55 lines
1.7 KiB
Markdown
55 lines
1.7 KiB
Markdown
---
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license: apache-2.0
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datasets:
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- QCRI/AZERG-Dataset
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language:
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- en
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base_model:
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- mistralai/Mistral-7B-Instruct-v0.3
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tags:
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- STIX standard
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- threat intelligence
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- MITRE ATT&CK
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---
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# QCRI/AZERG-MixTask-Mistral
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This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 specialized for Cyber Threat Intelligence (CTI) tasks. It was trained on the AZERG Dataset covering a mixture of all four tasks required for STIX data generation:
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- T1: Entity Detection
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- T2: Entity Type Identification
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- T3: Related Pair Detection
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- T4: Relationship Type Identification
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This is the most versatile model in the AZERG collection, capable of handling all STIX extraction sub-tasks.
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## Intended Use
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This model is intended to be used within the [AZERG framework](https://github.com/QCRI/azerg/) to extract STIX entities and relationships from security reports. Please check the exact prompts in the framework.
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Example Prompt (Task 1: Entity Detection):
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```
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Instruction:
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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.
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STIX entity types:
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- ATTACK_PATTERN: A type of TTP that describes ways that adversaries attempt to compromise targets. (e.g., T1051, T1548.001, etc.)
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[...]
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Answer in the following format: <entities>LIST OF IDENTIFIED ENTITIES SEPARATED BY PIPE |</entities>
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Input:
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- Text Passage: [INPUT TEXT]
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Response:
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```
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## Citation
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If you use this model, please cite our paper:
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```
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@article{lekssays2025azerg,
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title={From Text to Actionable Intelligence: Automating STIX Entity and Relationship Extraction},
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author={Lekssays, Ahmed and Sencar, Husrev Taha and Yu, Ting},
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journal={arXiv preprint arXiv:2507.16576},
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year={2025}
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}
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``` |