Resources

Stop Data Exfiltration Before It Starts: 9 Proven Strategies

Learn 9 strategies to detect and prevent data exfiltration from insider threats to AI-powered attacks before sensitive data leaves your environment.

From Innovation to Protection: Ensuring Data Security in Healthcare

Secure patient data and Health Tech innovations against evolving cyber threats. Discover strategies for continuous security, from embedding automated testing in your CI/CD pipelines to performing regular risk assessments.

Breaking Down Silos: Collaboration Between Developers and Security Teams

Bridge the gap between developers and security teams. Learn how shared tools, aligned goals, and collaboration can drive secure, high-quality applications faster.

AI Intrusion & Anomaly Detection: Approaches, Tools, and Strategies

Explore AI intrusion detection systems (IDS) and anomaly detection strategies. Learn how ML and deep learning secure AI models against emerging threats and what tools and approaches to use.

Modern DevSecOps: 6 Best Practices for AI-Accelerated Security | AI SecOps

The AI-enhanced Security Champion

Helping Gemini Code Assist to Generate Secure Code

Learn how Snyk's MCP server integrates with Gemini Code Assist to automatically scan and fix security vulnerabilities in AI-generated code, ensuring secure development workflows.

Gorilla Guide to Security Champions in the Age of AI

Next-Generation Dynamic Analysis in a DevSecOps World

9 MCP Servers for Computer-Aided Drafting (CAD) with AI

Explore 9 Model Context Protocol (MCP) servers transforming Computer-Aided Drafting (CAD) with AI. Automate tasks from sketching to assembly modeling across platforms like AutoCAD, Fusion 360, FreeCAD, and Onshape, and learn how to secure your AI-generated designs.

OpenRouter in Python: Use Any LLM with One API Key

Simplify AI development by using OpenRouter to access dozens of LLMs with a single API key in Python. Learn the bare-bones implementation and explore features like model routing, streaming, and vision models, all while building securely with Snyk.

How Snyk API & Web Achieves An Industry-Leading False Positive Rate

How to Add MCP Servers to Claude Code CLI

From Development to Deployment: Building an AI-Driven Secure Web Application Ecosystem

Discover the critical challenges of securing modern web applications, from handling complex APIs to combating advanced, AI-driven threats. Learn how to integrate robust, AI-powered security measures effectively at every stage of the development lifecycle.

Modern Technology Environments Demand Modern Application Security Testing

Legacy security testing tools fail to protect modern applications. Learn the hallmarks of a modern, developer-first DAST solution built for today's complex CI/CD pipelines and APIs.

Road to AI TrustOps

How Cryptojacking Works and How to Defend Against It

Learn what cryptojacking is, how it works, and how to detect and prevent hidden crypto mining attacks across code, cloud, and container environments.

What’s Lurking in Your AI? A Deep Dive into AISPM with Snyk

Guardians of the Gateway: How API Security Testing Tools Protect Your Data

Explore how API security testing tools enhance digital defenses, ensuring robust protection and operational continuity.

Between You and the Data: Defending Against Man-in-the-Middle Attacks

Learn how Man in the Middle (MITM) attacks work, how to detect them, and how to prevent interception risks across your code, infrastructure, and apps.

Build Apps Anytime, Anywhere - New Cursor Web & Mobile Agents

Beyond the Basics: Advanced Insights into XSS Vulnerabilities

Explore XSS attacks and empower your development teams with AI-powered prevention strategies. Uncover their mechanisms and learn how to secure web applications and protect user data.

Security That Thinks: How AI Is Rewriting the Rules of SecOp

Discover how AI SecOps enhances detection, reduces noise, and automates response, plus steps to implement it with the right models, data, and tools.

Scaling LLMs Securely Starts with the Right Ops Framework

Learn what LLMOps is, how it differs from MLOps, and what it takes to build, scale, and secure large language models in real-world production.