AnnoCTR Resources

This repository contains the companion material for the following publication:

Lukas Lange, Marc Müller, Ghazaleh Haratinezhad Torbati, Dragan Milchevski, Patrick Grau, Subhash Pujari, Annemarie Friedrich. AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reports. LREC-COLING 2024.

Please cite this paper if using the dataset or the code, and direct any questions to Lukas Lange. The paper can be found at the ACL Anthology (tbd.) or at ArXiv.

Purpose of this Software

This software is a research prototype, solely developed for and published as part of the publication cited above. It will neither be maintained nor monitored in any way.

The AnnoCTR Corpus

AnnoCTR consists of 400 cyber threat reports that have been obtained from commercial CTI vendors. The reports describe threat-related information such as tactics, techniques, actors, tools, and targeted industries. The reports have been annotated by a domain expert with named entities, temporal expressions, and cybersecurity-specific concepts. The annotations include mentions of organizations, locations, industry sectors, time expressions, code snippets, hacker groups, malware, tools, tactics, and techniques.

The dataset is split into three parts: train, dev, and test, with 60%, 15%, and 25% of the documents, respectively. The train set is used for model training, the dev set is used for model selection, and the test set is used for evaluation.

For further information on the annotation scheme, please refer to our paper and the annotation guidelines for the general concepts and cybersecurity-specific concepts.

Corpus File Formats

This is an HF friendly dataset loader for training LLMs on the NER tags.

Usage Example

from datasets import load_dataset

annodb = load_dataset("priamai/AnnoCTR","all_tags",trust_remote_code=True)

label_list = annodb["train"].features[f"all_tags"].feature.names

The letter that prefixes each tag indicates the token position of the entity:

• B- indicates the beginning of an entity.
• I- indicates a token is contained inside the same entity (for example, the State token is a part of an entity like Empire State Building).
• 0 indicates the token doesn't correspond to any entity.

There are 23 tags currently.

Acknowledgements

The reports have been kindly donated by Intel471, Lab52, the threat intelligence division of S2 Grupo, Proofpoint, QuoIntelligence, and ZScaler.

License

The AnnoCTR corpus located in the folder AnnoCTR is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC-BY-SA 4.0).