---
license: apache-2.0
datasets:
- QCRI/AZERG-Dataset
language:
- en
base_model:
- mistralai/Mistral-7B-Instruct-v0.3
tags:
- STIX standard
- threat intelligence
- MITRE ATT&CK
---

# QCRI/AZERG-T1-Mistral
This model is a fine-tuned version of `mistralai/Mistral-7B-Instruct-v0.3` specialized for `Task 1: STIX Entity Detection`. It has been trained on the [QCRI/AZERG-Dataset](https://huggingface.co/datasets/QCRI/AZERG-Dataset) to identify CTI-related entities (e.g., malware names, threat actors, vulnerabilities) in unstructured text.

This is a specialist model designed for high performance on entity detection within the [AZERG framework](https://github.com/QCRI/azerg/).

## Intended Use
Use this model to extract potential STIX entities from a given security text passage.

## Example Prompt:

```
Instruction:
You are a helpful threat intelligence analyst. Your task is to extract all STIX entities mentioned in the input. To help you, here is a list of the possible STIX entity types.
STIX entity types:
- ATTACK_PATTERN: A type of TTP that describes ways that adversaries attempt to compromise targets. (e.g., T1051, T1548.001, etc.)
[...]

Answer in the following format: <entities>LIST OF IDENTIFIED ENTITIES SEPARATED BY PIPE |</entities>

Input:
- Text Passage: [INPUT TEXT]

Response:
```

## Citation
If you use this model, please cite our paper:

```
@article{lekssays2025azerg,
  title={From Text to Actionable Intelligence: Automating STIX Entity and Relationship Extraction},
  author={Lekssays, Ahmed and Sencar, Husrev Taha and Yu, Ting},
  journal={arXiv preprint arXiv:2507.16576},
  year={2025}
}
```