Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Secure at Inception: Announcing the Snyk Studio Integration for Snowflake Cortex Code

Building on our initial partnership that brought Snyk’s security intelligence into the Snowflake AI Data Cloud, we are taking the next step in securing the future of data-driven development. This new collaboration integrates Snyk Studio directly with Snowflake Cortex Code, ensuring that as organizations move their application logic to where their data lives, security remains an inherent part of the process rather than a secondary hurdle. Play Video: YouTube video 1.

The Attacker Never Sleeps, Neither Can Your Testing

A few months ago, I wrote that AI is building your attack surface faster than you can test it. I stand by every word I wrote then. But in the months since, after more than a hundred conversations with CISOs, CIOs, and CTOs across nearly every industry and geography, I've watched the picture get sharper, and a lot more urgent. The attack surface was only half the story, because the attacker profile has changed too.

The Generator Can't Be the Validator: What OpenAI's Hugging Face Incident Proves About AI Security

Every so often, an industry gets a moment that quietly redraws where the line is — not because anything was said, but because something was proven. AI security had one of those moments last week, and it's worth being direct about that before getting into the details: this wasn't an incremental data point. It was the moment a risk that security and safety researchers had described in theory for years showed up, fully formed, in a disclosed incident report.

What Is AI Pentesting and How Does It Works?

AI pentesting (AI penetration testing) is the use of reasoning-capable AI models to autonomously find, exploit, and validate security vulnerabilities in running applications — especially the context-dependent flaws, such as broken authorization and business-logic abuse, that traditional scanners cannot detect.

OpenAI's Sol, Terra, Luna Explained: Which One Should You Use?

-OpenAI has completely overhauled its model naming system with the release of GPT-5.6, introducing three distinct tiers: Sol, Terra, and Luna. In this video, we put OpenAI's new flagship model, GPT-5.6 Sol, to the ultimate test. Using the Codex extension in VS Code, we throw our classic "Build me a secure notes app or I get fired" prompt at Sol. Watch as we break down the pricing and reasoning differences of the new tiers, run a full security audit using Snyk, and see if Sol's $5/$30 price tag is truly production-ready or if a small local CSRF bug gets us "fired" first.

Why You Must Still Review AI Code

In this video, we break down why skipping code reviews is a massive mistake that will ultimately slow you down, leave you vulnerable, and compromise your system's accountability. We dive into three concrete reasons why reviewing AI-generated pull requests actually makes you a faster, safer developer, including a real-world story of a production bug caught in under 90 seconds. Resources Chapters.

Symlinks Are Still Scary (And Yes, You Can Commit Them to Git)

Here's a genuinely unsettling way to lose control of your laptop in 2026. You clone a normal-looking repo, ask your AI coding assistant to "set it up," and it writes an attacker's SSH key into your ~/.ssh/authorized_keys -- without ever really telling you that's what it did. No memory corruption, no zero-day, nothing clever. Just a file in the repo that wasn't the file it claimed to be. That attack is real, it's this week's news, and I'll walk through it. But the trick underneath is decades old.