Articles

5 AI Cloud Security Best Practices: A Comprehensive Guide for Securing AI Systems in the Cloud

Discover the top 5 AI cloud security best practices to protect your AI models, data, and pipelines. Learn how to secure AI systems in the cloud against emerging threats with this comprehensive guide.

What Is Threat Modeling and Why Is It Essential for DevSecOps?

Learn how continuous threat modeling strengthens DevSecOps by identifying, prioritizing, and mitigating risks across evolving code, data, and pipelines.

Accelerating Public Sector Modernization with Secure AI-Driven Migration

Learn how generative AI accelerates legacy application migration for the public sector—and how Snyk secures AI-generated code, dependencies, containers, and cloud infrastructure from code to cloud.

Your AI "Skills" Are the New Agentic Attack Surface

As AI moves beyond simple chat to autonomous execution, the skills powering these agents have emerged as a dangerous new attack surface. Learn how to protect your organization from malicious AI agent tools while maintaining development velocity in the age of agentic workflows.

Debunking the Top 5 Myths About DAST

Modern Dynamic Application Security Testing (DAST) has evolved far beyond its outdated reputation for being slow or noisy. This guide debunks five common myths, demonstrating how AI-driven DAST provides fast, automated runtime security that catches critical vulnerabilities static analysis often misses.

Top 8 Claude Skills for Finance and Quantitative Developers

Quantitative finance is evolving as algorithmic traders shift from AI skepticism to practical automation using Claude Skills. Learn how to leverage the latest Claude Skills and security best practices to reclaim mental bandwidth for high-level financial judgment.

Building Secure MCP Servers: A Developer's Guide to Avoiding Critical Vulnerabilities

Building Safer AI Agents with Structured Outputs

Learn how structured outputs help developers build safer, more reliable AI agents by enforcing strict schemas during token generation. Discover the essential frameworks and security tools needed to move your AI agents to an enforcement-based production environment.

What Is Toxic Flow Analysis in Cybersecurity? Framework, Identification Techniques & Implementation

Toxic Flow Analysis maps how sensitive data moves across systems to uncover hidden risks, strengthen defenses, and improve security posture.

4 Reasons Why Dynamic Security Testing Is Critical For All Your Assets

Attackers don't just target your crown jewels; they look for the weakest link in your entire application footprint. Limiting dynamic security testing to tier-one apps leaves dangerous blind spots across forgotten APIs and internal tools. Discover why universal DAST is critical for modern risk management and how it helps teams uncover hidden vulnerabilities before they become entry points for a breach.

SAST for SQL Injection Detection: A Complete Guide

Static Application Security Testing (SAST) is a cornerstone of a proactive defense against SQL injection (SQLi). Snyk Code uses the power of SAST to detect SQL injection vulnerabilities in source code, prevent attacks early, & strengthen application security before deployment.

OWASP AI Exchange: a practical, “one-stop” guide to securing AI (not just GenAI)

The OWASP AI Exchange is a comprehensive open source guide for securing all AI systems, bridging the gap between traditional AppSec and modern machine learning threats. Use this practical resource to implement the G.U.A.R.D. starter plan and scale your AI security program with confidence.

Gemini Nano Banana Cheat Sheet for JavaScript Developers

Explore this cheat sheet for JavaScript/TypeScript developers on integrating Google's Gemini Nano Banana model. Master the AI SDK, prompt engineering, image generation, Data URL conversion, and security best practices with Snyk Studio.

Why AI Supply Chain Risk Has Outgrown the SBOM Model

AI supply chain risk extends beyond the repo. Learn why visibility across code and developer environments is key to governing AI safely.

How Claude Code Is Raising the Ceiling of Intelligence

Anthropic's Claude Code is evolving into a customizable agent framework. Learn about 7 new features: extended thinking, tool use, MCP, memory, and secure execution.

Top CI/CD Pipeline Security Best Practices for AI-Powered Development

Fortify your AI development lifecycle. Learn top CI/CD security best practices to protect against prompt injection, data poisoning, and model inversion from code to cloud.

From SBOM to AI-BOM: Rethinking Visibility in AI-Native Systems

AI supply chains move too fast for SBOMs. Learn why AI-BOM is becoming the foundation for AI security and governance.

From Gatekeeper to Guardrail: Embracing the Role of Governance for the AI Era

AI code assistants demand a new AppSec governance model. Shift from late-stage "gatekeepers" to real-time "guardrails" with Policy-as-Code and developer-first security. Learn how to secure Al-generated code from inception.

What Users Want When Vibe Coding

Vibe coding promises speed but delivers tech debt & security risks. Developers need guardrails, not just velocity, to avoid production disasters, cost explosions, and skill erosion. Learn what users truly want for AI-assisted coding.

What Is Threat Modeling and Why Is It Essential for DevSecOps?

Learn how continuous threat modeling strengthens DevSecOps by identifying, prioritizing, and mitigating risks across evolving code, data, and pipelines.