Home/Compare/agentdojo vs Open-Prompt-Injection

Comparison

agentdojo vs Open-Prompt-Injection

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 Open-Prompt-Injection if open-Prompt-Injection is a Python-based toolkit for benchmarking prompt injection attacks on LLMs, offering customization through config files and support for various LLM APIs.

Markdown twin · agentdojo alternatives · Open-Prompt-Injection alternatives

GraphCanon updated Oct 6, 2026

7views this month

agentdojo logo

agentdojo

ethz-spylab/agentdojo

★ 893pushed Jun 2, 2026
vs
Open-Prompt-Injection logo

Open-Prompt-Injection

liu00222/Open-Prompt-Injection

★ 503pushed Sep 27, 2026

Trust & integrity

SignalagentdojoOpen-Prompt-Injection
Maintenance
Slowing (125d since push)
As of Oct 6, 2026 · github_public_v1
Very active (6d since push)
As of Oct 4, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Oct 6, 2026 · github_public_v1
Not a fork · Personal account
As of Oct 4, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 2026 · 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
Open-Prompt-Injection
Benchmark and toolkit for prompt injection attacks and defenses in LLMs

Stars

agentdojo
893
Open-Prompt-Injection
503

Forks

agentdojo
235
Open-Prompt-Injection
81

Open issues

agentdojo
72
Open-Prompt-Injection
2

Language

agentdojo
Python
Open-Prompt-Injection
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.
Open-Prompt-Injection
Open-Prompt-Injection is a Python-based toolkit for benchmarking prompt injection attacks on LLMs, offering customization through config files and support for various LLM APIs.

Persona

agentdojo
-
Open-Prompt-Injection
-

Runtime

agentdojo
-
Open-Prompt-Injection
-

License

agentdojo
MIT
Open-Prompt-Injection
MIT

Last pushed

agentdojo
Jun 2, 2026
Open-Prompt-Injection
Sep 27, 2026

Categories

agentdojo
AI Agents, Evaluation & Observability
Open-Prompt-Injection
Evaluation & Observability, LLM Frameworks

Trust and health

Maintenance

agentdojo
Slowing (36%)
Open-Prompt-Injection
Very active (96%)

Days since push

agentdojo
125d
Open-Prompt-Injection
6d

Open issues (now)

agentdojo
72
Open-Prompt-Injection
2

Stars delta

agentdojo
+91 (30d)
Open-Prompt-Injection
+33 (30d)

Open issues delta

agentdojo
+21 (30d)
Open-Prompt-Injection
-12 (30d)

Owner type

agentdojo
Organization
Open-Prompt-Injection
User

Full report

agentdojo
Trust report
Open-Prompt-Injection
Trust report

Shared compatibility

  • Python · agentdojo: Python runtime · Open-Prompt-Injection: 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, large-language-models, 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

  • Last GitHub push was Jun 2, 2026 (slowing maintenance). Validate activity before betting a new project on 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 Open-Prompt-Injection if…

  • Tags unique to Open-Prompt-Injection: llm, llm-security, security-and-privacy.
  • Also covers LLM Frameworks.
  • You prioritize security testing specifically for prompt injection vulnerabilities in your LLM applications.

When NOT to use Open-Prompt-Injection

  • You require broader, more generalized security features not centered on prompt injection attacks.
  • Your project does not involve working with Google PaLM2 or other specific models like Meta's Llama and OpenAI's GPT.

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 893 · Open-Prompt-Injection 503 (synced Oct 6, 2026).

Common questions

What is the difference between agentdojo and Open-Prompt-Injection?
agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. Open-Prompt-Injection: Benchmark and toolkit for prompt injection attacks and defenses in LLMs. See the comparison table for live GitHub stats and shared categories.
When should I choose agentdojo over Open-Prompt-Injection?
Choose agentdojo over Open-Prompt-Injection 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, 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 Open-Prompt-Injection over agentdojo?
Choose Open-Prompt-Injection over agentdojo when Tags unique to Open-Prompt-Injection: llm, llm-security, security-and-privacy; Also covers LLM Frameworks; You prioritize security testing specifically for prompt injection vulnerabilities in your LLM applications.
When should I avoid agentdojo?
Last GitHub push was Jun 2, 2026 (slowing maintenance). Validate activity before betting a new project on 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 Open-Prompt-Injection?
You require broader, more generalized security features not centered on prompt injection attacks. Your project does not involve working with Google PaLM2 or other specific models like Meta's Llama and OpenAI's GPT.
Is agentdojo or Open-Prompt-Injection more popular on GitHub?
agentdojo has more GitHub stars (893 vs 503). Stars measure visibility, not whether either tool fits your constraints.
Are agentdojo and Open-Prompt-Injection open source?
Yes - both are open-source projects on GitHub (agentdojo: MIT, Open-Prompt-Injection: MIT).
Where can I find alternatives to agentdojo or Open-Prompt-Injection?
GraphCanon lists graph-backed alternatives at agentdojo alternatives and Open-Prompt-Injection alternatives (agentdojo markdown twin, Open-Prompt-Injection 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 Open-Prompt-Injection?
agentdojo: Slowing. Open-Prompt-Injection: 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 Open-Prompt-Injection?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentdojo trust report; Open-Prompt-Injection trust report.

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