Threat-based vulnerability management: mapping CVEs to the MITRE ATT&CK framework

Mapping Common Vulnerabilities and Exposures (CVEs) to the MITRE Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) framework plays a crucial role in cybersecurity, particularly in threat mitigation and risk management. Accurate and automated CVE-to-ATT&CK mapping enables defenders to better assess the risks posed by emerging vulnerabilities. Prior work has relied primarily on CVE descriptions to establish links to relevant tactics and techniques. However, these approaches struggle when descriptions are incomplete or poorly written. This research proposes that enriching CVE descriptions with extended features, such as exploitability scores, software weaknesses, system and software identifiers, attack patterns, and classification data, substantially improves mapping accuracy. In unsupervised evaluations, this enrichment increased correct mappings by 42% to 66.7% and reduced misclassifications by 6%. In supervised experiments, the proposed SecRoBERTa model significantly outperformed prior work. While baseline models achieved a weighted F1 score of 78.88%, the fully extended and Optuna-tuned version reached 93.47%, marking a 14.6% improvement. These results demonstrate the effectiveness of combining structured feature enrichment with hyperparameter optimization to enhance the accuracy and reliability of CVE-to-ATT&CK mappings.

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Research Portal (Queen's University Belfast)
Published
2025-10-26
Primary Topic
Information and Cyber Security
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article
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article

Threat-based vulnerability management: mapping CVEs to the MITRE ATT&CK framework

Oluwafemi; id_orcid 0000-0003-2771-2553 Olukoya, Logan McMahon
Research Portal (Queen's University Belfast)
Information and Cyber Security
article

Threat-based vulnerability management: mapping CVEs to the MITRE ATT&CK framework

Oluwafemi; id_orcid 0000-0003-2771-2553 Olukoya, Logan McMahon
article en

Abstract

Mapping Common Vulnerabilities and Exposures (CVEs) to the MITRE Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) framework plays a crucial role in cybersecurity, particularly in threat mitigation and risk management. Accurate and automated CVE-to-ATT&CK mapping enables defenders to better assess the risks posed by emerging vulnerabilities. Prior work has relied primarily on CVE descriptions to establish links to relevant tactics and techniques. However, these approaches struggle when descriptions are incomplete or poorly written. This research proposes that enriching CVE descriptions with extended features, such as exploitability scores, software weaknesses, system and software identifiers, attack patterns, and classification data, substantially improves mapping accuracy. In unsupervised evaluations, this enrichment increased correct mappings by 42% to 66.7% and reduced misclassifications by 6%. In supervised experiments, the proposed SecRoBERTa model significantly outperformed prior work. While baseline models achieved a weighted F1 score of 78.88%, the fully extended and Optuna-tuned version reached 93.47%, marking a 14.6% improvement. These results demonstrate the effectiveness of combining structured feature enrichment with hyperparameter optimization to enhance the accuracy and reliability of CVE-to-ATT&CK mappings.

Research Portal (Queen's University Belfast)
Queen's University Belfast (GB)
Openalex Percentile: Top 12%
Information and Cyber Security
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Threat-based vulnerability management: mapping CVEs to the MITRE ATT&CK framework — Oluwafemi; id_orcid 0000-0003-2771-2553 Olukoya, Logan McMahon · Research Portal (Queen's University Belfast) (2025) | TGRS Research Map | TGRS