Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Shadow AI refers to the unauthorized or unmanaged use of AI tools, models, frameworks, APIs or platforms within an organization, operating outside established governance frameworks. While employees may adopt these AI tools with good intentions, seeking to enhance productivity or solve problems more efficiently, the lack of oversight creates significant security, compliance, and operational risks.

Kubernetes security refers to practices, tools, and configurations that protect Kubernetes clusters and workloads from unauthorized access, vulnerabilities, and runtime threats. It involves securing all components of the Kubernetes environment—including the control plane, worker nodes, pods, container images, networking, and storage.

MCP adoption is surging across industries, fundamentally reshaping how systems connect to AI models. By establishing a universal protocol for data exchange, MCP simplifies integration complexity, empowering developers to build sophisticated AI capabilities in a fraction of the traditional development time. However, this streamlined connectivity to AI tools introduces significant security risks.

AI red teaming is the process of simulating adversarial behavior to test the safety, security, and robustness of artificial intelligence systems. It draws inspiration from traditional cybersecurity red teaming (where ethical hackers emulate real attackers to expose flaws) but applies that mindset to machine learning models, data pipelines, and the broader AI stack.

SAST tools automatically scan the source code of an application. The goal is to identify vulnerabilities before deployment. SAST tools perform white-box testing, which involves analyzing the code based on inside knowledge of the application. SAST offers granularity in detecting vulnerabilities, providing an assessment down to the line of code.

The OWASP Top 10 is a security research project that outlines the ten most critical security risks to web applications. Published by the Open Worldwide Application Security Project (OWASP), it serves as a widely recognized benchmark for web application security. The list is compiled from data gathered by security experts and organizations worldwide, based on the prevalence, detectability, and impact of various vulnerabilities.

Application security testing (AST) is the process of identifying and fixing security vulnerabilities in software applications. It ensures that applications are protected against threats such as unauthorized access, data breaches, and code manipulation. The application layer continues to be the most attacked and hardest to defend in the enterprise software stack.

The Open Web Application Security Project (OWASP), is an online community that produces free, publicly available articles, methodologies, documentation, tools, and technologies in the field of web application security. Open source components have become an integral part of software development. According to Mend’s Risk Report, 96.8% of developers rely on open source components.

Static application security testing (SAST) has matured from a gate-at-the-end to a developer-first discipline. Forrester’s Static Application Security Testing (SAST) 2025 landscape report highlights why: attack volume is rising, code is released at least monthly in one in four teams, and AI generated code is flooding pipelines with even more code to secure. The tools that succeed are those that shorten mean time to remediate (MTTR) while fitting the way modern teams build.

DAST is a security tool that attempts to penetrate an application from the outside by checking its exposed interfaces for vulnerabilities and flaws. Sometimes called a web application vulnerability scanner, it is a type of black-box security test. It looks for security vulnerabilities by simulating external attacks on an application while the application is running.