Snyk announced Evo Agentic Development Security, a product intended to give enterprises visibility, governance, and control over AI coding agents, their tool use, and the code they generate.
Snyk announced Evo Agentic Development Security, a new offering in its AI security platform designed to govern AI coding agents, their tools, and generated code in real time.
According to Snyk’s announcement, Evo Agentic Development Security is intended to act as an “enforcement layer” for enterprise software development environments where AI agents are increasingly taking part in writing, modifying, and shipping code. The company says the product addresses risks across what it calls the “agentic development lifecycle,” including agent inputs, agent behavior, tool use, and software output.
Snyk’s launch blog, “Announcing Agentic Development Security (ADS),” says the product embeds security into AI-driven development workflows and is designed to provide visibility, governance, and control over agent activity. The company frames this as a response to a shift from AI coding assistants that suggest code to more autonomous AI agents that can perform multi-step development tasks.
On its Evo Agentic Development Security product page, Snyk says the offering focuses on three areas: validating the tools that AI agents use, governing agent behavior in real time, and securing generated code at inception.
The product page says Evo ADS can help secure “how AI agents build software” by applying controls before and during agent-driven work rather than only scanning code after it has been produced. Snyk’s materials describe this as a way to manage both the behavior of the agent and the security quality of the resulting software.
The company’s announcement also emphasizes real-time governance. Snyk says the product is intended to let organizations define and enforce policies around what agents are allowed to do, what tools they may call, and how their outputs are assessed before code reaches later stages of development.
Snyk’s positioning reflects a growing concern around AI-assisted development: as AI systems move from suggesting snippets to executing broader development tasks, security teams may need controls that cover more than traditional static analysis or dependency scanning.
The sources provided by Snyk do not include independent benchmark results or third-party customer outcomes, so the announcement should be read as a product launch and company positioning rather than evidence of measured risk reduction. However, the specific risk model Snyk describes is clear: enterprises adopting AI coding agents need ways to monitor agent activity, restrict tool access, and check generated code early in the development process.
Snyk’s launch materials also suggest that the company is extending its existing application security focus into agentic development environments. Rather than treating AI-generated code as a separate category, Snyk presents Evo ADS as part of a broader AI security platform for software teams using automated development systems.
The announcement adds to a wider shift in developer tooling, where security vendors are adapting products for workflows that include AI agents as active participants. Snyk’s Evo Agentic Development Security is aimed at organizations that want to use these agents while maintaining policies over their behavior and outputs.
For now, the available information comes from Snyk’s announcement, launch blog, and product page. Those sources say Evo ADS is built to govern AI coding agents in real time, validate their tool use, and secure generated code at the point of creation.
Snyk adds controls for AI coding agents Snyk announced Evo Agentic Development Security, a new offering in its AI security platform designed to govern AI coding agents, their tools, and generated code in real time.
The company says the product addresses risks across what it calls the “agentic development lifecycle,” including agent inputs, agent behavior, tool use, and software output.
The company frames this as a response to a shift from AI coding assistants that suggest code to more autonomous AI agents that can perform multi step development tasks.
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