{ "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": 701, "ranked": true, "rankOf": 842, "categoryRank": 14, "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": "LlamaFirewall scores 50.8 (D) on agent readiness against Guardrails AI's 49.6 (D), and leads in 1 of 7 scored categories. Guardrails AI leads on reliability, schema \u0026 documentation, payments \u0026 pricing and maintenance \u0026 community.", "b": { "slug": "llamafirewall", "name": "LlamaFirewall", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai/llama/llama-protections", "kind": "framework", "category": "guardrails", "summary": "LlamaFirewall is Meta's open-source Python library for screening an AI agent's inputs, tool results and outputs. It runs scanners for prompt injection, hidden characters, insecure generated code and goal drift, and returns allow, block or human review.", "url": "https://www.anchorterminal.com/tools/llamafirewall", "markdownUrl": "https://www.anchorterminal.com/tools/llamafirewall.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/llamafirewall.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/llamafirewall.json", "repo": "https://github.com/meta-llama/PurpleLlama/tree/main/LlamaFirewall", "license": "MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence", "transports": [], "packages": [ { "registry": "pypi", "name": "llamafirewall" } ], "auth": "none", "authNotes": "The library has no account or key of its own. The Prompt Guard scanner needs a Hugging Face token for an account Meta has approved for the gated `meta-llama/Llama-Prompt-Guard-2-86M` weights. AlignmentCheck and the PII scanner need `TOGETHER_API_KEY` for Together AI. The regex, hidden ASCII and CodeShield scanners need neither.", "pricing": "free", "pricingNotes": "Free under the MIT licence, with nothing to buy from Meta and no hosted version found. The cost is the owner's compute, plus Together AI's own charges when AlignmentCheck or the PII scanner is switched on. Those were not priced here.", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source. LlamaFirewall is a library the owner runs, with no payment route (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 4423, "npmWeekly": null, "pypiWeekly": 1029, "asOf": "2026-10-08" }, "docsUrl": "https://meta-llama.github.io/PurpleLlama/LlamaFirewall/", "capabilities": [ "guard.injection", "guard.pii", "guard.policy", "guard.self-host" ], "tags": [ "framework", "open-source", "self-hosted", "local", "python", "free", "gated", "no-telemetry", "stale-release" ], "lastRelease": "2025-05-29", "graded": true, "anchor": { "graded": true, "score": 50.8, "grade": "D", "agentReady": false, "rank": 682, "ranked": true, "rankOf": 842, "categoryRank": 13, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 60, "maintenance": 15, "payments": 50, "reliability": 53, "schema": 49, "security": 56, "transparency": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "One `scan()` call runs several checks on the owner's machine and returns a short typed result. The last PyPI release is 1.0.3 from 29 May 2025, and its Prompt Guard loader imports a `huggingface_hub` class that current versions no longer export, so a fresh install needs older pins. The classifier weights also need Meta's manual approval.", "bestFor": "A Python agent team that wants injection, hidden-character and generated-code checks in process, is willing to pin dependencies or install from main, and can get the gated weights.", "strengths": [ "Six scanner types sit behind one call, set per message role (user, assistant, tool, system, memory) in a plain mapping", "`ScanResult` is four typed fields (`decision`, `reason`, `score`, `status`), with decisions limited to allow, block or human review", "Prompt Guard, CodeShield, regex and hidden-character scanners run locally, and no telemetry code was found in the source", "MIT licence for the library, with tests run in public CI on Python 3.10 and 3.12 that passed on main on 29 September 2026", "`scan_replay` checks a whole conversation trace, and AlignmentCheck compares each agent step with the first user message" ], "weaknesses": [ "No PyPI release since 1.0.3 on 29 May 2025, and no changelog, tags or deprecation notes were found", "The 1.0.3 wheel imports `HfFolder` from `huggingface_hub`, which version 2.2.0 no longer exports. Main fixed the scanner on 26 March 2026, unreleased", "The Prompt Guard 2 weights are gated on Hugging Face with manual review, and the loader calls an interactive `login()` when no token is set", "Prompt Guard input is