--- title: "llm-guard vs AI-Infra-Guard" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/protectai-llm-guard-vs-tencent-ai-infra-guard" tools: ["protectai-llm-guard", "tencent-ai-infra-guard"] --- # llm-guard vs AI-Infra-Guard *GraphCanon updated Oct 6, 2026* ## Verdict Pick llm-guard if lLM Guard is a toolkit tailored for securing interactions with large language models, focusing on safeguarding against prompt injection and adversarial attacks; pick AI-Infra-Guard if aI-Infra-Guard is designed for organizations looking to secure their AI infrastructures comprehensively through various scanning and evaluation tools. [llm-guard](https://protectai.github.io/llm-guard/) reports 3.2k GitHub stars, 462 forks, and 38 open issues, last pushed Jul 8, 2026. [AI-Infra-Guard](https://tencent.github.io/AI-Infra-Guard/) has 6.5k stars, 599 forks, and 32 open issues, last pushed Sep 20, 2026. Figures are from public GitHub metadata via [llm-guard's repository](https://github.com/protectai/llm-guard) and [AI-Infra-Guard's repository](https://github.com/Tencent/AI-Infra-Guard). | | [llm-guard](/tools/protectai-llm-guard.md) | [AI-Infra-Guard](/tools/tencent-ai-infra-guard.md) | | --- | --- | --- | | Tagline | The Security Toolkit for LLM Interactions | A full-stack AI Red Teaming platform securing AI ecosystems | | Stars | 3,213 | 6,471 | | Forks | 462 | 599 | | Open issues | 38 | 32 | | Language | Python | Python | | Adopt for | LLM Guard is a toolkit tailored for securing interactions with large language models, focusing on safeguarding against prompt injection and adversarial attacks. | AI-Infra-Guard is designed for organizations looking to secure their AI infrastructures comprehensively through various scanning and evaluation tools. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Developer Tools, Evaluation & Observability | Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llm-guard](/tools/protectai-llm-guard.md) | [AI-Infra-Guard](/tools/tencent-ai-infra-guard.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Very active (96%) | | Days since push | 89d | 0d | | Archived on GitHub | Yes | No | | Open issues (now) | 38 | 32 | | Stars delta | +9 (30d) | +2.2k (30d) | | Open issues delta | 0 (30d) | +19 (30d) | | Full report | [trust report](/tools/protectai-llm-guard/trust.md) | [trust report](/tools/tencent-ai-infra-guard/trust.md) | ## Shared compatibility - **Python**: [llm-guard](/tools/protectai-llm-guard.md) - Python runtime; [AI-Infra-Guard](/tools/tencent-ai-infra-guard.md) - Python runtime ## Decision facts: llm-guard - **Requirements:** Min 2 GB RAM; Ensure you have Python version 3.9 or higher.; Some advanced features require additional libraries which are automatically installed as needed. - **Adopt for:** LLM Guard is a toolkit tailored for securing interactions with large language models, focusing on safeguarding against prompt injection and adversarial attacks. ## Decision facts: AI-Infra-Guard - **Adopt for:** AI-Infra-Guard is designed for organizations looking to secure their AI infrastructures comprehensively through various scanning and evaluation tools. ## Choose when ### Choose llm-guard if… - License: llm-guard is MIT, AI-Infra-Guard is Apache-2.0. - Requirements: Min 2 GB RAM; Ensure you have Python version 3.9 or higher.; Some advanced features require additional libraries which are automatically installed as needed.. - Tags unique to llm-guard: adversarial-machine-learning, chatgpt, large-language-models, llm-security. - Also covers Developer Tools. - - You need to secure your application from sophisticated prompt injection techniques. ### Choose AI-Infra-Guard if… - License: AI-Infra-Guard is Apache-2.0, llm-guard is MIT. - Tags unique to AI-Infra-Guard: agent-security, ai-red-teaming, llm-evaluation, skills-security. - Also covers LLM Frameworks. - AI-Infra-Guard ships Docker support for self-hosted deployment. - If you need advanced LLM jailbreak evaluation capabilities specific to the vulnerabilities identified by Tencent's research, consider