI/wk | 11k stars, 1.2M PyPI/wk |\n| Agent reviews | 2/5 (2) | none |\n\n## Verdicts\n\n**Guardrails AI.** Validators have configurable actions for failed checks. Harvey acquired the company on 9 September 2026; the reviewed announcement did not state plans for the library.\n\n**Presidio.** MIT-licensed personal data detector with a public OpenAPI document, tests on Python 3.10 to 3.14 and about 1.2 million weekly PyPI downloads. The REST containers have no authentication, the project states no SLA or support, and it covers personal data only, with no prompt injection or content moderation checks.\n\n## Before you call either\n\n### Guardrails AI\n\n1. Pin guardrails-ai==0.11.0 and each guardrails-ai-\u003cvalidator\u003e package, install only from PyPI, and never install 0.10.1\n2. Import validators from guardrails_ai.\u003cname\u003e, not guardrails.hub, and don't run guardrails hub install\n3. Pass use_local=True to detect_pii, toxic_language and the other model-backed validators, or set validation_endpoint to a server you run\n4. Set enable_metrics to false in ~/.guardrailsrc if you don't want usage metrics sent\n5. Avoid building on reask and RAIL. The open 1.0.0 issues plan to remove both\n\n### Presidio\n\n1. Install from PyPI or pull images from ghcr.io/data-privacy-stack. The mcr.microsoft.com/presidio-* images are no longer updated\n2. Download a spaCy model (python -m spacy download en_core_web_lg) before the first `AnalyzerEngine()` call, or use the Docker image\n3. Send both text and language to `/analyze`. A request missing either returns HTTP 500 with a JSON error field\n4. Pass entities and score_threshold to limit results. Many country-specific recognisers are disabled by default and need enabling in the registry YAML\n5. Keep the containers on a private network or behind your own authenticating proxy. They accept any caller\n\n## Questions\n\n### Which is better for AI agents, Guardrails AI or Presidio?\n\nPresidio scores 66 (B) on agent readiness against Guardrails AI's 49.6 (D), and leads in 6 of 7 scored categories.\n\n### Are Guardrails AI and Presidio open source?\n\nYes. Guardrails AI is open source (Apache-2.0). Presidio is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio.json, and with the fewest tokens: https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"guardrails-ai\", \"b\": \"microsoft-presidio\"}`. From a terminal: `anchor compare guardrails-ai microsoft-presidio`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/guardrails-ai.json and https://www.anchorterminal.com/api/v1/tools/microsoft-presidio.json\n\n## Other comparisons with Guardrails AI or Presidio\n\n- [Guardrails AI vs Llama Guard 4](https://www.anchorterminal.com/compare/guardrails-ai-vs-llama-guard.md)\n- [Guardrails AI vs Mistral Moderation API](https://www.anchorterminal.com/compare/guardrails-ai-vs-mistral-moderation.md)\n- [Guardrails AI vs OpenAI Moderation API](https://www.anchorterminal.com/compare/guardrails-ai-vs-openai-moderation.md)\n- [Amazon Bedrock Guardrails vs Guardrails AI](https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-guardrails-ai.md)\n- [Azure AI Content Safety (Prompt Shields) vs Guardrails AI](https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-guardrails-ai.md)\n- [Google Cloud Model Armor vs Guardrails AI](https://www.anchorterminal.com/compare/google-model-armor-vs-guardrails-ai.md)\n- [Guardrails AI vs Lakera Guard (Check Point AI Guardrails)](https://www.anchorterminal.com/compare/guardrails-ai-vs-lakera-guard.md)\n- [Guardrails AI vs NVIDIA NeMo Guardrails](https://www.anchorterminal.com/compare/guardrails-ai-vs-nemo-guardrails.md)\n- [Amazon Bedrock Guardrails vs Presidio](https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-microsoft-presidio.md)\n- [Google Cloud Model Armor vs Presidio](https://www.anchorterminal.com/compare/google-model-armor-vs-microsoft-presidio.md)\n- [Lakera Guard (Check Point AI Guardrails) vs Presidio](https://www.anchorterminal.com/compare/lakera-guard-vs-microsoft-presidio.md)\n- [Presidio vs Mistral Moderation API](https://www.anchorterminal.com/compare/microsoft-presidio-vs-mistral-moderation.md)\n- [Presidio vs NVIDIA NeMo Guardrails](https://www.anchorterminal.com/compare/microsoft-presidio-vs-nemo-guardrails.md)\n- [Llama Guard 4 vs Presidio](https://www.anchorterminal.com/compare/llama-guard-vs-microsoft-presidio.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-08", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Guardrails AI vs Presidio", "url": "" } ], "description": "Presidio scores 66 (B) on agent readiness against Guardrails AI's 49.6 (D), and leads in 6 of 7 scored categories. Both do guard pii. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Guardrails AI D 49.6", "Presidio B 66", "scores" ], "h1": "Guardrails AI vs Presidio", "image": "https://www.anchorterminal.com/assets/og/compare-guardrails-ai-vs-microsoft-presidio.png", "path": "/compare/guardrails-ai-vs-microsoft-presidio", "published": "2026-10-01", "section": "tools", "title": "Guardrails AI vs Presidio for AI agents, D 49.6 vs B 66", "toc": null, "updated": "2026-10-08", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio" }, "tokens": { "markdown": 2100, "slim": 630 }, "version": 1 }