truncated at 512 tokens in the library, so later text in a long tool result is not scored", "AlignmentCheck and the PII scanner send the conversation to Together AI by default, and `create_scanner` passes no option to change the model or endpoint", "The custom scanner guide names a `BaseScanner` class that is not in the source, and LlamaFirewall issues from June and July 2025 have no reply" ], "agentNotes": [ "Pin `huggingface_hub` below 1.0 and a matching `transformers` 4.x before importing the Prompt Guard scanner from the 1.0.3 wheel, or install from main", "Get access to `meta-llama/Llama-Prompt-Guard-2-86M` and set a Hugging Face token first. Without one the loader prompts for a login and a headless run stalls", "Call `scan_async` inside a running event loop. `scan()` wraps `asyncio.run` and fails there. `scan_async` returns score 0.0 and reason `default` on every allow", "Split text longer than 512 tokens yourself before a Prompt Guard scan. The library truncates and does not chunk", "Do not feed a block `reason` back to the model. The Prompt Guard reason quotes the full scanned text, and the hidden ASCII reason decodes the hidden payload" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 50.8 } ], "editorialScores": { "ergonomics": 60, "maintenance": 15, "payments": 50, "reliability": 53, "schema": 49, "security": 56, "transparency": 56 }, "provenanceScore": 60 }, "connect": { "install": "pip install llamafirewall\nllamafirewall configure" }, "letme": { "capability": "https://letme.dev/guard.injection", "tool": "https://letme.dev/llamafirewall" }, "sameCompany": [ "llama-guard" ], "area": "models", "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "llama.com", "domainRegistered": "1994-11-01", "domainNote": "A Python library the owner runs, not a service. Code is on github.com under the meta-llama organisation, docs on meta-llama.github.io, and Meta's Llama Protections page lists it.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The MIT licence in the LlamaFirewall folder is the document that governs use of the library, so it is recorded as the terms. Its copyright line reads Meta Platforms, Inc. and affiliates.", "The Prompt Guard 2 weights the library downloads are under the Llama 4 Community Licence, a separate document, and the repository root carries a Llama 3.2 licence file.", "No privacy policy governs the library, because the owner runs it. The privacy field is left out. The Hugging Face access form for the weights says details entered are handled under the Meta Privacy Policy.", "AlignmentCheck and the PII scanner send data to Together AI under the owner's own Together account. Meta publishes no data statement for that path.", "www.llama.com/llama-protections redirected to dev.meta.ai/llama/llama-protections on 8 October 2026, which names LlamaFirewall and links its paper. RDAP gives 1 November 1994 as the registration date of llama.com.", "No status page, because nothing is hosted. No changelog, release notes or version tags were found in the repository.", "security.txt returns 404 on meta-llama.github.io and dev.meta.ai. SECURITY.md in the LlamaFirewall folder sends reports to bugbounty.meta.com." ], "score": 60 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/llamafirewall.json" }, "facts": [ { "a": "Agent framework", "b": "Agent framework", "name": "Kind" }, { "a": "Guardrails AI (Harvey)", "b": "Meta", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "", "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 (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-08-14", "b": "2025-05-29", "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": "4.4k stars, 1k PyPI/wk", "name": "Popularity" }, { "a": "2/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "LlamaFirewall scores 50.8 (D) on agent readiness against Guardrails AI's 49.6 (D), and leads in 1 of 7 scored categories. Guardrails AI leads on reliability, schema \u0026 documentation, payments \u0026 pricing and maintenance \u0026 community.", "question": "Which is better for AI agents, Guardrails AI or LlamaFirewall?" }, { "answer": "Yes. Guardrails AI is open source (Apache-2.0). LlamaFirewall is open source (MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence).", "question": "Are Guardrails AI and LlamaFirewall open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 58 against 53", "Schema \u0026 documentation, 59 against 49", "Payments \u0026 pricing, 60 against 50", "Maintenance \u0026 community, 44 against 15" ], "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": [ "Security \u0026 auth, 56 against 44" ], "also": [ "No incidents deducted, where Guardrails AI loses 6 points for them" ], "goodFor": "A Python agent team that wants injection, hidden-character and generated-code checks in process, is willing to pin dependencies or install from main, and can get the gated weights.", "slug": "llamafirewall", "watchFor": "No PyPI release since 1.0.3 on 29 May 2025, and no changelog, tags or deprecation notes were found" } ], "job": { "capability": "guard.injection", "name": "Guard injection" }, "others": [ { "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/amazon-bedrock-guardrails-vs-llamafirewall.json", "title": "Amazon Bedrock Guardrails vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llamafirewall" }, { "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/azure-ai-content-safety-vs-llamafirewall.json", "title": "Azure AI Content Safety (Prompt Shields) vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-guardrails-ai.json", "title": "Cisco AI Defense Inspection API vs Guardrails AI", "url": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-guardrails-ai" }, { "json": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llamafirewall.json", "title": "Cisco AI Defense Inspection API vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llamafirewall" }, { "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/google-model-armor-vs-llamafirewall.json", "title": "Google Cloud Model Armor vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/google-model-armor-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall.json", "title": "Granite Guardian vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall" }, { "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/guardrails-ai-vs-openai-guardrails.json", "title": "Guardrails AI vs OpenAI Guardrails", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-openai-guardrails" }, { "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-prisma-airs.json", "title": "Guardrails AI vs Prisma AIRS AI Runtime Security API", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-prisma-airs" }, { "json": "https://www.anchorterminal.com/compare/lakera-guard-vs-llamafirewall.json", "title": "Lakera Guard (Check Point AI Guardrails) vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/lakera-guard-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-nemo-guardrails.json", "title": "LlamaFirewall vs NVIDIA NeMo Guardrails", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-nemo-guardrails" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-openai-guardrails.json", "title": "LlamaFirewall vs OpenAI Guardrails", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-openai-guardrails" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-prisma-airs.json", "title": "LlamaFirewall vs Prisma AIRS AI Runtime Security API", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-prisma-airs" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-guardrails-ai.json", "title": "Granite Guardian vs Guardrails AI", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-guardrails-ai" }, { "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/guardrails-ai-vs-microsoft-presidio.json", "title": "Guardrails AI vs Presidio", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-microsoft-presidio.json", "title": "LlamaFirewall vs Presidio", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-mistral-moderation.json", "title": "LlamaFirewall vs Mistral Moderation API", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-mistral-moderation" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall.json", "title": "Llama Guard 4 vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall" } ], "scores": [ { "by": 5, "edge": "guardrails-ai", "guardrails-ai": 58, "key": "reliability", "llamafirewall": 53, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 10, "edge": "guardrails-ai", "guardrails-ai": 59, "key": "schema", "llamafirewall": 49, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 3, "edge": "guardrails-ai", "guardrails-ai": 63, "key": "ergonomics", "llamafirewall": 60, "name": "Agent ergonomics", "weight": 13 }, { "by": 12, "edge": "llamafirewall", "guardrails-ai": 44, "key": "security", "llamafirewall": 56, "name": "Security \u0026 auth", "weight": 14 }, { "by": 10, "edge": "guardrails-ai", "guardrails-ai": 60, "key": "payments", "llamafirewall": 50, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 29, "edge": "guardrails-ai", "guardrails-ai": 44, "key": "maintenance", "llamafirewall": 15, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 1, "edge": "guardrails-ai", "guardrails-ai": 59, "key": "transparency", "llamafirewall": 58, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "LlamaFirewall scores 50.8 (D) on agent readiness against Guardrails AI's 49.6 (D), and leads in 1 of 7 scored categories. Guardrails AI leads on reliability, schema \u0026 documentation, payments \u0026 pricing and maintenance \u0026 community. Both do guard injection.", "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.", "llamafirewall": "One `scan()` call runs several checks on the owner's machine and returns a short typed result. The last PyPI release is 1.0.3 from 29 May 2025, and its Prompt Guard loader imports a `huggingface_hub` class that current versions no longer export, so a fresh install needs older pins. The classifier weights also need Meta's manual approval." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall", "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall.md", "slim": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall.min.md" }, "markdown": "LlamaFirewall scores 50.8 (D) on agent readiness against Guardrails AI's 49.6 (D), and leads in 1 of 7 scored categories. Guardrails AI leads on reliability, schema \u0026 documentation, payments \u0026 pricing and maintenance \u0026 community. Both do guard injection.\n\n- Guardrails AI: grade D, 49.6/100, rank #701 of 842. Markdown https://www.anchorterminal.com/tools/guardrails-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/guardrails-ai.json\n- LlamaFirewall: grade D, 50.8/100, rank #682 of 842. Markdown https://www.anchorterminal.com/tools/llamafirewall.md · JSON https://www.anchorterminal.com/api/v1/tools/llamafirewall.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\nAhead on:\n- Reliability, 58 against 53\n- Schema \u0026 documentation, 59 against 49\n- Payments \u0026 pricing, 60 against 50\n- Maintenance \u0026 community, 44 against 15\n\nWatch for: Acquired by Harvey on 9 September 2026 with no statement on the library\n\n### LlamaFirewall (D)\n\nGood for: A Python agent team that wants injection, hidden-character and generated-code checks in process, is willing to pin dependencies or install from main, and can get the gated weights.\n\nAhead on:\n- Security \u0026 auth, 56 against 44\n\nAlso in its favour:\n- No incidents deducted, where Guardrails AI loses 6 points for them\n\nWatch for: No PyPI release since 1.0.3 on 29 May 2025, and no changelog, tags or deprecation notes were found\n\n\n## Score by category\n\n| Category | Weight | Guardrails AI | LlamaFirewall | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 58 | 53 | Guardrails AI +5 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 59 | 49 | Guardrails AI +10 |\n| Agent ergonomics | 13% (16.2 this run) | 63 | 60 | Guardrails AI +3 |\n| Security \u0026 auth | 14% (17.5 this run) | 44 | 56 | LlamaFirewall +12 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 50 | Guardrails AI +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 44 | 15 | Guardrails AI +29 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 59 | 58 | Guardrails AI +1 |\n| Negative events | ≤15 | -6 | 0 | |\n| **Total** | | **49.6 · D** | **50.8 · D** | |\n\n## Facts side by side\n\n| Fact | Guardrails AI | LlamaFirewall |\n| --- | --- | --- |\n| Kind | Agent framework | Agent framework |\n| Vendor | Guardrails AI (Harvey) | Meta |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-14 | 2025-05-29 |\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 | 4.4k stars, 1k 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**LlamaFirewall.** One `scan()` call runs several checks on the owner's machine and returns a short typed result. The last PyPI release is 1.0.3 from 29 May 2025, and its Prompt Guard loader imports a `huggingface_hub` class that current versions no longer export, so a fresh install needs older pins. The classifier weights also need Meta's manual approval.\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### LlamaFirewall\n\n1. Pin `huggingface_hub` below 1.0 and a matching `transformers` 4.x before importing the Prompt Guard scanner from the 1.0.3 wheel, or install from main\n2. Get access to `meta-llama/Llama-Prompt-Guard-2-86M` and set a Hugging Face token first. Without one the loader prompts for a login and a headless run stalls\n3. Call `scan_async` inside a running event loop. `scan()` wraps `asyncio.run` and fails there. `scan_async` returns score 0.0 and reason `default` on every allow\n4. Split text longer than 512 tokens yourself before a Prompt Guard scan. The library truncates and does not chunk\n5. Do not feed a block `reason` back to the model. The Prompt Guard reason quotes the full scanned text, and the hidden ASCII reason decodes the hidden payload\n\n## Questions\n\n### Which is better for AI agents, Guardrails AI or LlamaFirewall?