Articles

Generative AI vs. Predictive AI: A Practical Guide for Security Professionals

Get a practical roadmap for implementing Generative and Predictive AI in cybersecurity. This guide provides decision factors, budgets, timelines, and phased plans to help you choose the right AI strategy for your organization's security needs.

Generative AI vs Predictive AI: Understanding the types of AI

Explore Generative vs. Predictive AI in cybersecurity. Learn how one creates new content for simulations while the other forecasts threats. Combine both AI types to build an adaptive defense and stay ahead of modern attacks.

The Rise of API Security: Why It Matters More Than Ever

Discover why API security is essential in the age of AI-driven development. Learn how to manage risk, ensure compliance, and empower developers with real-time, AI-powered defense to safeguard vital data.

5 Tips for Agentic Coding with Gemini CLI

Unlock secure agentic coding with Gemini CLI. Learn five tips, including using GEMINI.md for project context, integrating Snyk for security scans, and leveraging custom commands to automate your workflow.

AI TRiSM: A Comprehensive Framework for Responsible AI Implementation

Discover what AI TRiSM is, why it matters, and how it ensures trust, risk, and security in artificial intelligence. Learn key strategies to manage AI responsibly.

Package Hallucination: Impacts and Mitigation

Malicious actors can exploit errors in generative AI tools, and packages can hallucinate. Learn how to identify and mitigate package hallucination attacks with Snyk

Transforming Healthtech Security Through Automation

Explore how automation enhances cybersecurity and operational efficiency in Healthtech, ensuring robust data protection.

What Is Prompt Engineering? A Practical Guide for Developers and Teams

Learn what prompt engineering is, how it improves LLM outputs, and the tools and techniques you need to write effective, secure AI prompts.

How To Run Models (LLM) Locally with Docker

Master how to run Large Language Models (LLMs) locally with Docker. This quick-start guide is for developers who want to learn more about the process of setting up models to run locally on their laptop.

Unified Security: Protecting Applications with SAST and DAST

Discover how combining SAST and DAST provides full application security, bridging gaps in visibility and ensuring protection from code to runtime vulnerabilities.

Next-Level CI/CD: Embedding Security in Your DevOps Journey

Discover how to integrate robust security into your CI/CD pipeline to safeguard against emerging threats and ensure compliance.

Shadow AI: Unmasking the hidden risks in your Enterprise

Unmask Shadow AI's hidden enterprise risks, from data leaks and compliance woes to security gaps. Learn why it's a threat and how to implement effective governance strategies for safer AI innovation.

AI asset management: Key functions, challenges, and benefits

AI asset management refers to the application of AI and machine learning to the management of financial assets. What are the challenges of AI introduction for the financial industry?

5 Key Learnings on How to Get Started in DevSecOps

During DevSecCon’s recent community call on How to Get Started in DevSecOps, security experts from the DevSecCon community shared actionable advice, practical steps, and insights for navigating this critical field. Here are the top five takeaways from this call.

5 Best MCP Servers for Developers

Here are Snyk’s Top 5 recommendations for MCP Servers that developers will get the most value from.

11 Data Science MCP Servers for Sourcing, Analyzing, and Visualizing Data

Discover eleven MCP servers specifically engineered for data science workflows, spanning everything from dataset discovery and exploration to sophisticated mathematical visualizations.

Preventing XXE Attacks: Strategies for Secure XML Processing

Discover how to safeguard your XML processes against XXE vulnerabilities with advanced prevention techniques.

AI Inference in Cybersecurity: Real-Time Threat Detection at Scale

Discover what AI inference is, how it powers real-time decision-making in machine learning models, and why it's crucial for edge computing and business innovation.

DAST and Compliance: Bridging the Gap Between Regulation and Innovation

Discover how DAST bridges the gap between compliance and innovation, empowering teams to meet regulatory standards while accelerating secure development.

AI Model Theft: Understanding the Threat Landscape and Protective Measures

Model theft attacks occur when an attacker gains access to the model's parameters. Find out how to prevent and mitigate LLM threats and security risks.