Comparison
agent-zero vs agentdojo
Verdict
Pick agent-zero if agent-zero is a Python-based autonomous agent framework that uses Docker for deployment and supports integration with LLM providers such as OpenAI Codex via OAuth; pick agentdojo if agentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
Markdown twin · agent-zero alternatives · agentdojo alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | agent-zero | agentdojo |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Steady (39d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | 99 low (99 low) As of today · osv@v1 | No lockfile As of today · none |
Tagline
- agent-zero
- Agent Zero AI framework
- agentdojo
- A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
Stars
- agent-zero
- 18k
- agentdojo
- 659
Forks
- agent-zero
- 3.7k
- agentdojo
- 168
Open issues
- agent-zero
- 235
- agentdojo
- 33
Language
- agent-zero
- Python
- agentdojo
- Python
Adopt for
- agent-zero
- Agent-zero is a Python-based autonomous agent framework that uses Docker for deployment and supports integration with LLM providers such as OpenAI Codex via OAuth.
- agentdojo
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
Persona
- agent-zero
- -
- agentdojo
- -
Runtime
- agent-zero
- -
- agentdojo
- -
License
- agent-zero
- Other
- agentdojo
- MIT
Last pushed
- agent-zero
- Jul 10, 2026
- agentdojo
- Jun 2, 2026
Categories
- agent-zero
- AI Agents, Inference & Serving
- agentdojo
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agent-zero
- Very active (96%)
- agentdojo
- Steady (60%)
Days since push
- agent-zero
- 0d
- agentdojo
- 39d
Open issues (now)
- agent-zero
- 235
- agentdojo
- 33
Security scan
- agent-zero
- 99 low (99 low)
- agentdojo
- No lockfile
Full report
- agent-zero
- Trust report
- agentdojo
- Trust report
Choose agent-zero if…
- License: agent-zero is Other, agentdojo is MIT.
- Pricing: The repository does not explicitly state any pricing information..
- Requirements: Requires Docker; Requires Docker setup and can be configured to leverage existing Docker environments..
- Tags unique to agent-zero: assistant, zero, linux, autonomous.
- Also covers Inference & Serving.
- * When setting up agents in SSH sessions, servers, recovery shells, or requiring scriptable installation processes.
When NOT to use agent-zero
- * When your deployment environment does not support or require Dockerization for agent operations.
- * In scenarios where OAuth-based integration with third-party language model providers is undesirable or impractical.
- * For installations that do not align well with the provided `/a0/usr` directory mapping conventions (e.g., specific data directories are required).
Choose agentdojo if…
- License: agentdojo is MIT, agent-zero 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: prompt-injection, benchmark, large-language-models, security.
- Also covers Evaluation & Observability.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (agent0ai/agent-zero) · observed Jul 11, 2026
- GitHub forks (agent0ai/agent-zero) · observed Jul 11, 2026
- Last push (agent0ai/agent-zero) · observed Jul 10, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ethz-spylab/agentdojo) · observed Jul 11, 2026
- GitHub forks (ethz-spylab/agentdojo) · observed Jul 11, 2026
- Last push (ethz-spylab/agentdojo) · observed Jun 2, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agent-zero 18k · agentdojo 659 (synced Jul 11, 2026).
Common questions
- What is the difference between agent-zero and agentdojo?
- agent-zero: Agent Zero AI framework. agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose agent-zero over agentdojo?
- Choose agent-zero over agentdojo when License: agent-zero is Other, agentdojo is MIT; Pricing: The repository does not explicitly state any pricing information.; Requirements: Requires Docker; Requires Docker setup and can be configured to leverage existing Docker environments.; Tags unique to agent-zero: assistant, zero, linux, autonomous; Also covers Inference & Serving; * When setting up agents in SSH sessions, servers, recovery shells, or requiring scriptable installation processes.
- When should I choose agentdojo over agent-zero?
- Choose agentdojo over agent-zero when License: agentdojo is MIT, agent-zero 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: prompt-injection, benchmark, large-language-models, security; Also covers Evaluation & Observability; AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
- When should I avoid agent-zero?
- * When your deployment environment does not support or require Dockerization for agent operations. * In scenarios where OAuth-based integration with third-party language model providers is undesirable or impractical. * For installations that do not align well with the provided
/a0/usrdirectory mapping conventions (e.g., specific data directories are required). - 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.
- Is agent-zero or agentdojo more popular on GitHub?
- agent-zero has more GitHub stars (18,393 vs 659). Stars measure visibility, not whether either tool fits your constraints.
- Are agent-zero and agentdojo open source?
- Yes - both are open-source projects on GitHub (agent-zero: Other, agentdojo: MIT).
- Where can I find alternatives to agent-zero or agentdojo?
- GraphCanon lists graph-backed alternatives at agent-zero alternatives and agentdojo alternatives (agent-zero markdown twin, agentdojo 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, agent-zero or agentdojo?
- agent-zero: Very active. agentdojo: Steady. 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 agent-zero and agentdojo?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-zero trust report; agentdojo trust report.