Presentation Material
AI Generated Summary
This talk details investigative methodologies for tracking and detecting ransomware groups, emphasizing the analysis of attack chains, tool reuse, and rebranding patterns. The research is based on real-world incident responses and telemetry from security products, combined with open-source intelligence.
Key findings include the identification of specific ransomware operations like Akira, which initially exploited Cisco VPN vulnerabilities without MFA before expanding to other vectors. The talk illustrates how threat hunters correlated initial access indicators (e.g., specific IPs, vulnerable VPN use) with later-stage ransomware deployment to build comprehensive attack narratives. A significant portion focuses on rebranding detection, demonstrating how code reuse, shared configuration structures, and identical TTPs (e.g., targeted file extensions, use of tools like AnyDesk and RustDesk) reveal connections between seemingly new ransomware families and their predecessors (e.g., Magniber/Server 2017, No Escape/Conti).
A major technical challenge highlighted is the detection of loaders—the malware staging tools that precede ransomware execution. Loaders employ sophisticated evasion techniques (API hashing, process hollowing, search order hijacking, anti-sandbox delays) and frequently evolve, making static hash-based detection ineffective. The speaker argues that effective detection requires building hunting queries around specific loader behaviors, such as in-memory decryption routines, known file naming patterns, and the use of particular command-line arguments for tools like Rclone or Cobalt Strike.
Practical takeaways stress the need for deep endpoint visibility to trace infection vectors, the importance of enriching threat knowledge bases by connecting disparate attack components (e.g., phishing emails → loader → ransomware), and the necessity for security products to include logic for detecting loader techniques and suspicious legitimate tool usage. The research underscores that understanding the full attack chain, especially the loader phase, is critical for early disruption.