Semgrep for AI Agent Security: Features, Pricing, and Alternatives

Semgrep has positioned itself as a security scanning tool designed for the age of AI-assisted development, using static analysis to catch vulnerabilities in code before they reach production.

While Semgrep excels at code security scanning, enterprises building agentic systems need comprehensive authentication and authorization—which is where WorkOS provides the enterprise-grade foundation that AI agents require.

What is Semgrep?

Semgrep, developed by r2c (now Semgrep Inc.), is a static application security testing (SAST) platform that has evolved to address the challenges introduced by AI-generated code.

Originally launched as an open-source code analysis engine based on pattern matching, Semgrep expanded into the agentic-security space with Semgrep Assistant, a product that analyzes, triages, and proposes fixes for vulnerabilities in both human- and AI-generated code.

Unlike products focused on authentication, guardrails, or policy enforcement, Semgrep focuses on what it does best: scanning code artifacts. Its model combines rule-driven static analysis with LLM-assisted triage that reduces noise and highlights high-confidence vulnerabilities. AI coding assistants generate code far faster than humans can review it; Semgrep’s bet is that accurate, iterative scanning can close that gap.

Semgrep is used by companies such as Lyft, Dropbox, Snowflake, HashiCorp, Figma, and Vanta. But it’s important to understand the boundary: Semgrep analyzes the code your agents produce. It does not authenticate agents, enforce authorization boundaries, or provide identity infrastructure.

Key Features and Capabilities

AI-Powered Vulnerability Triage

The Semgrep Assistant significantly improves the signal-to-noise ratio compared to traditional SAST tools. Instead of flooding developers with false positives, it uses LLM reasoning to add context to findings, helping security teams focus on real issues. When Semgrep flags an injection vector, insecure deserialization, or a flawed auth check, developers can generally trust it deserves attention.

Semgrep integrates into developer workflows through CI pipelines, PR checks, and IDE support. As AI coding assistants propose changes, Semgrep scans those changes early—catching problems before they land in a pull request or hit production.

Automated Code Fix Suggestions

Semgrep Assistant proposes secure remediation snippets tailored to each language and framework. It does not automatically apply changes to your repository, but it provides accurate, context-aware fix suggestions for common classes of vulnerabilities. These fixes differ per language—Python, Go, TypeScript, Java, Solidity, and others—and the platform understands these nuances.

Semgrep MCP Server (Official)

Semgrep maintains an official, open-source Model Context Protocol (MCP) Server, documented here:

https://semgrep.dev/docs/mcp

This allows LLM agents and AI coding tools to:

• request targeted scans

• run rules on-demand

• retrieve structured findings

• integrate Semgrep’s rule engine into chain-of-thought workflows

This transforms Semgrep from a passive scanner into an actionable security endpoint for AI agents. The server is currently marked beta, but it is real, documented, maintained, and functional.

Code Security at AI Velocity

The fundamental problem Semgrep tackles is velocity. A developer using Claude Code or GitHub Copilot may generate thousands of lines of code per day—far beyond what human reviewers can meaningfully inspect.

Semgrep handles this by:

• scanning early (IDE or PR time)

• scanning often (incremental checks)

• tracing dataflow between files

• preventing “buried-in-the-diff” security regressions

Semgrep provides interfile and dataflow analysis strong enough for most modern application stacks, though it stops short of heavyweight symbolic execution or full taint-tracking engines used by legacy enterprise SAST platforms.

But again, here’s the boundary: Semgrep analyzes the code your agents write. It does not authenticate or authorize those agents, cannot enforce IAM boundaries, and does not supply enterprise SSO, audit logs, or compliance infrastructure.

Pricing and Plans

Community Edition (Free):

Includes the open-source CLI, rule engine, and basic scanning. Good for small teams or manual security review.

Teams ($40/month per contributor):

Adds Semgrep Assistant, AI-powered triage, advanced rulepacks, GitHub/GitLab/Bitbucket integration, and quality-of-life features. Pricing is per contributor (developers making commits).

Enterprise (Custom):

Includes SSO, advanced compliance features, dedicated support, SLAs, and tailored onboarding. Pricing varies but typically falls in the mid-five-figure annual range for midsize organizations.

Semgrep typically pays for itself if it prevents even a single critical vulnerability—especially relevant when AI agents produce a significant portion of your codebase.

Semgrep vs. WorkOS

These products operate in entirely different layers of the security stack.

What Semgrep Provides

Semgrep is a static analysis platform that:

• scans code for vulnerabilities

• triages findings with LLM context

• proposes fixes

• integrates with AI coding agents through its MCP server

Semgrep is extremely useful in development workflows and particularly valuable for teams using AI coding assistants.

It does not provide:

• authentication

• authorization

• identity federation

• access control

• audit trails

• compliance infrastructure

Why WorkOS Is the Enterprise-Grade Authentication Platform

WorkOS provides what production AI agents and enterprise customers require:

• SAML, OAuth, and OIDC SSO

• MFA

• enterprise directory sync

• RBAC and fine-grained authorization

• audit logging

• customer admin portals

• 99.99% uptime SLA

• SOC 2, HIPAA, GDPR readiness

• SDKs for major languages (Node, Go, Python, Ruby, etc.)

Semgrep scans the code the agent writes.

WorkOS secures the agent itself.

If your AI agent must authenticate into customer systems or operate within enterprise environments, Semgrep cannot solve that problem—WorkOS can.

The Right Choice for Enterprise Teams

Both tools matter, but for completely different reasons.

For teams building enterprise-facing AI agents:

WorkOS is essential. You need authentication, authorization, provisioning, deprovisioning, audit logs, and enterprise identity integration.

For teams using AI coding assistants:

Semgrep is a high-value SAST layer. It reduces noise, accelerates remediation, and ensures AI-generated code is reviewed with consistent quality.

For production deployments:

WorkOS ensures agents only access the right resources, logs actions for compliance, and satisfies enterprise SSO requirements.

Semgrep ensures the code those agents produce is secure.

Final Thoughts

Semgrep made a smart, narrowly focused bet: securing AI-generated code through static analysis and LLM-powered triage. It’s a high-impact development tool with real, measurable value.

But it is not identity infrastructure.

It is not an auth platform.

It does not secure agent behavior.

It does not provide SSO or authorization boundaries.

WorkOS provides the authentication and authorization foundation enterprises require. When your AI agents must operate in production, access customer systems, and meet compliance obligations, WorkOS is the platform that makes those deployments viable.

Semgrep scans code artifacts.

WorkOS secures the agents themselves.

For enterprise AI systems intended for real-world deployment, WorkOS is the authentication and authorization foundation you actually need.