Semgrep raised a $100M Series D in February 2025, led by Menlo Ventures, with participation from Felicis Ventures, Harpoon Ventures, Lightspeed Venture Partners, Redpoint Ventures, and Sequoia Capital.

Semgrep raised a $53M Series C in April 2023. Earlier rounds include a Series B and Series A, bringing total capital raised across all rounds to $204M.

Semgrep is a code security platform that scans software for vulnerabilities during development, identifying issues before they reach production.

The platform is built on an open-source pattern-matching engine that parses the abstract syntax tree of more than 30 programming languages. Instead of scanning text with regular expressions, Semgrep parses code structure and traces how data flows through a program across multiple files and functions.

The commercial platform, built on top of the open-source engine, ships as four interconnected products.

Semgrep Code is the SAST layer. Developers can run a scan locally from the terminal, or it can trigger automatically when a pull request is opened on GitHub, GitLab, or Bitbucket. Findings appear as inline comments in the PR, with a link to a web dashboard where the security team can triage, assign, or auto-fix the issue. The Pro Engine adds cross-file taint analysis, which can follow user-supplied data from where it enters the application to where it might be executed, including paths that span dozens of files.

Semgrep Supply Chain handles open-source dependency risk. Rather than flagging every CVE in every imported package, it traces whether the vulnerable function in that dependency is actually called by the application's code. Only reachable vulnerabilities are surfaced, reducing the volume of findings typical of a software composition analysis (SCA) tool. The same reachability graph is used for malicious-package detection and license compliance checks.

Semgrep Secrets scans for hard-coded credentials (API keys, tokens, passwords) using a combination of entropy analysis and semantic context. It can detect a secret stored in a variable with a custom name that a regex-only tool would miss, and it validates whether the detected credential is live before raising an alert.

Semgrep Assistant is the AI layer across the three scanners. It auto-triages findings on day one, suppressing roughly 20% of SAST results it classifies as false positives, improving to around 40% suppression after a week as it learns the codebase. A Memories feature lets users record triage decisions that the model then re-applies across repositories, so the same false positive is not manually reviewed twice. For findings that are confirmed, Assistant generates remediation guidance and can open a PR with a suggested code fix.

The platform integrates with VS Code and JetBrains IDEs, GitHub, GitLab, Bitbucket, Azure DevOps, and major CI systems including Jenkins. An MCP server released in 2025 lets AI coding assistants call Semgrep directly, so when a developer uses an LLM to write code, Semgrep can scan the output in real time before it is committed.

Semgrep sells to enterprise security and engineering teams via a B2B SaaS model priced per contributing developer per month.

The per-contributor structure ties contract value to the size of the engineering organization rather than the number of security staff using the dashboard. As a customer's headcount grows, Semgrep's ARR from that account grows automatically, without a renewal negotiation.

The open-source Semgrep CE engine functions as the top of the funnel. Developers discover it, run it locally, and introduce it to their teams. This community-led adoption reduces the cost of initial sales motion and often brings Semgrep into an account at the individual developer level before a formal procurement conversation with a security team.

The commercial tiers add functionality above the free engine: the Pro Engine for cross-file analysis, Supply Chain for SCA, Secrets detection, and Assistant for AI triage and remediation. Each provides an expansion surface within an existing account; a customer that starts with Code can add Supply Chain or Secrets without switching vendors.

The AI features create a consumption-based upsell dynamic. Assistant's triage memories, autofix patches, and the MCP server integration are available in higher-tier plans, allowing Semgrep to expand ARPU as customers adopt more of the AI workflow rather than only the scanning engine.

Gross margins in this model are high relative to traditional AppSec vendors because the scanning engine runs in the customer's own CI environment, and Semgrep does not need to ingest or store full codebases. Only the code snippet around a finding is sent to OpenAI for AI-powered analysis, which reduces enterprise concerns about intellectual property exposure.

The go-to-market motion is primarily direct enterprise sales, with the open-source community as a continuous source of inbound pipeline. Managed Scanning, which handles CI configuration on behalf of customers without mature DevOps pipelines, lowers the barrier for mid-market accounts that would otherwise require significant setup time before seeing value.

The most structurally threatening competitive dynamic for Semgrep is the bundling of security scanning into the platforms developers already use.

GitHub Advanced Security, powered by CodeQL, is embedded in GitHub pull requests and offers free scanning for open-source repositories. It competes directly with Semgrep Code for the same PR-comment workflow, though enterprise pricing above $50 per developer per month and limited coverage of infrastructure-as-code have slowed adoption. GitLab's Ultimate tier packages the open-source Semgrep engine as its built-in SAST scanner, which validates Semgrep's technical approach and creates a no-incremental-cost alternative for GitLab customers.

AWS launched Inspector Code Security at re:Inforce 2025, scanning code, IaC, and open-source dependencies inside AWS pipelines. For cloud-native companies that run their entire development workflow inside AWS, this creates a credible zero-incremental-cost alternative to a standalone Semgrep subscription. Google and Microsoft are moving in similar directions, with AI-assisted code review moving toward a standard feature of their developer platforms rather than a separate purchase.

