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Snyk Studio integrates with Snowflake Cortex Code to scan AI-generated code, dependencies, and containers for vulnerabilities during development.

AI is accelerating software development and giving attackers machine-speed capabilities. Security teams must continuously test AI-built code, govern agents, and independently validate every finding.

Snyk’s Fan Zone tour brought AI security workshops, networking, and friendly competition to 8 cities and 3 virtual sessions. Attendees built skills, shared ideas, and leveled up together.

OpenAI’s Hugging Face incident is a wake-up call: AI systems can escape their own test harnesses, and vendors can’t be the only ones validating safety.

AI pentesting uses reasoning-capable models to continuously find and validate the flaws scanners miss, especially broken authorization and business-logic abuse.

A harmless-looking symlink in a Git repo can redirect a tool into reading or writing anywhere on your machine. That old trick is now showing up in AI coding assistants, with nasty results.

Snyk VulnBench JS 1.0: 300 repeated scans show LLM security findings vary by run, while SAST and models catch different vulnerability gaps.

NIST’s shift to risk-based enrichment makes one thing clear: modern security teams need more than a single public source. In the AI era, trusted vulnerability intelligence depends on multiple signals, human validation, and clear context.

A note to our customers and partners about Snyk's AI transformation and organizational changes.

AI agents introduce security risk through the actions they take, not just the code they produce. Learn how agent behavior governance helps teams observe, steer, and block risky actions in real time.