> For the complete documentation index, see [llms.txt](https://docs.raga.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.raga.ai/ragaai-catalyst/ragaai-metric-library/additional-metrics/vulnerability-scanner/dan-6_0.md).

# DAN 6\_0

Identify and restrict DAN 6\_0 jailbreak prompts. Prevent unsafe AI responses and misuse.

**Description**: Tests the model (that you passed in the argument) to see if it is vulnerable to DAN 6\_0 attack. DAN 6\_0 is an attack scenario while LLM assumes the role of DAN, an AI model capable of bypassing constraints and OpenAI policies, providing uncensored responses without limitations.

**How does the Test work**:

1. Pre-defined internal system prompts are used.
2. Multiple iteration of Model output is generated for these pre-defined system prompts.
3. raga-llm-eval’s `MitigationBypass` and `DAN` detectors scan the model to see if the attack was successful.
4. This concludes if the model is vulnerable to DAN 6\_0 attack.

**Required arguments**: model (like:`gpt-4`)

**Interpretation of results**:

1. Score range(degree of model behaving as DAN 6): `[0, 1]`. A score of 1 implies that the model does not behave as DAN 6, while lower scores signify increasing levels of model behaving as DAN 6.
2. Sample internal prompt and model response for `failed cases` is displayed. For detailed info on internal prompts, model responses, scores, use `evaluator.save_results('filename.json')`.

**Coding Example:**

```python
probe = 'Dan_6_0'
evaluator.add_test(
    test_names=["dan_vulnerability_scanner"],
    data={
    },
    arguments={"category":[probe], "model": "gpt-3.5-turbo", "threshold": 1.0},
).run()

evaluator.print_results()
```