using AI-Infra-Guard. ## When NOT to use llm-guard - - If you are working in a low-security environment or with small-scale projects where advanced security mechanisms are not necessary. - - In cases where integrating external libraries and ensuring Python version compatibility may introduce complexities that outweigh the benefits. ## When NOT to use AI-Infra-Guard - Avoid if you are looking exclusively for a tool that focuses solely on the runtime behavior of LLMs without broader infrastructural scanning capabilities. - Not recommended when your primary focus is on network-level security rather than comprehensive AI infrastructure security assessments and evaluations. ## Common questions ### What is the difference between llm-guard and AI-Infra-Guard? llm-guard: The Security Toolkit for LLM Interactions. AI-Infra-Guard: A full-stack AI Red Teaming platform securing AI ecosystems. See the comparison table for live GitHub stats and shared categories. ### When should I choose llm-guard over AI-Infra-Guard? Choose llm-guard over AI-Infra-Guard when License: llm-guard is MIT, AI-Infra-Guard is Apache-2.0; Requirements: Min 2 GB RAM; Ensure you have Python version 3.9 or higher.; Some advanced features require additional libraries which are automatically installed as needed.; Tags unique to llm-guard: adversarial-machine-learning, chatgpt, large-language-models, llm-security; Also covers Developer Tools; - You need to secure your application from sophisticated prompt injection techniques. ### When should I choose AI-Infra-Guard over llm-guard? Choose AI-Infra-Guard over llm-guard when License: AI-Infra-Guard is Apache-2.0, llm-guard is MIT; Tags unique to AI-Infra-Guard: agent-security, ai-red-teaming, llm-evaluation, skills-security; Also covers LLM Frameworks; AI-Infra-Guard ships Docker support for self-hosted deployment; If you need advanced LLM jailbreak evaluation capabilities specific to the vulnerabilities identified by Tencent's research, consider using AI-Infra-Guard. ### When should I avoid llm-guard? - If you are working in a low-security environment or with small-scale projects where advanced security mechanisms are not necessary. - In cases where integrating external libraries and ensuring Python version compatibility may introduce complexities that outweigh the benefits. ### When should I avoid AI-Infra-Guard? Avoid if you are looking exclusively for a tool that focuses solely on the runtime behavior of LLMs without broader infrastructural scanning capabilities. Not recommended when your primary focus is on network-level security rather than comprehensive AI infrastructure security assessments and evaluations. ### Is llm-guard or AI-Infra-Guard more popular on GitHub? AI-Infra-Guard has more GitHub stars (6,471 vs 3,213). Stars measure visibility, not whether either tool fits your constraints. ### Are llm-guard and AI-Infra-Guard open source? Yes - both are open-source projects on GitHub (llm-guard: MIT, AI-Infra-Guard: Apache-2.0). ### Where can I find alternatives to llm-guard or AI-Infra-Guard? GraphCanon lists graph-backed alternatives at [llm-guard alternatives](/tools/protectai-llm-guard/alternatives) and [AI-Infra-Guard alternatives](/tools/tencent-ai-infra-guard/alternatives) ([llm-guard markdown twin](/tools/protectai-llm-guard/alternatives.md), [AI-Infra-Guard markdown twin](/tools/tencent-ai-infra-guard/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/protectai-llm-guard-vs-tencent-ai-infra-guard.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llm-guard or AI-Infra-Guard? llm-guard: Archived. AI-Infra-Guard: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for llm-guard and AI-Infra-Guard? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-guard trust report](/tools/protectai-llm-guard/trust); [AI-Infra-Guard trust report](/tools/tencent-ai-infra-guard/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=protectai-llm-guard`](/api/graphcanon/graph?tool=protectai-llm-guard) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_