\n\nLlamaFirewall scores 50.8 (D) on agent readiness against Guardrails AI's 49.6 (D), and leads in 1 of 7 scored categories. Guardrails AI leads on reliability, schema \u0026 documentation, payments \u0026 pricing and maintenance \u0026 community.\n\n### Are Guardrails AI and LlamaFirewall open source?\n\nYes. Guardrails AI is open source (Apache-2.0). LlamaFirewall is open source (MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall.json, and with the fewest tokens: https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"guardrails-ai\", \"b\": \"llamafirewall\"}`. From a terminal: `anchor compare guardrails-ai llamafirewall`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/guardrails-ai.json and https://www.anchorterminal.com/api/v1/tools/llamafirewall.json\n\n## Other comparisons with Guardrails AI or LlamaFirewall\n\n- [Amazon Bedrock Guardrails vs Guardrails AI](https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-guardrails-ai.md)\n- [Amazon Bedrock Guardrails vs LlamaFirewall](https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llamafirewall.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- [Azure AI Content Safety (Prompt Shields) vs LlamaFirewall](https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-llamafirewall.md)\n- [Cisco AI Defense Inspection API vs Guardrails AI](https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-guardrails-ai.md)\n- [Cisco AI Defense Inspection API vs LlamaFirewall](https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llamafirewall.md)\n- [Google Cloud Model Armor vs Guardrails AI](https://www.anchorterminal.com/compare/google-model-armor-vs-guardrails-ai.md)\n- [Google Cloud Model Armor vs LlamaFirewall](https://www.anchorterminal.com/compare/google-model-armor-vs-llamafirewall.md)\n- [Granite Guardian vs LlamaFirewall](https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall.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- [Guardrails AI vs OpenAI Guardrails](https://www.anchorterminal.com/compare/guardrails-ai-vs-openai-guardrails.md)\n- [Guardrails AI vs Prisma AIRS AI Runtime Security API](https://www.anchorterminal.com/compare/guardrails-ai-vs-prisma-airs.md)\n- [Lakera Guard (Check Point AI Guardrails) vs LlamaFirewall](https://www.anchorterminal.com/compare/lakera-guard-vs-llamafirewall.md)\n- [LlamaFirewall vs NVIDIA NeMo Guardrails](https://www.anchorterminal.com/compare/llamafirewall-vs-nemo-guardrails.md)\n- [LlamaFirewall vs OpenAI Guardrails](https://www.anchorterminal.com/compare/llamafirewall-vs-openai-guardrails.md)\n- [LlamaFirewall vs Prisma AIRS AI Runtime Security API](https://www.anchorterminal.com/compare/llamafirewall-vs-prisma-airs.md)\n- [Granite Guardian vs Guardrails AI](https://www.anchorterminal.com/compare/granite-guardian-vs-guardrails-ai.md)\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- [Guardrails AI vs Presidio](https://www.anchorterminal.com/compare/guardrails-ai-vs-microsoft-presidio.md)\n- [LlamaFirewall vs Presidio](https://www.anchorterminal.com/compare/llamafirewall-vs-microsoft-presidio.md)\n- [LlamaFirewall vs Mistral Moderation API](https://www.anchorterminal.com/compare/llamafirewall-vs-mistral-moderation.md)\n- [Llama Guard 4 vs LlamaFirewall](https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-09", "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 LlamaFirewall", "url": "" } ], "description": "LlamaFirewall scores 50.8 (D) on agent readiness against Guardrails AI's 49.6 (D), and leads in 1 of 7 scored categories. Guardrails AI leads on reliability, schema \u0026 documentation, payments \u0026 pricing and maintenance \u0026 community. Both do guard injection. Category scores, facts…", "facts": [ "Guardrails AI D 49.6", "LlamaFirewall D 50.8", "scores" ], "h1": "Guardrails AI vs LlamaFirewall", "image": "https://www.anchorterminal.com/assets/og/compare-guardrails-ai-vs-llamafirewall.png", "path": "/compare/guardrails-ai-vs-llamafirewall", "published": "2026-10-01", "section": "tools", "title": "Guardrails AI vs LlamaFirewall for AI agents, D 49.6 vs D 50.8", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall" }, "tokens": { "markdown": 2600, "slim": 680 }, "version": 1 }