Comparison
ALERT vs agentdojo
Verdict
Pick ALERT if aLERT is designed specifically for red-teaming based safety evaluation on large language models, using MIT licensed prompts and adversarial augmentation; 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 · ALERT alternatives · agentdojo alternatives
GraphCanon updated Sep 20, 2026
7views this month
Trust & integrity
| Signal | ALERT | agentdojo |
|---|---|---|
| Maintenance | Dormant (719d since push) As of Sep 10, 2026 · github_public_v1 | Slowing (94d since push) As of Sep 5, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 10, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 5, 2026 · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-07-15 As of Jul 15, 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
- ALERT
- A Comprehensive Benchmark for Assessing Large Language Models' Safety Through Red Teaming
- agentdojo
- A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
Stars
- ALERT
- 59
- agentdojo
- 802
Forks
- ALERT
- 8
- agentdojo
- 205
Open issues
- ALERT
- 0
- agentdojo
- 51
Language
- ALERT
- Python
- agentdojo
- Python
Adopt for
- ALERT
- ALERT is designed specifically for red-teaming based safety evaluation on large language models, using MIT licensed prompts and adversarial augmentation.
- agentdojo
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
Persona
- ALERT
- -
- agentdojo
- -
Runtime
- ALERT
- -
- agentdojo
- -
License
- ALERT
- Other
- agentdojo
- MIT
Last pushed
- ALERT
- Sep 20, 2024
- agentdojo
- Jun 2, 2026
Categories
- ALERT
- Evaluation & Observability
- agentdojo
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- ALERT
- Dormant (18%)
- agentdojo
- Slowing (36%)
Days since push
- ALERT
- 719d
- agentdojo
- 94d
Open issues (now)
- ALERT
- 0
- agentdojo
- 51
Stars delta
- ALERT
- 0 (30d)
- agentdojo
- +86 (30d)
Open issues delta
- ALERT
- 0 (30d)
- agentdojo
- +10 (30d)
OSV dependency advisories
- ALERT
- No published findings from this source as of 2026-07-15
- agentdojo
- No lockfile (source not queried)
Full report
- ALERT
- Trust report
- agentdojo
- Trust report
Choose ALERT if…
- License: ALERT is Other, agentdojo is MIT.
- Tags unique to ALERT: ai, artificial-intelligence, bias-detection, llm-evaluation.
- When evaluating safety metrics of large language models through red-teaming approaches
When NOT to use ALERT
- If your evaluation does not require bias detection or safety assessment under adversarial conditions
- In scenarios where a broader range of model aspects beyond safety is needed, as ALERT focuses primarily on safety benchmarks
Choose agentdojo if…
- License: agentdojo is MIT, ALERT 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: 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
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Babelscape/ALERT) · observed Sep 20, 2026
- GitHub forks (Babelscape/ALERT) · observed Sep 20, 2026
- Last push (Babelscape/ALERT) · observed Sep 20, 2024
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- 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 on cards: ALERT 59 · agentdojo 802 (synced Sep 20, 2026).
Common questions
- What is the difference between ALERT and agentdojo?
- ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety Through Red Teaming. 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 ALERT over agentdojo?
- Choose ALERT over agentdojo when License: ALERT is Other, agentdojo is MIT; Tags unique to ALERT: ai, artificial-intelligence, bias-detection, llm-evaluation; When evaluating safety metrics of large language models through red-teaming approaches.
- When should I choose agentdojo over ALERT?
- Choose agentdojo over ALERT when License: agentdojo is MIT, ALERT 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: 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 ALERT?
- If your evaluation does not require bias detection or safety assessment under adversarial conditions In scenarios where a broader range of model aspects beyond safety is needed, as ALERT focuses primarily on safety benchmarks
- 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.
- Is ALERT or agentdojo more popular on GitHub?
- agentdojo has more GitHub stars (802 vs 59). Stars measure visibility, not whether either tool fits your constraints.
- Are ALERT and agentdojo open source?
- Yes - both are open-source projects on GitHub (ALERT: Other, agentdojo: MIT).
- Where can I find alternatives to ALERT or agentdojo?
- GraphCanon lists graph-backed alternatives at ALERT alternatives and agentdojo alternatives (ALERT 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, ALERT or agentdojo?
- ALERT: Dormant. agentdojo: Slowing. 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 ALERT and agentdojo?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ALERT trust report; agentdojo trust report.