---
title: "AutoAudit vs llm-self-defense"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/ddzipp-autoaudit-vs-poloclub-llm-self-defense"
tools: ["ddzipp-autoaudit", "poloclub-llm-self-defense"]
---

# AutoAudit vs llm-self-defense

*GraphCanon updated Aug 24, 2026*

## 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.

[AutoAudit](https://github.com/ddzipp/AutoAudit) reports 354 GitHub stars, 38 forks, and 4 open issues, last pushed Feb 28, 2025. [llm-self-defense](https://github.com/poloclub/llm-self-defense) has 52 stars, 7 forks, and 7 open issues, last pushed May 21, 2024. Figures are from public GitHub metadata via [AutoAudit's repository](https://github.com/ddzipp/AutoAudit) and [llm-self-defense's repository](https://github.com/poloclub/llm-self-defense).

| | [AutoAudit](/tools/ddzipp-autoaudit.md) | [llm-self-defense](/tools/poloclub-llm-self-defense.md) |
| --- | --- | --- |
| Tagline | LLM for Cyber Security | LLM Self Defense: By Self Examination, LLMs know they are being tricked |
| Stars | 354 | 52 |
| Forks | 38 | 7 |
| Open issues | 4 | 7 |
| Language | HTML | Python |
| Adopt for | AutoAudit leverages LLMs specifically for cyber security tasks and supports custom fine-tuning through models such as GPT, LLAMA, LoRA, and QLORA. | Mitigates harmful content generation via self-examination by LLM outputs without fine-tuning. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | BSD-3-Clause |
| Categories | Evaluation & Observability, Model Training | Evaluation & Observability |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [AutoAudit](/tools/ddzipp-autoaudit.md) | [llm-self-defense](/tools/poloclub-llm-self-defense.md) |
| --- | --- | --- |
| Days since push | 542d | 805d |
| Open issues (now) | 4 | 7 |
| Stars delta | -1 (30d) | Unknown |
| Open issues delta | 0 (30d) | Unknown |
| Owner type | User | Organization |
| Full report | [trust report](/tools/ddzipp-autoaudit/trust.md) | [trust report](/tools/poloclub-llm-self-defense/trust.md) |

## Decision facts: AutoAudit

- **Adopt for:** AutoAudit leverages LLMs specifically for cyber security tasks and supports custom fine-tuning through models such as GPT, LLAMA, LoRA, and QLORA.

## Decision facts: llm-self-defense

- **Adopt for:** Mitigates harmful content generation via self-examination by LLM outputs without fine-tuning.

## Choose when

### 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.

### 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 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 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.

## 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](/tools/ddzipp-autoaudit/alternatives) and [llm-self-defense alternatives](/tools/poloclub-llm-self-defense/alternatives) ([AutoAudit markdown twin](/tools/ddzipp-autoaudit/alternatives.md), [llm-self-defense markdown twin](/tools/poloclub-llm-self-defense/alternatives.md)), 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](/compare/ddzipp-autoaudit-vs-poloclub-llm-self-defense.md) 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](/tools/ddzipp-autoaudit/trust); [llm-self-defense trust report](/tools/poloclub-llm-self-defense/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=ddzipp-autoaudit`](/api/graphcanon/graph?tool=ddzipp-autoaudit)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_