Research

Modern compilers are remarkably effective at transforming source code into efficient machine code. Over decades, compiler optimization has evolved through carefully designed passes that simplify instructions, remove unnecessary work, improve memory access, and take advantage of processor capabilities. Large Language Models introduce a different type of capability. Instead of relying only on predefined transformation rules,

Software testing is one of the most important safeguards in modern software development. Unit tests, integration tests, and regression suites help teams detect defects before software reaches production. But there is an important difference between having tests and having tests that are actually capable of detecting incorrect behavior. A test suite may cover most of

Building AI and security products today is no longer just about model accuracy or security metrics. It’s about end-to-end performance, security posture, infrastructure efficiency, and economic viability. If you’re making product or research decisions, you need a holistic benchmark framework, one that spans: Below is a structured deep dive into the most important metrics across

Last year, we introduced Software Component Analysis (SCA) as a core capability in our Application Security platform. The goal was simple but critical: extend vulnerability detection beyond first-party code and into the vast ecosystem of third-party and open-source dependencies that modern software is built on. In today’s cloud-native and AI-driven development environments, applications are rarely

As organizations race to adopt AI, modern cloud environments are becoming more complex, distributed, and dynamic than ever before. AI workloads demand elastic infrastructure, access to massive datasets, accelerated compute, and deep integration across cloud services. At the same time, this expansion dramatically increases the attack surface. Security teams are no longer protecting a single

AI-driven applications are reshaping how software is built, deployed, and operated. Models are trained continuously, inference services scale elastically, and data flows across clouds and clusters at unprecedented speed. In this environment, traditional security controls focused on static configurations and perimeter defenses are no longer sufficient. Modern security must assume that applications are always running,

Exploit Prediction Scoring System (EPSS) and Common Vulnerability Scoring System (CVSS) are two widely used scoring systems in cybersecurity, each answering a different question about vulnerabilities. EPSS tells you how likely a vulnerability is to be exploited, while CVSS tells you how bad a vulnerability is. Used together, they provide a more complete picture for

In the rapidly evolving landscape of enterprise AI, data privacy remains the single biggest barrier to entry. Organizations in finance, healthcare, and software development want the productivity gains of AI, like automated fraud detection, predictive maintenance, and intelligent code assistants, but they cannot risk exposing their intellectual property or violating data residency regulations by pooling

When a database needs to handle more data, more queries, or higher throughput, there are two fundamentally different approaches to scaling: Vertical Scaling and Horizontal Scaling. Vertical scaling means increasing the capacity of a single MongoDB server instance by adding more powerful hardware resources—more CPU cores, more RAM, faster disks, or larger storage. Horizontal scaling

Introduction Security vulnerabilities are rarely isolated incidents. In real-world systems, weaknesses tend to cluster, cascade, and compound, often stemming from the same underlying design or validation failures. As part of our research to build models that can detect and remediate vulnerabilities automatically, we analyzed the Top 25 CWEs, their scope, parent–child relationships, and correlations across