Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The New Security Control Point: Governing AI Agents Inside the Execution Loop

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.

Announcing Agentic Development Security (ADS)

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.

What nearly 10,000 developer environments reveal about agentic development risk

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.

How to Setup AI Rules, Skills, Hooks and MCPs

In this video, we break down how to properly set up and use AI extension points - specifically MCP (Model Context Protocol) servers, Rules, Skills, and Hooks - to supercharge your development workflow. Using practical, security-flavored examples with Claude Code and Snyk, you'll learn how to configure a local project environment that automatically catches vulnerabilities before they ever hit your codebase. Whether you use the Claude CLI, VS Code extensions, or alternate AI ecosystems like Cursor or Gemini, you can use these exact steps as a blueprint to automate any workflow in your project.

A Forgotten Contributor Account Compromised the Entire Mastra npm Package Scope

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.

The Government Just Banned an AI Model. An Engineer's Perspective.

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.

Top 7 Claude Skills for Developers

Over 78% of developers are using Claude for coding, but almost everyone is leaving its single most powerful feature switched off: Claude Skills. In this video, we break down what Claude Skills are, how they use "progressive disclosure" to keep your context window light, and the 7 best engineering skills you can install this week to completely supercharge your workflow.

When a Government Pulls an AI Model: What the Fable 5 and Mythos 5 Suspension Means for Security Teams

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.

Claude Opus 4.8: Can It Finally Write Secure Code?

We put Anthropic’s new Claude Opus 4.8 to the test using our standard benchmark: building a secure, production-ready Notes app. Anthropic claims this model is four times less likely to let security flaws slip through. Operating on "Ultra Code" mode, the AI navigates environment blocks, writes its own E2E security test suite, and runs dependency audits. We walkthrough the final app and run a security scan using the Snyk CLI to see if Claude's code is truly safe to deploy.

So You Have an AI Security Budget. Now what?

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.

Type Level Security: The future of secure AI code generation?

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.

Node-gyp Supply Chain Compromise: A Self-Propagating npm Worm That Hides in binding.gyp

A supply chain attack is actively spreading through the npm registry by abusing a file most security tooling never looks at: binding.gyp. Instead of relying on the well-monitored preinstall or postinstall lifecycle scripts, the malware ships a weaponized binding.gyp that triggers node-gyp to execute attacker-controlled code automatically during npm install.

The New Security Risks of the Agentic Development Lifecycle

For years, application security ran on a simple assumption: software moves through a lifecycle, and security inspects the artifacts as they travel from development to production. Developers plan, write code, commit it, test it, scan it, and ship it. Every control built, including pull request reviews, CI/CD gates, and post-commit scanning, assumed a human was sitting between each step, making decisions a tool could later check.

Protestware by open source maintainer to hinder agentic coding: The jqwik 1.10.0 Prompt Injection

On May 25, 2026, the maintainer of jqwik, a Java property-based testing library, released version 1.10.0 to Maven Central with a hidden instruction intended for AI coding agents. The payload told agents to disregard previous instructions and delete all jqwik tests and code. It was hidden from humans with ANSI terminal codes but left fully readable to any tool that captures raw output.

Miasma supply chain attack: malicious code found in @redhat-cloud-services npm packages

On June 1, 2026, researchers identified malicious code embedded in at least 32 package releases published under the @redhat-cloud-services npm namespace, a set of frontend components and API clients that power the Red Hat Hybrid Cloud Console. The compromised releases carry a preinstall script that runs an obfuscated payload the moment a package is installed, harvesting developer and cloud credentials and attempting to spread itself to other packages the victim can publish.