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”.

Managing compliance in federal IT is a critical and complex task, especially when it comes to addressing findings from security assessments. One of the key tools to bridge the gap between requirements and the current state is the Plan of Action and Milestones (POA&M). Required by federal security frameworks like the Federal Information Security Modernization Act (FISMA) and NIST 800-53, POA&Ms are used to document security weaknesses, outline mitigation plans, and track their resolution.

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.

With sophisticated cyberattacks getting more frequent every day, and regulations around data privacy tightening, businesses across Europe are facing a big challenge: How do you keep your network safe, stay ahead of threats and make sure you're compliant with the latest regulations? Enter the NIS2 Directive — a step up for cybersecurity that demands organizations be ready to face any cyber storm that comes their way.

As networks become increasingly distributed, user identities are becoming a top adversary target. CrowdStrike’s 2024 Threat Hunting Report and 2024 Global Threat Report state 5 of the top 10 MITRE tactics we observed in 2023 were identity-based, and the CrowdStrike 2023 Threat Hunting Report noted a 583% year-over-year increase in Kerberoasting attacks. These findings illustrate how modern adversaries aren’t breaking in — they’re logging in.

Despite the rapid evolution of security technologies, many SOCs are still weighed down by manual processes and outdated tools. Analysts are burdened with repetitive tasks, inefficient workflows, and disjointed incident response mechanisms. This broken system is leaving SOCs reacting to incidents instead of preventing them. There’s a better way forward.

Historically, Mac users haven't had to worry about malware as much as their Windows-using cousins. Although malware targeting Apple devices actually predates viruses written for PCs, and there have been some families of malware that have presented a significant threat for both operating systems (for instance, the Word macro viruses that hit computers hard from 1995 onwards), it is generally the case that you're simply a lot less likely to encounter malware on your Mac than you are on your Windows PC.

Over the past few decades, securing remote access has become monumentally more complex. Remote work, with all of its benefits, has also furthered the threats of shadow IT and unauthorized remote access.

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.

During the long-awaited Snyk Launch 2024, we announced the exciting general availability of Snyk Code's auto-fixing feature, DeepCode AI Fix, powered by our AI machine, DeepCode AI! To celebrate this milestone, let’s explore how Snyk’s AI-powered features differentiate our approach to application security. AI is on everyone's minds, along with its countless applications that offer a wide variety of solutions (and issues).