TTPXHunter: Actionable Threat Intelligence Extraction as TTPs from Finished Cyber Threat Reports
Nanda Rani, Bikash Saha, Vikas Maurya, Sandeep Kumar Shukla

TL;DR
TTPXHunter is a novel NLP-based system that automatically extracts structured Tactics, Techniques, and Procedures (TTPs) from cyber threat reports, significantly improving threat intelligence analysis accuracy and speed.
Contribution
It introduces a new methodology leveraging domain-specific NLP and data augmentation to enhance TTP extraction from unstructured threat reports, outperforming existing solutions.
Findings
Achieved 92.42% F1-score on augmented dataset
Achieved 97.09% F1-score on real-world report dataset
Created large-scale datasets for TTP extraction evaluation
Abstract
Understanding the modus operandi of adversaries aids organizations in employing efficient defensive strategies and sharing intelligence in the community. This knowledge is often present in unstructured natural language text within threat analysis reports. A translation tool is needed to interpret the modus operandi explained in the sentences of the threat report and translate it into a structured format. This research introduces a methodology named TTPXHunter for the automated extraction of threat intelligence in terms of Tactics, Techniques, and Procedures (TTPs) from finished cyber threat reports. It leverages cyber domain-specific state-of-the-art natural language processing (NLP) to augment sentences for minority class TTPs and refine pinpointing the TTPs in threat analysis reports significantly. The knowledge of threat intelligence in terms of TTPs is essential for comprehensively…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Cybercrime and Law Enforcement Studies · Network Security and Intrusion Detection