Snyk, Checkmarx, Veracode, and Sonar compete for the same enterprise AppSec budget with broader product portfolios.

Snyk has the highest developer mindshare in the SAST and SCA evaluation process, with a large vulnerability database, deep IDE integrations, and coverage across containers and IaC in addition to code and open-source dependencies. Its weakness relative to Semgrep is scan speed and noise, Snyk surfaces more findings, which increases triage workload for security teams. SonarQube holds the largest share of SAST evaluations overall, with a long-standing presence in continuous code quality workflows that predates the modern AppSec framing. Checkmarx is positioning its Checkmarx One platform around unified application security posture management (ASPM), adding AI-powered query building and PR-native remediation to compete with Semgrep's Assistant features.

These vendors are converging on the same product surface area, a single platform covering SAST, SCA, secrets, IaC, and container security with AI-assisted triage, which narrows Semgrep's differentiation on scan accuracy and developer experience.

A cluster of newer entrants is attacking from below on price and from above on AI capability.

Aikido and Qwiet AI position as leaner, faster alternatives to the full-stack incumbents, often leading with AI-native detection rather than rule-based scanning. DeepSource's Globstar project and the Opengrep fork of Semgrep's own open-source engine represent a more direct threat: if the community forks and maintains a permissively licensed version of the core engine, Semgrep's ability to monetize the open-source funnel depends on the commercial Pro Engine and AI features remaining meaningfully ahead of what the fork can replicate.

Semgrep launched as a pure SAST tool and has added Supply Chain for SCA and Secrets detection, expanding its addressable market from the roughly $2-3B SAST segment into a combined SAST, SCA, and secrets market estimated at $6-7B.

The next expansion is into business logic vulnerabilities, the class of bugs like insecure direct object references (IDORs) and multi-step authorization flaws that traditional static analysis cannot find because they require understanding application intent, not just code patterns. Semgrep's hybrid deterministic-plus-LLM engine, in private beta as of late 2025, targets this category. Budget for finding these vulnerabilities has historically gone to manual penetration testing and bug bounty programs, creating a new spending pool rather than reallocating from existing AppSec tools.

The multimodal AppSec engine announced at Semgrep Secure 2026 pairs code parsing with LLM reasoning to target near-zero false positives for AI-generated code. As developers increasingly use tools like GitHub Copilot and Cursor to write large portions of their codebases, the security properties of that code are opaque in ways that traditional rule-based scanners handle poorly, creating a category of demand that Semgrep can address ahead of incumbents.

Semgrep's open-source engine has historically concentrated adoption among security-forward engineering teams at larger technology companies. The Series D capital is directed in part toward expanding into mid-market accounts and regulated industries like fintech that have strong compliance requirements but less mature DevSecOps infrastructure.

Managed Scanning removes the CI configuration burden that has historically blocked mid-market adoption. Rather than requiring a customer to instrument their own pipelines, Semgrep handles the setup, lowering the time-to-first-finding from weeks to hours for teams without dedicated platform engineering resources.

The MCP server integration opens a different expansion path: selling to platform engineering groups and AI tooling buyers rather than only to security teams. As enterprise developers adopt AI coding assistants at scale, the MCP server positions Semgrep as a safety layer that runs automatically inside those workflows, creating a procurement motion that bypasses the traditional security-team sales cycle.

Semgrep's revenue base is concentrated in North America, with the Series D explicitly earmarked for international go-to-market expansion. European enterprises face increasing regulatory pressure around software security under frameworks like the EU Cyber Resilience Act, which mandates security testing throughout the software development lifecycle, creating a compliance-driven demand signal that maps to Semgrep's product.

The open-source community is global, with developers in Europe and Asia-Pacific running Semgrep CE in their local pipelines. Converting that existing community adoption into commercial relationships in new geographies follows the same playbook that worked in North America, with regulatory pressure accelerating the enterprise sales motion in markets where compliance requirements are becoming mandatory rather than aspirational.

Open-source commoditization: Semgrep's commercial moat depends on the Pro Engine and AI features maintaining a measurable lead over what the open-source Semgrep CE engine, and community forks like Opengrep, can replicate at no cost. If the performance gap between the free and paid engines narrows, the developer community that currently feeds Semgrep's enterprise pipeline has less incentive to convert to paid plans, and the top-of-funnel advantage that differentiates Semgrep from traditional AppSec vendors weakens.

Platform bundling: GitHub, GitLab, AWS, and Google are embedding code security scanning into platforms where developers already work, at zero or near-zero marginal cost to the customer. As bundled scanners improve in accuracy and coverage, the incremental value of a standalone Semgrep subscription becomes harder to defend for accounts already paying for GitHub Advanced Security or AWS Inspector under broader platform contracts.

AI false-positive arms race: Semgrep's core value proposition to security teams is high signal and low noise; the Pro Engine and Assistant are designed to surface fewer, more accurate findings than competitors. As Snyk, Checkmarx, and newer AI-native entrants invest in LLM-powered triage and remediation, the noise-reduction advantage Semgrep cites can converge into baseline functionality across vendors rather than remaining a durable differentiator.