Anna Seitz and Daria Pop, both Microsoft security researchers, delve deep into the world of ransomware and cyber threats. They discuss the Black Basta ransomware group’s evolution from simple phishing to sophisticated social engineering tactics, including malware distribution via Microsoft Teams. The duo highlights the persistence of malvertising and its implications for cybersecurity. They reveal how state-sponsored actors are leveraging large language models, emphasizing the dual nature of AI as both a tool for security and a weapon for attackers.
Black Basta has evolved its tactics from phishing to advanced social engineering, demonstrating agility in response to law enforcement actions like the Qakbot takedown.
State-sponsored groups like Emerald Sleep are utilizing large language models to enhance their cyber operations, raising concerns about the sophistication of AI-enhanced phishing attempts.
Deep dives
Evolution of BlackBasta's Tactics
BlackBasta has adapted its initial access methods over the years, highlighting a trend of evolving cybercrime techniques. Initially, phishing was the primary access method, involving malicious emails with links or documents that distributed malware like Quackbot. As recent operations unfolded, the group shifted to employing tools like Peekabot and Darkgate, showing agility in response to law enforcement actions like the Quackbot takedown. The latest tactics include complex social engineering strategies using voice phishing and Microsoft Teams to exploit targets, indicating a broader evolution of their operational tactics.
Social Engineering and Remote Management Tools
A noteworthy tactic employed by threat actors involves impersonating IT support to gain unauthorized access to victims' devices via remote management tools. This approach includes targeted mass email campaigns followed by phone calls, deceiving victims into believing they are receiving technical assistance. Once access is granted, attackers can upload malicious payloads and conduct further exploits. The discussion emphasizes the importance for organizations to disable unused remote tools and remain vigilant against unsolicited tech support interactions to mitigate these risks.
Threat Actors Leveraging AI Technology
Threat actors are increasingly utilizing large language models (LLMs) to enhance their cyber operations, reflecting a trend where adversaries adapt to new technologies for more effective attacks. Specific state-sponsored groups, such as Forest Blizzard and Emerald Sleep, employ LLMs to conduct research, automate tasks, and refine social engineering campaigns. The integration of AI tools into their strategies raises concerns about the difficulty of identifying phishing attempts, as these tools enable more sophisticated and convincing communications. Security organizations are urged to bolster their defenses, maintain security hygiene, and educate staff to recognize potential AI-enhanced threats.
In this episode of the Microsoft Threat Intelligence Podcast host Sherrod DeGrippo is joined by Microsoft security researchers Anna Seitz and Daria Pop to discuss the latest trends in ransomware and the evolving role of AI in cyber threats. Daria Pop provides insights into the shifting tactics of Black Basta ransomware, including their use of phishing, social engineering, and remote management tools. The discussion also covers the persistence of malvertising and its challenges for defenders. Anna Seitz explores how state-sponsored threat actors, including Forest Blizzard, Emerald Sleet, and Crimson Sandstorm, are leveraging large language models (LLMs) for various malicious activities.
In this episode you’ll learn:
Why the takedown of Qakbot impacted Black Basta’s strategies
What malvertising is and why its persistence is due to the complex nature of ad traffic
How the MITRE Atlas framework assists defenders in identifying new threats
Some questions we ask:
What role does social engineering play in the campaigns involving Quick Assist?
How are North Korean threat actors like Emerald Sleep using LLMs for their campaigns?
Can you explain the changes in Black Basta’s initial access methods over the years?