Investigación

Generative AI continues to be misused and abused by malicious individuals. In this article, we dive into new criminal LLMs, criminal services with ChatGPT-like capabilities, and deepfakes being offered on criminal sites.

Distributed energy generation (DEG) is a term used to describe the shift from centralized energy generation, such as power companies, to a source — typically a renewable energy source — closer to the user.

As technologies continue to evolve and expand, organizations experience a technological paradox: Their increasing interconnectivity means that they simultaneously become more distributed. Case in point, robust cloud and networking technologies support today’s widespread adoption of hybrid and remote work arrangements, allowing employees all over the globe to work remotely full time or at least part of the time.

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.

The lack of encryption and authentication mechanisms in the GTP-U protocol between base stations and 5GC UPFs could allow cybercriminals to use a packet reflection vulnerability to carry out attacks on 5G devices in internal networks.

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.

Our research identifies sensitive environmental variables in the Microsoft Azure environment that, when leaked, can be used by malicious actors to compromise the entire serverless environment.

Our research paper shows how decision-makers that are in a position to affect ransomware at scale – including policy-makers and industry leaders – can use data-science approaches to understand ransomware risk holistically and build cybersecurity strategies that can affect the ransomware ecosystem as a whole.