Google unveiled a significant wave of advancements designed to supercharge how developers build and scale AI applications – from early-stage experimentation right through to large-scale deployment.
Security and software go together like peanut butter and jelly (PB&J). They're a good thing apart but a great thing together. So why are many developers prioritizing one or the other and not leveraging this awesome combination?
More than 90%(link is external) of modern applications contain personal data from users, meaning they're susceptible to attacks. However, conducting manual application security tests is a hectic task that involves a significant amount of time and resources and slows down your project's development velocity.
For this reason, developers are often forced to compromise security to improve delivery times. For example, even as cloud technologies are taking over, only 40% of global enterprises have security policies to protect their cloud infrastructure, development processes, and applications, according to research findings. And this is a very bad thing.
With the increasing threat of cyber attacks, developers need to take the necessary steps to protect applications and find a middle ground between security and delivery time. Just like a PB&J, it'll be worth it in the end.
What is SAST?
SAST (Static Application Security Testing)(link is external) detects vulnerabilities in an application at the code level by scanning source code. As we all know, fixing issues after going live with a new or updated application takes a significant effort. SAST solves this problem by helping you find security flaws during the initial design and build stages.
Integrating SAST into your existing development environment promotes automation to streamline the assessments, and its analytics capabilities act as a learning tool for devs by providing them with feedback.
These tools support the existing language that your dev teams use and plug into common IDEs to perform comprehensive code-level security assessments; SAST tools give devs a helping hand in fixing vulnerabilities while meeting security industry standards like OWASP Top 10(link is external).
What is DAST?
Rather than analyzing the source code, DAST (Dynamic Application Security Testing)(link is external) infiltrates the application and provides a real-time assessment of the exposed vulnerabilities by mimicking the actions of an attacker. Kind of like putting your red hat on.
This strategy emulates a black-box testing approach to find misconfigurations within servers that affect the web application at runtime, authentication, and encryption, essentially covering what a typical SAST doesn't.
DAST doesn't offer the feedback and dev learning capabilities of SAST. In fact, dynamic testing falls into the hands of dedicated QA teams just before deployment in the latter stages of the SDLC, after the code compilation. Of course, detection later in the SDLC makes remediation more expensive, so DAST is pricier than SAST.
Finally, What is IAST?
You guessed it, next up is IAST (Interactive Application Security Testing), which brings together the best of SAST and DAST while addressing the drawbacks of each. IAST conducts dynamic assessments of the application during operation, similar to DAST, and it also runs from inside the application server to analyze the code, like SAST. Interactive analysis provides devs with information and real-time insights into the root cause of vulnerabilities. It evaluates a focused part of the application and runs during the testing phase of the development lifecycle.
Although IAST works well with modern apps, legacy applications might run into trouble because this strategy offers limited language support. In situations like this, you can use RASP (Runtime Application Self Protection)(link is external), an evolution of the typical testing approach that focuses more on end-user and traffic analysis to prevent attacks at runtime rather than security testing.
Go to SAST vs. DAST vs. IAST: How is a Developer to Choose? - Part 2
Industry News
Red Hat announced Red Hat Advanced Developer Suite, a new addition to Red Hat OpenShift, the hybrid cloud application platform powered by Kubernetes, designed to improve developer productivity and application security with enhancements to speed the adoption of Red Hat AI technologies.
Perforce Software announced Perforce Intelligence, a blueprint to embed AI across its product lines and connect its AI with platforms and tools across the DevOps lifecycle.
CloudBees announced CloudBees Unify, a strategic leap forward in how enterprises manage software delivery at scale, shifting from offering standalone DevOps tools to delivering a comprehensive, modular solution for today’s most complex, hybrid software environments.
Azul and JetBrains announced a strategic technical collaboration to enhance the runtime performance and scalability of web and server-side Kotlin applications.
Docker, Inc.® announced Docker Hardened Images (DHI), a curated catalog of security-hardened, enterprise-grade container images designed to meet today’s toughest software supply chain challenges.
GitHub announced that GitHub Copilot now includes an asynchronous coding agent, embedded directly in GitHub and accessible from VS Code—creating a powerful Agentic DevOps loop across coding environments.
Red Hat announced its integration with the newly announced NVIDIA Enterprise AI Factory validated design, helping to power a new wave of agentic AI innovation.
JFrog announced the integration of its foundational DevSecOps tools with the NVIDIA Enterprise AI Factory validated design.
GitLab announced the launch of GitLab 18, including AI capabilities natively integrated into the platform and major new innovations across core DevOps, and security and compliance workflows that are available now, with further enhancements planned throughout the year.
Perforce Software is partnering with Siemens Digital Industries Software to transform how smart, connected products are designed and developed.
Reply launched Silicon Shoring, a new software delivery model powered by Artificial Intelligence.
CIQ announced the tech preview launch of Rocky Linux from CIQ for AI (RLC-AI), an operating system engineered and optimized for artificial intelligence workloads.
The Linux Foundation, the nonprofit organization enabling mass innovation through open source, announced the launch of the Cybersecurity Skills Framework, a global reference guide that helps organizations identify and address critical cybersecurity competencies across a broad range of IT job families; extending beyond cybersecurity specialists.
CodeRabbit is now available on the Visual Studio Code editor.
The integration brings CodeRabbit’s AI code reviews directly into Cursor, Windsurf, and VS Code at the earliest stages of software development—inside the code editor itself—at no cost to the developers.