Snyk alternative for AI-written changes: AI CodeOps

Snyk is a security platform: static analysis with Snyk Code, dependency scanning with Snyk Open Source, plus containers and infrastructure as code. If you are reading this because you want a cheaper scanner, AI CodeOps is not one, and this page will say so plainly. If you are reading it because more of your code is now written by AI agents and you want control over how those changes reach main, read on.

Snyk in one paragraph

Snyk's docs call Snyk Code a developer-first SAST solution and Snyk Open Source a developer-first software composition analysis (SCA) solution with license compliance checks (Snyk Code, Snyk Open Source). It scans in the IDE, the CLI, CI pipelines and on pull requests, and with branch protection a failed pull request check stops the merge (pull request checks). As of October 2026 the Free plan covers 5 projects and 100 Snyk Code tests a month, Team starts at $25 a month for up to 10 developers, and Enterprise is priced through sales with usage credits (plans). Generating SBOMs with snyk sbom is on Enterprise plans (sbom command).

What AI CodeOps adds, and what it doesn't

Security review inside the change

In an AI CodeOps session, agents write the change and a Security Auditor reviews the diff. Findings carry a severity, file and line. Open high or critical findings block the change until someone triages them, so it never becomes a pull request with a known high finding open (quality gates). The Security-Sensitive Change workflow runs a risk analysis before the change is written and audits it after; Threat Model produces a STRIDE analysis (agents and workflows).

Control over who ships what

A code change needs an approval from someone other than the person who launched it, when the team has another approver. Policies can require approval for changes to protected paths (approvals and policies). Each change has an Ed25519-signed evidence pack with its findings, tests and approvals.

License rules from your SBOM

You record the SBOM your build already produces, in CycloneDX or SPDX, against the project. The release gate your CI calls can then deny a change whose SBOM contains a license you disallow, and denies it if there is no SBOM to check (security and SBOM).

What it does not do

AI CodeOps has no CVE scanner and no secrets scanner, and it doesn't generate SBOMs. Its Dependency Auditor reads your manifests and relies on the model's knowledge, which has a training cut-off, not a live vulnerability database. It reviews only the changes made in its own sessions, not the rest of your code.

When to keep Snyk

Almost always. In particular:

• You need known-vulnerability and dependency scanning. That is what Snyk Open Source does.
• You need SAST across all code. Snyk Code can scan every repository and pull request, whoever wrote it.
• You need container or infrastructure-as-code scanning. AI CodeOps has neither.
• You need an audited vendor. Snyk states ISO 27001:2022 certification (data handling). AI CodeOps is not certified yet.

Using both

Keep Snyk's pull request check required in branch protection. AI CodeOps opens ordinary pull requests, so every change an AI agent writes passes the AI CodeOps gate first and Snyk's check second. One note if you use Snyk Studio: Snyk's MCP server runs locally over stdio, and AI CodeOps sessions run on the platform, where they only connect to remote MCP servers (MCP servers).

Try a first session from the quickstart, or read the side-by-side AI CodeOps vs Snyk Code. For quality gates beyond security, see SonarQube alternatives.