Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

For over twenty years, the global security community has operated under a single, comfortable assumption: that a centralized public source could help track, analyze, and enrich the world’s software vulnerabilities at the pace the industry needed. When the National Vulnerability Database (NVD) was established, the open source vulnerability lifecycle moved at a radically different pace.

As organizations adopt AI agents to build software, security teams face a new challenge: risk is no longer introduced only through the code that gets produced. It emerges continuously through the tools agents use, the actions they take, and the code they generate. This is the problem Evo Agentic Development Security (ADS) was designed to solve. ADS secures all three layers of the agentic development system—what agents use, what they do, and what they generate.

Today, we're announcing Agentic Development Security (ADS), a new Evo solution designed for securing AI-driven software development. AI agents are now active participants in the software development process, selecting tools, executing actions across systems, and generating production-ready code at machine speed.

For years, application security teams have focused on a familiar set of questions: Is the code secure? Are the dependencies vulnerable? Is the build pipeline protected? Are issues being caught before they reach production? Agentic development adds a new question: What systems, tools, instructions, and permissions helped produce this code? AI coding agents are no longer just suggesting snippets or completing lines of code.

Finding issues is easier than ever. Triaging and fixing them is what's scarce. Through Snyk's Secure Developer Program, open source maintainers get the signal to cut through the noise and the platform to fix what matters, free for their open source projects.

An attacker republished the entire @mastra npm scope on June 17, 2026, slipping a single malicious dependency into 143 packages and counting, including @mastra/core, which pulls roughly 4 million downloads a month and has hundreds of dependent projects. The injected dependency, easy-day-js, is a dayjs lookalike whose install hook disables TLS verification, downloads a second-stage payload from a raw IP address, and runs a cross-platform cryptocurrency stealer in the background.

I've spent the better part of three years wiring AI into how my teams build and ship software. So when the news broke this week that the US government had effectively switched off an AI model, I was legitimately shocked. Not for one country. Not for one company. For everyone on the planet, all at once. Three days. That's how long Anthropic's Fable 5 and Mythos 5 models were available before the government ordered them shut off for everyone.

On the evening of June 12, 2026, Anthropic disabled access to two of its newest models, Claude Fable 5 and Claude Mythos 5, for every customer worldwide. The company did not do this because of an outage or a self-discovered flaw. It did it to comply with a US government export-control directive, received at 5:21 PM ET that day, citing national security authorities.

Most organizations spend their AI security budget on the wrong layer. The instinct is to just buy visibility to inventory the models, map the APIs, and ship a dashboard. But visibility alone won’t stop the coding agent that just pulled in a compromised MCP server. It won’t stop the production agent that’s about to forward a customer record to a place it shouldn’t go.

With code being written (& generated) faster than ever before, there is the unfortunate side effect that security vulnerabilities are also coming faster than ever before. Asking your LLM not to include security vulnerabilities in its code doesn't always work. It is becoming clear that the way software is built today, manually or with assistance, is insufficient when it comes to reliably, consistently, and provably writing secure code.