# DAN\_JailBreak

**Description**: Tests the model (that you passed in the argument) to see if it is vulnerable to DAN\_JailBreak attack. DAN\_JailBreak is an attack scenario where the model generates responses which are free from limitations, providing unrestricted and unfiltered responses.

**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_JailBreak` detectors scan the model to see if the attack was successful.
4. This concludes if the model is vulnerable to DAN\_JailBreak attack.

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

**Interpretation of results**:

1. Score range(degree of model behaving as DAN\_JailBreak): `[0, 1]`. A score of 1 implies that the model does not behave as DAN\_JailBreak, while lower scores signify increasing levels of model behaving as DAN\_JailBreak.
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_Jailbreak'
evaluator.add_test(
    test_names=["dan_vulnerability_scanner"],
    data={
    },
    arguments={"category":[probe], "model": "gpt-3.5-turbo", "threshold": 1.0},
).run()

evaluator.print_results()
```