Comparison
agentdojo vs WeaveBench
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 WeaveBench if weaveBench is designed for evaluating computer-use agents that integrate both GUI and CLI interactions in real-world scenarios across various work domains.
Markdown twin · agentdojo alternatives · WeaveBench alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | agentdojo | WeaveBench |
|---|---|---|
| Maintenance | Steady (63d since push) As of 2w · github_public_v1 | Very active (6d since push) As of 4w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 4w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- agentdojo
- A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
- WeaveBench
- A Long-Horizon Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces
Stars
- agentdojo
- 716
- WeaveBench
- 157
Forks
- agentdojo
- 188
- WeaveBench
- 1
Open issues
- agentdojo
- 41
- WeaveBench
- 4
Language
- agentdojo
- Python
- WeaveBench
- Python
Adopt for
- agentdojo
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
- WeaveBench
- WeaveBench is designed for evaluating computer-use agents that integrate both GUI and CLI interactions in real-world scenarios across various work domains.
Persona
- agentdojo
- -
- WeaveBench
- -
Runtime
- agentdojo
- -
- WeaveBench
- -
License
- agentdojo
- MIT
- WeaveBench
- MIT
Last pushed
- agentdojo
- Jun 2, 2026
- WeaveBench
- Jul 22, 2026
Categories
- agentdojo
- AI Agents, Evaluation & Observability
- WeaveBench
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agentdojo
- Steady (60%)
- WeaveBench
- Very active (96%)
Days since push
- agentdojo
- 63d
- WeaveBench
- 6d
Open issues (now)
- agentdojo
- 41
- WeaveBench
- 4
OSV dependency advisories
- agentdojo
- No lockfile (source not queried)
- WeaveBench
- Published findings
Full report
- agentdojo
- Trust report
- WeaveBench
- Trust report
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: 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 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.
Choose WeaveBench if…
- Tags unique to WeaveBench: agent-as-judge, computer-use-agent, gui-agent, hybrid-interface.
- Use WeaveBench if you need to assess agents capable of handling tasks that require intermingling graphical user interface operations with command-line or code-based actions.
- More recently updated (last pushed Jul 22, 2026).
When NOT to use WeaveBench
- Avoid WeaveBench if your testing needs do not involve scenarios that require the integration of both GUI and CLI operations.
- Do not use it when you are specifically interested only in benchmarking agents designed for single-channel tasks, either strictly CLI-based or purely graphical interface-driven.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ethz-spylab/agentdojo) · observed Aug 5, 2026
- GitHub forks (ethz-spylab/agentdojo) · observed Aug 5, 2026
- Last push (ethz-spylab/agentdojo) · observed Jun 2, 2026
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (weavebench/WeaveBench) · observed Jul 29, 2026
- GitHub forks (weavebench/WeaveBench) · observed Jul 29, 2026
- Last push (weavebench/WeaveBench) · observed Jul 22, 2026
- License file (MIT) · observed Jul 29, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentdojo 716 · WeaveBench 157 (synced Aug 5, 2026).
Common questions
- What is the difference between agentdojo and WeaveBench?
- agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. WeaveBench: A Long-Horizon Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentdojo over WeaveBench?
- Choose agentdojo over WeaveBench 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: 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 WeaveBench over agentdojo?
- Choose WeaveBench over agentdojo when Tags unique to WeaveBench: agent-as-judge, computer-use-agent, gui-agent, hybrid-interface; Use WeaveBench if you need to assess agents capable of handling tasks that require intermingling graphical user interface operations with command-line or code-based actions; More recently updated (last pushed Jul 22, 2026).
- 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 WeaveBench?
- Avoid WeaveBench if your testing needs do not involve scenarios that require the integration of both GUI and CLI operations. Do not use it when you are specifically interested only in benchmarking agents designed for single-channel tasks, either strictly CLI-based or purely graphical interface-driven.
- Is agentdojo or WeaveBench more popular on GitHub?
- agentdojo has more GitHub stars (716 vs 157). Stars measure visibility, not whether either tool fits your constraints.
- Are agentdojo and WeaveBench open source?
- Yes - both are open-source projects on GitHub (agentdojo: MIT, WeaveBench: MIT).
- Where can I find alternatives to agentdojo or WeaveBench?
- GraphCanon lists graph-backed alternatives at agentdojo alternatives and WeaveBench alternatives (agentdojo markdown twin, WeaveBench markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, agentdojo or WeaveBench?
- agentdojo: Steady. WeaveBench: 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 agentdojo and WeaveBench?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentdojo trust report; WeaveBench trust report.