In early August, Arctic Wolf Labs began observing a marked increase in Fog and Akira ransomware intrusions where initial access to victim environments involved the use of SonicWall SSL VPN accounts. Based on victimology data showing a variety of targeted industries and organization sizes, we assess that the intrusions are likely opportunistic, and the threat actors are not targeting a specific set of industries.

Read also: Japan's police arrest 18 members of a cybercrime group, FBI’s most wanted cybercriminal arrested in Italy, and more.

Application security has transformed from being an afterthought to a central focus as threats have evolved. What was once about securing code has expanded to protecting the entire application lifecycle. The rise of cloud-native architectures, microservices, and APIs has broadened the attack surface, requiring security teams to rethink their approaches.

Wallarm’s Security Edge is setting a new standard in API security—far beyond the reach of traditional Content Delivery Networks (CDNs). Let’s get it straight: Security Edge is not just a new addition to the API security market; it’s a disruption. Designed to deliver fast, effective, and advanced API protection where APIs need it, Wallarm’s Security Edge targets what CDNs cannot.

As small and mid-sized businesses (SMBs) across Asia adopt cloud technologies to accelerate growth, securing your cloud infrastructure becomes a significant challenge. The complexities of managing cloud environments, regulatory compliance, and ensuring real-time threat detection require robust solutions that are both scalable and cost-effective.

AI is growing in power and scope and many organizations have moved on from “simply” training models. In this blog, we will cover a common system of LLM use called Retrieval-Augmented Generation (RAG). RAG adds some extra steps to typical use of a large language model (LLM) so that instead of working off just the prompt and its training data, the LLM has additional, usually more up-to-date, data “fresh in mind”.

If you’re on the frontlines of your organization’s cybersecurity department, you’ve likely found yourself burdened by security questionnaires. Whether you’re in charge of evaluating vendor responses or completing questionnaires yourself, it’s no secret these requests can be time-consuming for everyone involved. Well, what if this didn’t have to be the case?

Source code leaks refer to the process in which the source codes of proprietary applications are made available to unauthorized persons or the public domain for various reasons. This might happen in several scenarios, including when information is leaked through public repositories, hacking attacks, internal threats, or when it is posted in version control systems.

Cloud native applications are dominating the tech landscape for modern enterprises. A garden-variety cloud native application consists of microservices deployed in containers orchestrated with Kubernetes, and these microservices interact together via APIs. Netflix, Salesforce, and Atlassian products like Jira and Confluence are all common examples of cloud native applications.

We all know identity management and security are critical to hardening cybersecurity ecosystems. We also know that we can make it happen using the many features and functions across Active Directory (AD), Entra ID and Microsoft 365. The challenge is making sure these are deployed in a way that allows them to work seamlessly together, staying aligned even in environments where there’s fluidity and decentralization.