--- title: "agentdojo vs BIPIA" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ethz-spylab-agentdojo-vs-microsoft-bipia" tools: ["ethz-spylab-agentdojo", "microsoft-bipia"] --- # agentdojo vs BIPIA *GraphCanon updated Aug 5, 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 BIPIA if bIPIA, developed by Microsoft, is a benchmarking tool designed to assess the robustness and security of Large Language Models (LLMs) against indirect prompt injection attacks. [agentdojo](https://agentdojo.spylab.ai/) reports 716 GitHub stars, 188 forks, and 41 open issues, last pushed Jun 2, 2026. [BIPIA](https://github.com/microsoft/BIPIA) has 149 stars, 19 forks, and 4 open issues, last pushed Apr 15, 2024. Figures are from public GitHub metadata via [agentdojo's repository](https://github.com/ethz-spylab/agentdojo) and [BIPIA's repository](https://github.com/microsoft/BIPIA). | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [BIPIA](/tools/microsoft-bipia.md) | | --- | --- | --- | | Tagline | A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents | Benchmark for evaluating LLM robustness to indirect prompt injection attacks. | | Stars | 716 | 149 | | Forks | 188 | 19 | | Open issues | 41 | 4 | | 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. | BIPIA, developed by Microsoft, is a benchmarking tool designed to assess the robustness and security of Large Language Models (LLMs) against indirect prompt injection attacks. | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [BIPIA](/tools/microsoft-bipia.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 63d | 842d | | Open issues (now) | 41 | 4 | | Full report | [trust report](/tools/ethz-spylab-agentdojo/trust.md) | [trust report](/tools/microsoft-bipia/trust.md) | ## Shared compatibility - **Python**: [agentdojo](/tools/ethz-spylab-agentdojo.md) - Python runtime; [BIPIA](/tools/microsoft-bipia.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: BIPIA - **Requirements:** For API-based model experiments (like GPT), no GPU is needed but an account's API key must be set up.; For open-source models of 13B or below, test on a machine with at least 2 V100 GPUs. For larger models over 13B, 4-8 V100 GPUs are required. - **Adopt for:** BIPIA, developed by Microsoft, is a benchmarking tool designed to assess the robustness and security of Large Language Models (LLMs) against indirect prompt injection attacks. ## Choose when ### Choose agentdojo if… - License: agentdojo is MIT, BIPIA is Other. - 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. - Also covers AI Agents. - AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ### Choose BIPIA if… - License: BIPIA is Other, agentdojo is MIT. - Requirements: For API-based model experiments (like GPT), no GPU is needed but an account's API key must be set up.; For open-source models of 13B or below, test on a machine with at least 2 V100 GPUs. For larger models over 13B, 4-8 V100 GPUs are required.. - Tags unique to BIPIA: indirect-prompt-injection-attacks, llm security, microsoft-research, python library. - Use BIPIA when you need to evaluate your LLM's resilience specifically to indirect prompt injection attacks, a niche but critical type of adversarial attack. ## 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 BIPIA - Avoid BIPIA if your primary focus is on general security enhancements without a particular emphasis on indirect prompt injection attacks. - Not recommended for users who primarily operate outside a Linux environment, specifically Ubuntu 20.04.6, as it can significantly affect compatibility and performance. ## Common questions ### What is the difference between agentdojo and BIPIA? agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. BIPIA: Benchmark for evaluating LLM robustness to indirect prompt injection attacks.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentdojo over BIPIA? Choose agentdojo over BIPIA when License: agentdojo is MIT, BIPIA is Other; 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; Also covers AI Agents; 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 BIPIA over agentdojo? Choose BIPIA over agentdojo when License: BIPIA is Other, agentdojo is MIT; Requirements: For API-based model experiments (like GPT), no GPU is needed but an account's API key must be set up.; For open-source models of 13B or below, test on a machine with at least 2 V100 GPUs. For larger models over 13B, 4-8 V100 GPUs are required.; Tags unique to BIPIA: indirect-prompt-injection-attacks, llm security, microsoft-research, python library; Use BIPIA when you need to evaluate your LLM's resilience specifically to indirect prompt injection attacks, a niche but critical type of adversarial attack. ### 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 BIPIA? Avoid BIPIA if your primary focus is on general security enhancements without a particular emphasis on indirect prompt injection attacks. Not recommended for users who primarily operate outside a Linux environment, specifically Ubuntu 20.04.6, as it can significantly affect compatibility and performance. ### Is agentdojo or BIPIA more popular on GitHub? agentdojo has more GitHub stars (716 vs 149). Stars measure visibility, not whether either tool fits your constraints. ### Are agentdojo and BIPIA open source? Yes - both are open-source projects on GitHub (agentdojo: MIT, BIPIA: Other). ### Where can I find alternatives to agentdojo or BIPIA? GraphCanon lists graph-backed alternatives at [agentdojo alternatives](/tools/ethz-spylab-agentdojo/alternatives) and [BIPIA alternatives](/tools/microsoft-bipia/alternatives) ([agentdojo markdown twin](/tools/ethz-spylab-agentdojo/alternatives.md), [BIPIA markdown twin](/tools/microsoft-bipia/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-microsoft-bipia.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentdojo or BIPIA? agentdojo: Steady. BIPIA: Dormant. 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 BIPIA? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentdojo trust report](/tools/ethz-spylab-agentdojo/trust); [BIPIA trust report](/tools/microsoft-bipia/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/_