Dynamic Application Security Testing (DAST), sometimes referred to as “pentesting in a box”, tests running code for a variety of issues that can’t easily be found by analyzing code with static scanning tools. DAST tools are platform and language agnostic—as long as you have a website or API they can connect to, they’ll get the job done, and find real vulnerabilities in the same places an attacker would.

The application security landscape is shifting as organizations move away from a fragmented ecosystem of point solutions towards a unified platform such as the Mend AppSec Platform. Leveraging these platform-specific strengths brings numerous advantages: streamlined workflows, a cross-product workflow engine, a consolidated data model that enhances security posture, and developers that can focus fully on innovation.

With external threats looming as a constant source of potential disruption, multiple government agencies have coordinated to compile a catalog of Known Exploited Vulnerabilities (KEV). The Known Exploited Vulnerabilities Catalog, or KEV catalog, is a database of actively exploited vulnerabilities, including those that have been exploited by ransomware campaigns, that can help application security professionals in the public and private sectors monitor threats and prioritize fixes.

Application security is the combination of tools, practices, and policies that are used to protect the application layer of software from threat actors. Once something of an afterthought, application security is now widely and rightfully recognized as a vital part of the software development life cycle (SDLC). As the complexity of technology increases, considering application security early and often in the SDLC is imperative to keeping data and resources from falling into the wrong hands.

According to Dimension Market Research, the global Application Security Market size is projected to “reach USD $9.6 billion by 2024 and is further anticipated to reach USD $47.3 billion by 2033 at a CAGR of 19.4%.” However, companies confront extensive barriers when developing reliable application security programs.

Gartner’s 2024 Hype Cycle for Application Security is making the rounds, and Application Security Posture Management (ASPM) continues to climb up and around the famous curve, from the Peak of Inflated Expectations in 2023 to this year’s slide towards the Trough of Disillusionment. That’s pretty fast movement for a technology that we haven’t yet succeeded in clearly defining!

After speaking to a wide spectrum of customers ranging from SMBs to enterprises, three things have become clear: Add that together, and we get Shadow AI. This refers to AI usage that is not known or visible to an organization’s IT and security teams. Shadow AI comes in many forms, but in this blog we’ll stick to a discussion of Shadow AI as it pertains to applications. Application security teams are well aware that AI models come with additional risk.

I’m back from another Black Hat! It was great seeing everyone. I put out a message on LinkedIn for people to come find me and, boy, did they. The hallway conversations were so engaging, I was sometimes late getting to the official talks, but I’m getting ahead of myself. AI was everywhere, as we’d expect, but I also sat down to listen to experts on other topics like critical infrastructure, cyber insurance, and the root causes of cybersecurity failure.

This is a public service announcement: The not-so-simple act of securing applications produces a lot of documentation, including playbooks and policies, that isn’t typically needed on a daily basis. But when a zero-day event occurs, such as the recent Crowdstrike incident, application security teams better be able to find everything they need—and fast. Sadly, in both big and small companies, missing and outdated documentation is rampant.

Large language models are fascinating tools for cybersecurity. They can analyze large quantities of text and are excellent for data extraction. One application is researching and analyzing vulnerability data, specifically Common Vulnerabilities and Exposures (CVE) information. As an application security company with roots in open source software vulnerability detection and remediation, the research team at Mend.io found this a particularly relevant area of exploration.