Cybercrime & Digital Threats

Red teaming tools, which organizations use in cyberattack simulations and security assessments, have become an important cybersecurity component for those looking to strengthen organizational defenses.

Our report dives into the evolution and security of blockchains and how enterprises are increasingly adopting this technology in the forms of private and hybrid blockchains.

Businesses worldwide are increasingly moving to the cloud. The demand for remote work, for instance, has driven a surge in cloud-based services, offering companies the flexibility and efficiency that traditional data centers often lack.

As cybercriminals shift their attacks with new technologies and strategies, maintaining visibility across the attack surface becomes increasingly challenging.

Elections are the cornerstone of modern democracy, an exercise where a populace expresses its political will through the casting of ballots. But as electoral systems adopt and embrace technology, this introduces significant cybersecurity risks, not only to the infrastructure supporting an election but also to the people lining up in polling booths.

This article dives into the practice of “red teaming“. Red team exercises give enterprises valuable insights into their security posture, and promote a culture of continuous improvement. It has become an integral part of global risk management.

The cybercriminal abuse of generative AI (GenAI) is developing at a blazing pace. After only a few weeks since we reported on Gen AI and how it is used for cybercrime, new key developments have emerged. Threat actors are proliferating their offerings on criminal large language models (LLMs) and deepfake technologies, ramping up the volume and extending their reach.

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.

In the latest installment of our ongoing series where we identify and investigate security flaws in Azure Machine Learning (AML), we explore how cybercriminals could manage to covertly gain persistence in AML workspaces.