Automated ATT&CK Technique Chaining

Author:

Skjøtskift Geir1ORCID,Eian Martin1ORCID,Bromander Siri1ORCID

Affiliation:

1. mnemonic AS, Norway

Abstract

Incident response teams need to determine what happened before and after an observation of adversary behavior in order to effectively respond to incidents. The MITRE ATT&CK knowledge base provides useful information about adversary behaviors, but provides no guidance on what most likely happened before and after an observed behavior. We have developed methods and open source tools to help incident responders answer the questions “What did most likely happen prior to this observation?” and “What are the adversary's most likely next steps given this observation?”. To be able to answer these questions, we combine semantic modeling of subject matter expert knowledge with data-driven methods trained on data from computer security incidents.

Publisher

Association for Computing Machinery (ACM)

Reference21 articles.

1. Palo Alto Unit 42. 2023. Unit 42 Adversary Playbooks. Retrieved December 20 2023 from https://github.com/pan-unit42/playbook_viewer/tree/master/playbook_json

2. Rawan Al-Shaer Jonathan M. Spring and Eliana Christou. 2020. Learning the Associations of MITRE ATT&CK Adversarial Techniques. In 2020 IEEE Conference on Communications and Network Security (CNS). 1–9. https://doi.org/10.1109/CNS48642.2020.9162207

3. Andy Appelbaum. 2019. Finding Dependencies Between Adversary Techniques. Retrieved December 11 2023 from https://www.first.org/resources/papers/conf2019/1100-Applebaum.pdf

4. Jan A. Bergstra and Mark Burgess. 2014. Promise Theory: Principles and Applications (2nd. ed.). Independently published.

5. Christian Ellerhold Johann Schnagl and Thomas Schreck. 2023. Enterprise Cyber Threat Modeling and Simulation of Loss Events for Cyber Risk Quantification. In Proceedings of the 2023 on Cloud Computing Security Workshop. 17–29.

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