Home/Compare/agentdojo vs weak-to-strong

Comparison

agentdojo vs weak-to-strong

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 weak-to-strong if weak-to-Strong is an inference-time attack exploiting smaller models to guide larger LLMs towards harmful output generation.

Markdown twin · agentdojo alternatives · weak-to-strong alternatives

GraphCanon updated 3w

agentdojo logo

agentdojo

ethz-spylab/agentdojo

716pushed Jun 2, 2026
vs
weak-to-strong logo

weak-to-strong

XuandongZhao/weak-to-strong

90pushed May 2, 2025

Trust & integrity

Signalagentdojoweak-to-strong
Maintenance
Steady (63d since push)
As of 3w · github_public_v1
Dormant (459d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Personal account
As of 3w · 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

agentdojo
A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
weak-to-strong
Novel Inference-Time Attack Leveraging Small Models to Guide Larger LLMs into Generating Harmful Outputs

Stars

agentdojo
716
weak-to-strong
90

Forks

agentdojo
188
weak-to-strong
10

Open issues

agentdojo
41
weak-to-strong
3

Language

agentdojo
Python
weak-to-strong
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.
weak-to-strong
Weak-to-Strong is an inference-time attack exploiting smaller models to guide larger LLMs towards harmful output generation.

Persona

agentdojo
-
weak-to-strong
-

Runtime

agentdojo
-
weak-to-strong
-

License

agentdojo
MIT
weak-to-strong
MIT

Last pushed

agentdojo
Jun 2, 2026
weak-to-strong
May 2, 2025

Categories

agentdojo
AI Agents, Evaluation & Observability
weak-to-strong
Inference & Serving

Trust and health

Maintenance

agentdojo
Steady (60%)
weak-to-strong
Dormant (18%)

Days since push

agentdojo
63d
weak-to-strong
459d

Open issues (now)

agentdojo
41
weak-to-strong
3

Owner type

agentdojo
Organization
weak-to-strong
User

Full report

agentdojo
Trust report
weak-to-strong
Trust report

Shared compatibility

  • Python · agentdojo: Python runtime · weak-to-strong: Python runtime

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, prompt-injection, security.
  • Also covers AI Agents, 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.

Choose weak-to-strong if…

  • Requirements: Min 8 GB RAM; The smaller models guiding the large LLM must be available.; A high-performance computing environment might be necessary if running on very large datasets or models..
  • Tags unique to weak-to-strong: inference-time attack, jailbreaking.
  • Also covers Inference & Serving.
  • Use it for research purposes specifically geared at understanding the vulnerabilities in large language models and improving their robustness against adversarial attacks.

When NOT to use weak-to-strong

  • Do not use it for applications requiring ethical guidelines adherence as it is designed to navigate around the safety mechanisms in large language models.
  • Avoid using this tool if you are developing systems that must ensure consistent alignment and prevent any form of harmful output generation, such as public communication platforms or education tools.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: agentdojo 716 · weak-to-strong 90 (synced Aug 5, 2026).

Common questions

What is the difference between agentdojo and weak-to-strong?
agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. weak-to-strong: Novel Inference-Time Attack Leveraging Small Models to Guide Larger LLMs into Generating Harmful Outputs. See the comparison table for live GitHub stats and shared categories.
When should I choose agentdojo over weak-to-strong?
Choose agentdojo over weak-to-strong 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, prompt-injection, security; Also covers AI Agents, 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 choose weak-to-strong over agentdojo?
Choose weak-to-strong over agentdojo when Requirements: Min 8 GB RAM; The smaller models guiding the large LLM must be available.; A high-performance computing environment might be necessary if running on very large datasets or models.; Tags unique to weak-to-strong: inference-time attack, jailbreaking; Also covers Inference & Serving; Use it for research purposes specifically geared at understanding the vulnerabilities in large language models and improving their robustness against adversarial attacks.
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 weak-to-strong?
Do not use it for applications requiring ethical guidelines adherence as it is designed to navigate around the safety mechanisms in large language models. Avoid using this tool if you are developing systems that must ensure consistent alignment and prevent any form of harmful output generation, such as public communication platforms or education tools.
Is agentdojo or weak-to-strong more popular on GitHub?
agentdojo has more GitHub stars (716 vs 90). Stars measure visibility, not whether either tool fits your constraints.
Are agentdojo and weak-to-strong open source?
Yes - both are open-source projects on GitHub (agentdojo: MIT, weak-to-strong: MIT).
Where can I find alternatives to agentdojo or weak-to-strong?
GraphCanon lists graph-backed alternatives at agentdojo alternatives and weak-to-strong alternatives (agentdojo markdown twin, weak-to-strong 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 weak-to-strong?
agentdojo: Steady. weak-to-strong: 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 weak-to-strong?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentdojo trust report; weak-to-strong trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.