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--- |
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license: odc-by |
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task_categories: |
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- text-generation |
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language: |
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- en |
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pretty_name: Primus-Seed |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/*/*/* |
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- config_name: cybersecurity_companies_websites |
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data_files: |
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- split: train |
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path: data/web_crawler_official_dump/cybersecurity_companies_websites/* |
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- config_name: cybersecurity_wikis |
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data_files: |
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- split: train |
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path: data/web_crawler_official_dump/cybersecurity_wikis/* |
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- config_name: mitre |
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data_files: |
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- split: train |
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path: data/web_crawler_official_dump/mitre/* |
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tags: |
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- cybersecurity |
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- pretraining |
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- wikipedia |
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- MITRE |
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size_categories: |
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- 100K<n<1M |
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extra_gated_fields: |
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Affiliation: text |
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Country: country |
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I want to use this model for: |
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type: select |
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options: |
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- Research |
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- Commercial |
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- label: Other |
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value: other |
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Job title: |
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type: select |
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options: |
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- Student |
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- Research graduate |
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- AI researcher |
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- AI developer/engineer |
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- Cybersecurity researcher |
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- Reporter |
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- Other |
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geo: ip_location |
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--- |
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# PRIMUS: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Training |
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## 🤗 Primus-Seed |
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**Primus-Seed** is a high-quality🚀 cybersecurity text dataset composed of data crawled from reputable sources such as MITRE, Wikipedia, and well-known cybersecurity company websites, as well as CTI manually collected by our threat experts. |
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## Statistics |
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| **Category** | **Samples** | **Tokens** | **Avg.** | |
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|-------------|------------|------------|----------| |
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| **_Web Crawl / Official Dump_** | | | | |
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| Cybersecurity Blogs/News | 2,946 | 9,751,002 | 3,309.9 | |
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| Cybersecurity Books | 6,499 | 2,910,464 | 447.8 | |
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| Cybersecurity Companies Websites | 76,919 | 65,798,561 | 855.4 | |
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| Cybersecurity Wikipedia | 6,636 | 9,567,196 | 1,441.7 | |
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| MITRE | 3,432 | 2,435,118 | 709.5 | |
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| **_Expert Curation_** | | | | |
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| Campaigns | 136 | 37,106 | 272.8 | |
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| Intrusion Sets | 343 | 60,524 | 176.5 | |
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| Malware | 7,301 | 1,362,681 | 186.6 | |
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| Reports | 11,317 | 934,954 | 82.6 | |
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| Threat Actors | 27 | 2,264 | 83.9 | |
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| Tools | 238 | 19,926 | 83.7 | |
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| Vulnerabilities | 559,054 | 98,006,720 | 175.3 | |
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| **Total** | **674,848** | **190,886,516** | **282.9** | |
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❗❗Currently, we have only released **Cybersecurity Companies Websites, Cybersecurity Wikipedia, and MITRE**. Other categories are under review to ensure compliance and verify whether redistribution falls under "_fair use_." |
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## How Did We Collect Cybersecurity Wikipedia? |
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_Wikipedia_ does not provide a predefined cybersecurity subset, so we perform a custom filtering process. Each Wikipedia article is associated with one or more category tags, which can be further expanded into subcategory tags. Starting from the root category "_Computer Security_", we recursively traverse its subcategories, using GPT-4o to determine whether a category is cybersecurity-related. This process yields **375** relevant categories, from which we extract corresponding Wikipedia articles. |
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_Prompt_: |
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``` |
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[System] |
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You are a helpful assistant. |
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[User] |
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Help me identify and mark the categories related to "cybersecurity", "information |
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security", "data protection", "cryptography", "hacker activity", "cyber attack", |
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"cybercrime" from a list of categories I have. |
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For each category, provide a reason for marking it as 'Y' (Yes) or 'N' (No) in relation to the |
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specified topics. Finally, output the results in JSON format with the fields: category, |
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reason, security. |
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{{category-list} |
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``` |
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🚀🚀 For more details, see our paper: |
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[https://arxiv.org/abs/2502.11191](https://arxiv.org/abs/2502.11191) |
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## License |
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This dataset is released under the **ODC-By** license. |
