--- title: "agentdojo vs IB4LLMs" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ethz-spylab-agentdojo-vs-zichuan-liu-ib4llms" tools: ["ethz-spylab-agentdojo", "zichuan-liu-ib4llms"] --- # agentdojo vs IB4LLMs *GraphCanon updated Jul 12, 2026* ## Verdict Pick agentdojo when pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs.; pick IB4LLMs when tags unique to IB4LLMs: adversarial prompts defense, information bottleneck, jailbreak defense, llms protection. [agentdojo](https://agentdojo.spylab.ai/) reports 659 GitHub stars, 168 forks, and 33 open issues, last pushed Jun 2, 2026. [IB4LLMs](https://zichuan-liu.github.io/projects/IBProtector/index.html) has 25 stars, 2 forks, and 4 open issues, last pushed Nov 7, 2024. Figures are from public GitHub metadata via [agentdojo's repository](https://github.com/ethz-spylab/agentdojo) and [IB4LLMs's repository](https://github.com/zichuan-liu/IB4LLMs). | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [IB4LLMs](/tools/zichuan-liu-ib4llms.md) | | --- | --- | --- | | Tagline | A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents | Protecting Your LLMs with Information Bottleneck | | Stars | 659 | 25 | | Forks | 168 | 2 | | Open issues | 33 | 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. | - | | Persona | - | - | | Runtime | - | - | | License | MIT | - | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [IB4LLMs](/tools/zichuan-liu-ib4llms.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 39d | 611d | | Open issues (now) | 33 | 4 | | Owner type | Organization | User | | Security scan | No lockfile | 77 low (77 low) | | Full report | [trust report](/tools/ethz-spylab-agentdojo/trust.md) | [trust report](/tools/zichuan-liu-ib4llms/trust.md) | ## Shared compatibility - **Python**: [agentdojo](/tools/ethz-spylab-agentdojo.md) - Python runtime; [IB4LLMs](/tools/zichuan-liu-ib4llms.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. ## 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. - 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 IB4LLMs if… - Tags unique to IB4LLMs: adversarial prompts defense, information bottleneck, jailbreak defense, llms protection. - Also covers LLM Frameworks. - Leaner open-issue backlog (4). ## 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 IB4LLMs - Last GitHub push was 612 days ago (dormant maintenance, Nov 7, 2024). Validate activity before betting a new project on IB4LLMs. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between agentdojo and IB4LLMs? agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. IB4LLMs: Protecting Your LLMs with Information Bottleneck. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentdojo over IB4LLMs? Choose agentdojo over IB4LLMs 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; 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 IB4LLMs over agentdojo? Choose IB4LLMs over agentdojo when Tags unique to IB4LLMs: adversarial prompts defense, information bottleneck, jailbreak defense, llms protection; Also covers LLM Frameworks; Leaner open-issue backlog (4). ### 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 IB4LLMs? Last GitHub push was 612 days ago (dormant maintenance, Nov 7, 2024). Validate activity before betting a new project on IB4LLMs. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is agentdojo or IB4LLMs more popular on GitHub? agentdojo has more GitHub stars (659 vs 25). Stars measure visibility, not whether either tool fits your constraints. ### Are agentdojo and IB4LLMs open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to agentdojo or IB4LLMs? GraphCanon lists graph-backed alternatives at [agentdojo alternatives](/tools/ethz-spylab-agentdojo/alternatives) and [IB4LLMs alternatives](/tools/zichuan-liu-ib4llms/alternatives) ([agentdojo markdown twin](/tools/ethz-spylab-agentdojo/alternatives.md), [IB4LLMs markdown twin](/tools/zichuan-liu-ib4llms/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-zichuan-liu-ib4llms.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentdojo or IB4LLMs? agentdojo: Steady. IB4LLMs: 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 IB4LLMs? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentdojo trust report](/tools/ethz-spylab-agentdojo/trust); [IB4LLMs trust report](/tools/zichuan-liu-ib4llms/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/_