Cybercrime & Digital Threats

In today’s rapidly evolving digital landscape, the risk of personal and professional data being stolen by nefarious actors looms larger than ever. This report lays bare the stark reality of this threat, with a specific focus on the unequal risks associated with data theft and its subsequent misuse.

In our previous entry, we examined how credentials were being stored and logged in cleartext on compute instances (CIs) created in Azure Machine Learning (AML) service and the risks posed by the same. This article examines an information disclosure bug we found in one of the cloud agents used in the AML service and sheds light on the importance of threat modeling the agents’ features to uncover silent and hidden attack surfaces.

We summarize the cybercriminal trends surrounding the Linux threat landscape last year, and what security teams and organizations can do to mitigate the risks and defend against attacks.

We probed the Azure Machine Learning (AML) service to identify security flaws and vulnerabilities and shed light on the unseen aspects of silent threats in managed services like AML.

This report discusses the state of generative artificial intelligence (AI) in the cybercriminal underground: how cybercriminals are using ChatGPT, how they're adding ChatGPT features to their criminal products, and how they’re trying to remove censorship to ask ChatGPT anything.

This report discusses how malicious actors will be able to deploy harpoon whaling attacks, which are highly targeted whaling attacks on specific groups of powerful and high-ranking individuals, by abusing AI tools.

This article gives an overview of the elements of virtual kidnapping and how malicious actors use social engineering tactics and abuse AI voice cloning tools and ChatGPT to launch these attacks.

This report delves into the nature of pig-butchering scams, how scammers carry out their operations, the new pig-butchering tactics we’ve observed in the wild, and what individuals can do to avoid falling for these fraudulent investments and dealing with massive amounts of debt.

We explore three differently sized criminal groups to determine how they compare to similarly sized legitimate businesses in terms of how they are organized. We also discuss the advantages of knowing the size of a target criminal organization for cybercrime investigators.