Comparison
AutoAudit vs agentic_security
Verdict
Pick AutoAudit if autoAudit leverages LLMs specifically for cyber security tasks and supports custom fine-tuning through models such as GPT, LLAMA, LoRA, and QLORA; pick agentic_security if agentic Security is an agent-based framework for scanning vulnerabilities in large language models with a Python-based toolkit for robust security assessments via fuzz testing.
Markdown twin · AutoAudit alternatives · agentic_security alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | AutoAudit | agentic_security |
|---|---|---|
| Maintenance | Dormant (542d since push) As of 1d · github_public_v1 | Steady (35d since push) As of 4w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1d · github_public_v1 | Not a fork · Personal account As of 4w · 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
- AutoAudit
- LLM for Cyber Security
- agentic_security
- Agentic LLM Vulnerability Scanner / AI red teaming kit
Stars
- AutoAudit
- 354
- agentic_security
- 1.9k
Forks
- AutoAudit
- 38
- agentic_security
- 270
Open issues
- AutoAudit
- 4
- agentic_security
- 70
Language
- AutoAudit
- HTML
- agentic_security
- Python
Adopt for
- AutoAudit
- AutoAudit leverages LLMs specifically for cyber security tasks and supports custom fine-tuning through models such as GPT, LLAMA, LoRA, and QLORA.
- agentic_security
- Agentic Security is an agent-based framework for scanning vulnerabilities in large language models with a Python-based toolkit for robust security assessments via fuzz testing.
Persona
- AutoAudit
- -
- agentic_security
- -
Runtime
- AutoAudit
- -
- agentic_security
- -
License
- AutoAudit
- MIT
- agentic_security
- Apache-2.0 - Permissive license encouraging free use and modification under the condition of preserving notices.
Last pushed
- AutoAudit
- Feb 28, 2025
- agentic_security
- Jun 23, 2026
Categories
- AutoAudit
- Evaluation & Observability, Model Training
- agentic_security
- Evaluation & Observability, LLM Frameworks
Trust and health
Maintenance
- AutoAudit
- Dormant (18%)
- agentic_security
- Steady (60%)
Days since push
- AutoAudit
- 542d
- agentic_security
- 35d
Open issues (now)
- AutoAudit
- 4
- agentic_security
- 70
Stars delta
- AutoAudit
- -1 (30d)
- agentic_security
- Unknown
Open issues delta
- AutoAudit
- 0 (30d)
- agentic_security
- Unknown
Full report
- AutoAudit
- Trust report
- agentic_security
- Trust report
Choose AutoAudit if…
- AutoAudit is primarily HTML; agentic_security is Python.
- License: AutoAudit is MIT, agentic_security is Apache-2.0.
- Tags unique to AutoAudit: cyber-security, fine-tuning, gpt, llama.
- Also covers Model Training.
- When your project requires a language model focused on cyber security applications rather than general content generation.
When NOT to use AutoAudit
- For projects needing broad, general-purpose text generation that does not require cyber security expertise embedded in the model.
- In scenarios where proprietary data privacy is a concern, given AutoAudit's nature as an LLM for cyber security may imply certain data processing policies could be less flexible.
Choose agentic_security if…
- agentic_security is primarily Python; AutoAudit is HTML.
- License: agentic_security is Apache-2.0, AutoAudit is MIT.
- Tags unique to agentic_security: agent-framework, fuzzing, llm-evaluation, red-teaming.
- Also covers LLM Frameworks.
- agentic_security ships Docker support for self-hosted deployment.
- Developers need to ensure their LLMs are secure from jailbreak attempts and vulnerabilities.
When NOT to use agentic_security
- Teams require solutions that do not involve agent frameworks for vulnerability scanning.
- Projects seek a no-fuzz-testing approach for evaluating LLM security.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ddzipp/AutoAudit) · observed Aug 24, 2026
- GitHub forks (ddzipp/AutoAudit) · observed Aug 24, 2026
- Last push (ddzipp/AutoAudit) · observed Feb 28, 2025
- License file (MIT) · observed Aug 24, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (msoedov/agentic_security) · observed Jul 28, 2026
- GitHub forks (msoedov/agentic_security) · observed Jul 28, 2026
- Last push (msoedov/agentic_security) · observed Jun 23, 2026
- License file (Apache-2.0) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: AutoAudit 354 · agentic_security 1.9k (synced Aug 24, 2026).
Common questions
- What is the difference between AutoAudit and agentic_security?
- AutoAudit: LLM for Cyber Security. agentic_security: Agentic LLM Vulnerability Scanner / AI red teaming kit. See the comparison table for live GitHub stats and shared categories.
- When should I choose AutoAudit over agentic_security?
- Choose AutoAudit over agentic_security when AutoAudit is primarily HTML; agentic_security is Python; License: AutoAudit is MIT, agentic_security is Apache-2.0; Tags unique to AutoAudit: cyber-security, fine-tuning, gpt, llama; Also covers Model Training; When your project requires a language model focused on cyber security applications rather than general content generation.
- When should I choose agentic_security over AutoAudit?
- Choose agentic_security over AutoAudit when agentic_security is primarily Python; AutoAudit is HTML; License: agentic_security is Apache-2.0, AutoAudit is MIT; Tags unique to agentic_security: agent-framework, fuzzing, llm-evaluation, red-teaming; Also covers LLM Frameworks; agentic_security ships Docker support for self-hosted deployment; Developers need to ensure their LLMs are secure from jailbreak attempts and vulnerabilities.
- When should I avoid AutoAudit?
- For projects needing broad, general-purpose text generation that does not require cyber security expertise embedded in the model. In scenarios where proprietary data privacy is a concern, given AutoAudit's nature as an LLM for cyber security may imply certain data processing policies could be less flexible.
- When should I avoid agentic_security?
- Teams require solutions that do not involve agent frameworks for vulnerability scanning. Projects seek a no-fuzz-testing approach for evaluating LLM security.
- Is AutoAudit or agentic_security more popular on GitHub?
- agentic_security has more GitHub stars (1,943 vs 354). Stars measure visibility, not whether either tool fits your constraints.
- Are AutoAudit and agentic_security open source?
- Yes - both are open-source projects on GitHub (AutoAudit: MIT, agentic_security: Apache-2.0).
- Where can I find alternatives to AutoAudit or agentic_security?
- GraphCanon lists graph-backed alternatives at AutoAudit alternatives and agentic_security alternatives (AutoAudit markdown twin, agentic_security 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, AutoAudit or agentic_security?
- AutoAudit: Dormant. agentic_security: 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 AutoAudit and agentic_security?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AutoAudit trust report; agentic_security trust report.