Agentic coding tools are moving from “interesting demo” to “active developer”, and the security implication is blunt: if no-one governs what the agent can see, build, and do, then governance becomes theoretical—and risk becomes operational.
Snyk announced the launch of its Agent Security solution and the general availability of Snyk Evo AI-SPM, positioning both as enforcement layers for the full AI lifecycle—from when agents are introduced into software to how they behave during production executiion.
Snyk’s argument is that enterprises thought they “had AI under control”, yet rapidly discovered a governance gap.
In Snyk’s 2026 State of Agentic AI Adoption reporting (as described in the announcement), for every deployed AI model, organisations introduce nearly three times as many untracked software components—and early checks can reveal ungoverned agentic components that bypass existing security stacks.
That mirrors a wider third-party pattern: agentic AI is advancing quickly, but safe scaling depends on orchestration, visibility, and controls. For instance, a Dynatrace survey reported that about half of agentic AI projects remain stuck at pilot stage, with security/privacy concerns and the challenge of managing agents at scale cited as key barriers.
Snyk’s countermeasure is to convert plain-English policy into machine-enforceable guardrails that agents must pass through—so governance is not a checklist, but a control plane.
The proposed mechanics are threefold: a Discovery Agent to map a “code-first” attack surface and generate a live AI-BOM; a Risk Intelligence Agent to enrich findings with metadata and risk signals; and a Policy Agent to turn governance intent into CI-pipeline execution controls.
"Agentic architectures turn governance into a software supply chain problem," said Manoj Nair, chief innovation officer at Snyk. "Our value is confirming which findings are real and exploitable, using ground truth data from a decade of enterprise deployment that no AI model can produce alone. Claude finds. Snyk confirms. The agent fixes only what's real."
Crucially, Snyk emphasises lifecycle coverage in three phases:
- Environment: agent scan to secure the tools agents rely on (e.g., MCP servers and agent skills).
- Artifact: “Snyk Studio” to enforce validation within CI/CD as code is produced.
- Behavior: “Agent Guard” to enforce rules in real time during the development loop and stop destructive commands.
Beyond development, Snyk also highlights securing AI-native runtime patterns (including authorisation and business-logic classes such as BOLA/IDOR) and agentic red teaming to simulate multi-turn attack flows before weaknesses reach production.
The next security battleground is not “prompt safety” alone—it is agent governance as software supply-chain enforcement. When agents can modify code and trigger actions at machine speed, the only sustainable approach is continuous policy enforcement across the lifecycle, with evidence-backed visibility.
