Home/Compare/jailbreak-evaluation vs agentdojo

Comparison

jailbreak-evaluation vs agentdojo

Verdict

Pick jailbreak-evaluation if jailbreak-evaluation is a Python package aimed at evaluating if AI models have been jailbroken by generating outputs that diverge from expected programming; 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 · jailbreak-evaluation alternatives · agentdojo alternatives

GraphCanon updated 2w

jailbreak-evaluation logo

jailbreak-evaluation

controllability/jailbreak-evaluation

27pushed Nov 4, 2024
vs
agentdojo logo

agentdojo

ethz-spylab/agentdojo

716pushed Jun 2, 2026

Trust & integrity

Signaljailbreak-evaluationagentdojo
Maintenance
Dormant (638d since push)
As of 2w · github_public_v1
Steady (63d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
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

jailbreak-evaluation
Python package for language model jailbreak evaluation
agentdojo
A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents

Stars

jailbreak-evaluation
27
agentdojo
716

Forks

jailbreak-evaluation
8
agentdojo
188

Open issues

jailbreak-evaluation
0
agentdojo
41

Language

jailbreak-evaluation
Python
agentdojo
Python

Adopt for

jailbreak-evaluation
jailbreak-evaluation is a Python package aimed at evaluating if AI models have been jailbroken by generating outputs that diverge from expected programming.
agentdojo
AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.

Persona

jailbreak-evaluation
-
agentdojo
-

Runtime

jailbreak-evaluation
-
agentdojo
-

License

jailbreak-evaluation
Apache-2.0
agentdojo
MIT

Last pushed

jailbreak-evaluation
Nov 4, 2024
agentdojo
Jun 2, 2026

Categories

jailbreak-evaluation
Evaluation & Observability
agentdojo
AI Agents, Evaluation & Observability

Trust and health

Maintenance

jailbreak-evaluation
Dormant (18%)
agentdojo
Steady (60%)

Days since push

jailbreak-evaluation
638d
agentdojo
63d

Open issues (now)

jailbreak-evaluation
0
agentdojo
41

Full report

jailbreak-evaluation
Trust report
agentdojo
Trust report

Shared compatibility

  • Python · jailbreak-evaluation: Python runtime · agentdojo: Python runtime

Choose jailbreak-evaluation if…

  • License: jailbreak-evaluation is Apache-2.0, agentdojo is MIT.
  • Requirements: The tool depends on having PyTorch and FastChat installed; An API key from the OpenAI Platform is required for full functionality.
  • Tags unique to jailbreak-evaluation: ai safety, evaluation tools, jailbreaks, language-models.
  • When you need to assess whether an AI model can be manipulated to produce unpredictable or unintended outcomes through specific inputs, such as jailbreaking.

When NOT to use jailbreak-evaluation

  • If your project does not involve assessing the security or integrity of how an AI model responds to manipulative input techniques designed to exploit design weaknesses.
  • When you do not need dependencies on specific frameworks like PyTorch and FastChat, as jailbreak-evaluation requires these without automating their installation.

Choose agentdojo if…

  • License: agentdojo is MIT, jailbreak-evaluation is Apache-2.0.
  • 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 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 on cards: jailbreak-evaluation 27 · agentdojo 716 (synced Aug 5, 2026).

Common questions

What is the difference between jailbreak-evaluation and agentdojo?
jailbreak-evaluation: Python package for language model jailbreak evaluation. 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 jailbreak-evaluation over agentdojo?
Choose jailbreak-evaluation over agentdojo when License: jailbreak-evaluation is Apache-2.0, agentdojo is MIT; Requirements: The tool depends on having PyTorch and FastChat installed; An API key from the OpenAI Platform is required for full functionality; Tags unique to jailbreak-evaluation: ai safety, evaluation tools, jailbreaks, language-models; When you need to assess whether an AI model can be manipulated to produce unpredictable or unintended outcomes through specific inputs, such as jailbreaking.
When should I choose agentdojo over jailbreak-evaluation?
Choose agentdojo over jailbreak-evaluation when License: agentdojo is MIT, jailbreak-evaluation is Apache-2.0; 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 avoid jailbreak-evaluation?
If your project does not involve assessing the security or integrity of how an AI model responds to manipulative input techniques designed to exploit design weaknesses. When you do not need dependencies on specific frameworks like PyTorch and FastChat, as jailbreak-evaluation requires these without automating their installation.
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 jailbreak-evaluation or agentdojo more popular on GitHub?
agentdojo has more GitHub stars (716 vs 27). Stars measure visibility, not whether either tool fits your constraints.
Are jailbreak-evaluation and agentdojo open source?
Yes - both are open-source projects on GitHub (jailbreak-evaluation: Apache-2.0, agentdojo: MIT).
Where can I find alternatives to jailbreak-evaluation or agentdojo?
GraphCanon lists graph-backed alternatives at jailbreak-evaluation alternatives and agentdojo alternatives (jailbreak-evaluation 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, jailbreak-evaluation or agentdojo?
jailbreak-evaluation: Dormant. 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 jailbreak-evaluation and agentdojo?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: jailbreak-evaluation trust report; agentdojo trust report.

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