Comparison
agentdojo vs Aegis
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 Aegis if aegis provides runtime policy enforcement for AI agents with cryptographic audit trails and human-in-the-loop approvals, supporting zero-code deployment switches suited for various compliance needs.
Markdown twin · agentdojo alternatives · Aegis alternatives
GraphCanon updated Sep 20, 2026
9views this month
Trust & integrity
| Signal | agentdojo | Aegis |
|---|---|---|
| Maintenance | Slowing (94d since push) As of Sep 5, 2026 · github_public_v1 | Very active (4d since push) As of Sep 10, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 5, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 10, 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 15, 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
- Aegis
- Runtime policy enforcement for AI agents with cryptographic audit trail and human-in-the-loop approvals.
Stars
- agentdojo
- 802
- Aegis
- 340
Forks
- agentdojo
- 205
- Aegis
- 37
Open issues
- agentdojo
- 51
- Aegis
- 3
Language
- agentdojo
- Python
- Aegis
- TypeScript
Adopt for
- agentdojo
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
- Aegis
- Aegis provides runtime policy enforcement for AI agents with cryptographic audit trails and human-in-the-loop approvals, supporting zero-code deployment switches suited for various compliance needs.
Persona
- agentdojo
- -
- Aegis
- -
Runtime
- agentdojo
- -
- Aegis
- -
License
- agentdojo
- MIT
- Aegis
- MIT
Last pushed
- agentdojo
- Jun 2, 2026
- Aegis
- Sep 6, 2026
Categories
- agentdojo
- AI Agents, Evaluation & Observability
- Aegis
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agentdojo
- Slowing (36%)
- Aegis
- Very active (96%)
Days since push
- agentdojo
- 94d
- Aegis
- 4d
Open issues (now)
- agentdojo
- 51
- Aegis
- 3
Stars delta
- agentdojo
- +86 (30d)
- Aegis
- -27 (30d)
Open issues delta
- agentdojo
- +10 (30d)
- Aegis
- 0 (30d)
Owner type
- agentdojo
- Organization
- Aegis
- User
Full report
- agentdojo
- Trust report
- Aegis
- Trust report
Choose agentdojo if…
- agentdojo is primarily Python; Aegis is TypeScript.
- 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.
- 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 Aegis if…
- Aegis is primarily TypeScript; agentdojo is Python.
- Tags unique to Aegis: ai-safety, anthropic, audit-trail, llm-observability.
- Aegis ships Docker support for self-hosted deployment.
- You need cryptographic assurance of the audit trail to meet high-security standards.
When NOT to use Aegis
- The project does not require a zero-code deployment switch and can manage changes directly in the codebase.
- Minimal regulatory requirements mean that elaborate configurations like Aegis's strict retention policies are unnecessary.
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 Sep 20, 2026
- GitHub forks (ethz-spylab/agentdojo) · observed Sep 20, 2026
- Last push (ethz-spylab/agentdojo) · observed Jun 2, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Justin0504/Aegis) · observed Sep 20, 2026
- GitHub forks (Justin0504/Aegis) · observed Sep 20, 2026
- Last push (Justin0504/Aegis) · observed Sep 6, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: agentdojo 802 · Aegis 340 (synced Sep 20, 2026).
Common questions
- What is the difference between agentdojo and Aegis?
- agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. Aegis: Runtime policy enforcement for AI agents with cryptographic audit trail and human-in-the-loop approvals.. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentdojo over Aegis?
- Choose agentdojo over Aegis when agentdojo is primarily Python; Aegis is TypeScript; 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; 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 Aegis over agentdojo?
- Choose Aegis over agentdojo when Aegis is primarily TypeScript; agentdojo is Python; Tags unique to Aegis: ai-safety, anthropic, audit-trail, llm-observability; Aegis ships Docker support for self-hosted deployment; You need cryptographic assurance of the audit trail to meet high-security standards.
- 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 Aegis?
- The project does not require a zero-code deployment switch and can manage changes directly in the codebase. Minimal regulatory requirements mean that elaborate configurations like Aegis's strict retention policies are unnecessary.
- Is agentdojo or Aegis more popular on GitHub?
- agentdojo has more GitHub stars (802 vs 340). Stars measure visibility, not whether either tool fits your constraints.
- Are agentdojo and Aegis open source?
- Yes - both are open-source projects on GitHub (agentdojo: MIT, Aegis: MIT).
- Where can I find alternatives to agentdojo or Aegis?
- GraphCanon lists graph-backed alternatives at agentdojo alternatives and Aegis alternatives (agentdojo markdown twin, Aegis 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 Aegis?
- agentdojo: Slowing. Aegis: 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 Aegis?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentdojo trust report; Aegis trust report.