--- title: "agentdojo vs fast-llm-security-guardrails" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ethz-spylab-agentdojo-vs-zenguard-ai-fast-llm-security-guardrails" tools: ["ethz-spylab-agentdojo", "zenguard-ai-fast-llm-security-guardrails"] --- # agentdojo vs fast-llm-security-guardrails *GraphCanon updated Aug 10, 2026* ## Verdict Pick agentdojo if agentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents; pick fast-llm-security-guardrails if fast-llm-security-guardrails, also known as ZenGuard, is designed for the rapid deployment of security measures into AI agent systems to ensure they operate within defined trust constraints. [agentdojo](https://agentdojo.spylab.ai/) reports 716 GitHub stars, 188 forks, and 41 open issues, last pushed Jun 2, 2026. [fast-llm-security-guardrails](https://zenguard.ai/) has 154 stars, 21 forks, and 0 open issues, last pushed Feb 3, 2026. Figures are from public GitHub metadata via [agentdojo's repository](https://github.com/ethz-spylab/agentdojo) and [fast-llm-security-guardrails's repository](https://github.com/ZenGuard-AI/fast-llm-security-guardrails). | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [fast-llm-security-guardrails](/tools/zenguard-ai-fast-llm-security-guardrails.md) | | --- | --- | --- | | Tagline | A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents | The fastest Trust Layer for AI Agents | | Stars | 716 | 154 | | Forks | 188 | 21 | | Open issues | 41 | 0 | | Language | Python | Python | | Adopt for | AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. | fast-llm-security-guardrails, also known as ZenGuard, is designed for the rapid deployment of security measures into AI agent systems to ensure they operate within defined trust constraints. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [fast-llm-security-guardrails](/tools/zenguard-ai-fast-llm-security-guardrails.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 63d | 187d | | Open issues (now) | 41 | 0 | | Full report | [trust report](/tools/ethz-spylab-agentdojo/trust.md) | [trust report](/tools/zenguard-ai-fast-llm-security-guardrails/trust.md) | ## Shared compatibility - **Python**: [agentdojo](/tools/ethz-spylab-agentdojo.md) - Python runtime; [fast-llm-security-guardrails](/tools/zenguard-ai-fast-llm-security-guardrails.md) - Python runtime ## Decision facts: agentdojo - **Pricing:** freemium - Open-source under the MIT License. Some advanced features might require additional libraries or APIs. - **Requirements:** Min 8 GB RAM - **Adopt for:** AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ## Decision facts: fast-llm-security-guardrails - **Adopt for:** fast-llm-security-guardrails, also known as ZenGuard, is designed for the rapid deployment of security measures into AI agent systems to ensure they operate within defined trust constraints. ## Choose when ### Choose agentdojo if… - Pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs.. - Requirements: Min 8 GB RAM. - Tags unique to agentdojo: benchmark, large language models, prompt-injection, security. - AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ### Choose fast-llm-security-guardrails if… - Tags unique to fast-llm-security-guardrails: agentic-ai, ai-agent, ai-agents, ai-runtime. - Fast integration of privacy and security guardrails in environments where real-time evaluation and observability are critical. - Leaner open-issue backlog (0). ## When NOT to use agentdojo - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## When NOT to use fast-llm-security-guardrails - If your project requires a more customizable solution than what fast-llm-security-guardrails offers in its out-of-the-box configurations. - For teams that operate without established runtime environments like LangChain or LlamaIndex, as this may necessitate significant adaptation of ZenGuard. ## Common questions ### What is the difference between agentdojo and fast-llm-security-guardrails? agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. fast-llm-security-guardrails: The fastest Trust Layer for AI Agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentdojo over fast-llm-security-guardrails? Choose agentdojo over fast-llm-security-guardrails when Pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs.; Requirements: Min 8 GB RAM; Tags unique to agentdojo: benchmark, large language models, prompt-injection, security; AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ### When should I choose fast-llm-security-guardrails over agentdojo? Choose fast-llm-security-guardrails over agentdojo when Tags unique to fast-llm-security-guardrails: agentic-ai, ai-agent, ai-agents, ai-runtime; Fast integration of privacy and security guardrails in environments where real-time evaluation and observability are critical; Leaner open-issue backlog (0). ### When should I avoid agentdojo? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### When should I avoid fast-llm-security-guardrails? If your project requires a more customizable solution than what fast-llm-security-guardrails offers in its out-of-the-box configurations. For teams that operate without established runtime environments like LangChain or LlamaIndex, as this may necessitate significant adaptation of ZenGuard. ### Is agentdojo or fast-llm-security-guardrails more popular on GitHub? agentdojo has more GitHub stars (716 vs 154). Stars measure visibility, not whether either tool fits your constraints. ### Are agentdojo and fast-llm-security-guardrails open source? Yes - both are open-source projects on GitHub (agentdojo: MIT, fast-llm-security-guardrails: MIT). ### Where can I find alternatives to agentdojo or fast-llm-security-guardrails? GraphCanon lists graph-backed alternatives at [agentdojo alternatives](/tools/ethz-spylab-agentdojo/alternatives) and [fast-llm-security-guardrails alternatives](/tools/zenguard-ai-fast-llm-security-guardrails/alternatives) ([agentdojo markdown twin](/tools/ethz-spylab-agentdojo/alternatives.md), [fast-llm-security-guardrails markdown twin](/tools/zenguard-ai-fast-llm-security-guardrails/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/ethz-spylab-agentdojo-vs-zenguard-ai-fast-llm-security-guardrails.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentdojo or fast-llm-security-guardrails? agentdojo: Steady. fast-llm-security-guardrails: 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 agentdojo and fast-llm-security-guardrails? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentdojo trust report](/tools/ethz-spylab-agentdojo/trust); [fast-llm-security-guardrails trust report](/tools/zenguard-ai-fast-llm-security-guardrails/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ethz-spylab-agentdojo`](/api/graphcanon/graph?tool=ethz-spylab-agentdojo) - 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/_