As seen in recent sophisticated cyberattacks, especially human-operated campaigns, it’s critical to not only detect an attack as early as possible but also to rapidly determine the scope of the compromise and predict how it will progress. How an attack proceeds depends on the attacker’s goals and the set of tactics, techniques, and procedures (TTPs) that they utilize to achieve these goals. Hence, quickly associating observed behaviors and characteristics to threat actors provides important insights that can empower organizations to better respond to attacks.
Microsoft uses statistical methods to improve our ability to track specific threat actors and the TTPs associated with them. Threat actor tracking is a constant arms race: as defenders implement new detection and mitigation methods, attackers are quick to modify techniques and behaviors to evade detection or attribution. Manually mapping specific indicators like files, IP addresses, or known techniques to threat actors and keeping track of changes over time isn’t effective or scalable.
To tackle this challenge, Microsoft has built a probabilistic models that enable us to quickly predict the likely threat group responsible for an attack, as well as the likely next attack stages. With these models, security analysts can move from a manual method of investigating small sets of disparate signals to probabilistic determinations of likely threat groups based on all activity observed, comparing the activity against all known behaviors, both past and present, encoded in the model. These models help threat intelligence teams stay current on threat actor activity and help analysts quickly identify behaviors they need to analyze when investigating an attack.
The model enriches targeted attack notifications with additional context on the threat, the likely attacker and their motivation, the steps the said attacker is likely to make next, and the immediate action the customer can take to contain and remediate the attack. Below we discuss an incident in which automated threat actor tracking translated to real-world protection against a human-operated ransomware attack.
Read the full article by Microsoft 365 Defender Research Team - https://www.microsoft.com/security/blog/2021/04/01/automating-threat-actor-tracking-understanding-attacker-behavior-for-intelligence-and-contextual-alerting/
