--- title: "AI-Infra-Guard vs circle-guard-bench" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/tencent-ai-infra-guard-vs-whitecircle-circle-guard-bench" tools: ["tencent-ai-infra-guard", "whitecircle-circle-guard-bench"] --- # AI-Infra-Guard vs circle-guard-bench *GraphCanon updated Sep 20, 2026* ## Verdict 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; pick circle-guard-bench if circle-guard-bench is a Python-based AI benchmark tool for evaluating large language model guard systems under various protection scenarios. [AI-Infra-Guard](https://tencent.github.io/AI-Infra-Guard/) reports 6.5k GitHub stars, 599 forks, and 32 open issues, last pushed Sep 20, 2026. [circle-guard-bench](https://whitecircle.ai) has 75 stars, 5 forks, and 1 open issues, last pushed Mar 7, 2026. Figures are from public GitHub metadata via [AI-Infra-Guard's repository](https://github.com/Tencent/AI-Infra-Guard) and [circle-guard-bench's repository](https://github.com/whitecircle/circle-guard-bench). | | [AI-Infra-Guard](/tools/tencent-ai-infra-guard.md) | [circle-guard-bench](/tools/whitecircle-circle-guard-bench.md) | | --- | --- | --- | | Tagline | A full-stack AI Red Teaming platform securing AI ecosystems | AI benchmark for evaluating LLM guard systems | | Stars | 6,471 | 75 | | Forks | 599 | 5 | | Open issues | 32 | 1 | | Language | Python | Python | | Adopt for | AI-Infra-Guard is designed for organizations looking to secure their AI infrastructures comprehensively through various scanning and evaluation tools. | circle-guard-bench is a Python-based AI benchmark tool for evaluating large language model guard systems under various protection scenarios. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability, LLM Frameworks | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AI-Infra-Guard](/tools/tencent-ai-infra-guard.md) | [circle-guard-bench](/tools/whitecircle-circle-guard-bench.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 185d | | Open issues (now) | 32 | 1 | | Stars delta | +2.2k (30d) | +3 (30d) | | Open issues delta | +19 (30d) | +1 (30d) | | Full report | [trust report](/tools/tencent-ai-infra-guard/trust.md) | [trust report](/tools/whitecircle-circle-guard-bench/trust.md) | ## Shared compatibility - **Python**: [AI-Infra-Guard](/tools/tencent-ai-infra-guard.md) - Python runtime; [circle-guard-bench](/tools/whitecircle-circle-guard-bench.md) - Python runtime ## 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. ## Decision facts: circle-guard-bench - **Adopt for:** circle-guard-bench is a Python-based AI benchmark tool for evaluating large language model guard systems under various protection scenarios. ## Choose when ### Choose AI-Infra-Guard if… - Tags unique to AI-Infra-Guard: agent-security, ai-red-teaming, security-tools, 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. ### Choose circle-guard-bench if… - Tags unique to circle-guard-bench: ai, benchmarking, guardrail, large-language-models. - Use circle-guard-bench when you need to evaluate the effectiveness of guardrails and safeguards in your LLM environment, as it offers an unparalleled set of scenarios specific to these protections. - Leaner open-issue backlog (1). ## 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. ## When NOT to use circle-guard-bench - Avoid circle-guard-bench if your primary focus is on benchmarking the performance aspects like speed and latency of LLMs, as it specializes in evaluating protections rather than performance. - Do not use this tool when you intend to conduct general purpose evaluations or comparisons between different LLM models that do not specifically involve security-related guard systems. ## Common questions ### What is the difference between AI-Infra-Guard and circle-guard-bench? AI-Infra-Guard: A full-stack AI Red Teaming platform securing AI ecosystems. circle-guard-bench: AI benchmark for evaluating LLM guard systems. See the comparison table for live GitHub stats and shared categories. ### When should I choose AI-Infra-Guard over circle-guard-bench? Choose AI-Infra-Guard over circle-guard-bench when Tags unique to AI-Infra-Guard: agent-security, ai-red-teaming, security-tools, 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 choose circle-guard-bench over AI-Infra-Guard? Choose circle-guard-bench over AI-Infra-Guard when Tags unique to circle-guard-bench: ai, benchmarking, guardrail, large-language-models; Use circle-guard-bench when you need to evaluate the effectiveness of guardrails and safeguards in your LLM environment, as it offers an unparalleled set of scenarios specific to these protections; Leaner open-issue backlog (1). ### 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. ### When should I avoid circle-guard-bench? Avoid circle-guard-bench if your primary focus is on benchmarking the performance aspects like speed and latency of LLMs, as it specializes in evaluating protections rather than performance. Do not use this tool when you intend to conduct general purpose evaluations or comparisons between different LLM models that do not specifically involve security-related guard systems. ### Is AI-Infra-Guard or circle-guard-bench more popular on GitHub? AI-Infra-Guard has more GitHub stars (6,471 vs 75). Stars measure visibility, not whether either tool fits your constraints. ### Are AI-Infra-Guard and circle-guard-bench open source? Yes - both are open-source projects on GitHub (AI-Infra-Guard: Apache-2.0, circle-guard-bench: Apache-2.0). ### Where can I find alternatives to AI-Infra-Guard or circle-guard-bench? GraphCanon lists graph-backed alternatives at [AI-Infra-Guard alternatives](/tools/tencent-ai-infra-guard/alternatives) and [circle-guard-bench alternatives](/tools/whitecircle-circle-guard-bench/alternatives) ([AI-Infra-Guard markdown twin](/tools/tencent-ai-infra-guard/alternatives.md), [circle-guard-bench markdown twin](/tools/whitecircle-circle-guard-bench/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/tencent-ai-infra-guard-vs-whitecircle-circle-guard-bench.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AI-Infra-Guard or circle-guard-bench? AI-Infra-Guard: Very active. circle-guard-bench: Slowing. 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 AI-Infra-Guard and circle-guard-bench? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AI-Infra-Guard trust report](/tools/tencent-ai-infra-guard/trust); [circle-guard-bench trust report](/tools/whitecircle-circle-guard-bench/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=tencent-ai-infra-guard`](/api/graphcanon/graph?tool=tencent-ai-infra-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/_