Comparison
AutoAudit vs llm-self-defense
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 llm-self-defense if mitigates harmful content generation via self-examination by LLM outputs without fine-tuning.
Markdown twin · AutoAudit alternatives · llm-self-defense alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | AutoAudit | llm-self-defense |
|---|---|---|
| Maintenance | Dormant (542d since push) As of 1d · github_public_v1 | Dormant (805d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1d · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- llm-self-defense
- LLM Self Defense: By Self Examination, LLMs know they are being tricked
Stars
- AutoAudit
- 354
- llm-self-defense
- 52
Forks
- AutoAudit
- 38
- llm-self-defense
- 7
Open issues
- AutoAudit
- 4
- llm-self-defense
- 7
Language
- AutoAudit
- HTML
- llm-self-defense
- 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.
- llm-self-defense
- Mitigates harmful content generation via self-examination by LLM outputs without fine-tuning.
Persona
- AutoAudit
- -
- llm-self-defense
- -
Runtime
- AutoAudit
- -
- llm-self-defense
- -
License
- AutoAudit
- MIT
- llm-self-defense
- BSD-3-Clause
Last pushed
- AutoAudit
- Feb 28, 2025
- llm-self-defense
- May 21, 2024
Categories
- AutoAudit
- Evaluation & Observability, Model Training
- llm-self-defense
- Evaluation & Observability
Trust and health
Days since push
- AutoAudit
- 542d
- llm-self-defense
- 805d
Open issues (now)
- AutoAudit
- 4
- llm-self-defense
- 7
Stars delta
- AutoAudit
- -1 (30d)
- llm-self-defense
- Unknown
Open issues delta
- AutoAudit
- 0 (30d)
- llm-self-defense
- Unknown
Owner type
- AutoAudit
- User
- llm-self-defense
- Organization
OSV dependency advisories
- AutoAudit
- No lockfile (source not queried)
- llm-self-defense
- Published findings
Full report
- AutoAudit
- Trust report
- llm-self-defense
- Trust report
Choose AutoAudit if…
- AutoAudit is primarily HTML; llm-self-defense is Python.
- License: AutoAudit is MIT, llm-self-defense is BSD-3-Clause.
- 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 llm-self-defense if…
- llm-self-defense is primarily Python; AutoAudit is HTML.
- License: llm-self-defense is BSD-3-Clause, AutoAudit is MIT.
- Tags unique to llm-self-defense: adversarial prompts, gpt 3.5, harmful content reduction, llama-2.
- When you need to reduce the success rate of adversarial attacks on text generation.
When NOT to use llm-self-defense
- If real-time performance is critical and additional latency cannot be tolerated.
- In scenarios where API access to both GPT 3.5 and Llama models is not feasible.
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 (poloclub/llm-self-defense) · observed Aug 5, 2026
- GitHub forks (poloclub/llm-self-defense) · observed Aug 5, 2026
- Last push (poloclub/llm-self-defense) · observed May 21, 2024
- License file (BSD-3-Clause) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: AutoAudit 354 · llm-self-defense 52 (synced Aug 24, 2026).
Common questions
- What is the difference between AutoAudit and llm-self-defense?
- AutoAudit: LLM for Cyber Security. llm-self-defense: LLM Self Defense: By Self Examination, LLMs know they are being tricked. See the comparison table for live GitHub stats and shared categories.
- When should I choose AutoAudit over llm-self-defense?
- Choose AutoAudit over llm-self-defense when AutoAudit is primarily HTML; llm-self-defense is Python; License: AutoAudit is MIT, llm-self-defense is BSD-3-Clause; 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 llm-self-defense over AutoAudit?
- Choose llm-self-defense over AutoAudit when llm-self-defense is primarily Python; AutoAudit is HTML; License: llm-self-defense is BSD-3-Clause, AutoAudit is MIT; Tags unique to llm-self-defense: adversarial prompts, gpt 3.5, harmful content reduction, llama-2; When you need to reduce the success rate of adversarial attacks on text generation.
- 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 llm-self-defense?
- If real-time performance is critical and additional latency cannot be tolerated. In scenarios where API access to both GPT 3.5 and Llama models is not feasible.
- Is AutoAudit or llm-self-defense more popular on GitHub?
- AutoAudit has more GitHub stars (354 vs 52). Stars measure visibility, not whether either tool fits your constraints.
- Are AutoAudit and llm-self-defense open source?
- Yes - both are open-source projects on GitHub (AutoAudit: MIT, llm-self-defense: BSD-3-Clause).
- Where can I find alternatives to AutoAudit or llm-self-defense?
- GraphCanon lists graph-backed alternatives at AutoAudit alternatives and llm-self-defense alternatives (AutoAudit markdown twin, llm-self-defense 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 llm-self-defense?
- AutoAudit: Dormant. llm-self-defense: 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 AutoAudit and llm-self-defense?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AutoAudit trust report; llm-self-defense trust report.