Endor Labs raised a $93 million Series B in April 2025, led by DFJ Growth, with participation from Salesforce Ventures, Lightspeed Venture Partners, Coatue, Dell Technologies Capital, Section 32, Citi Ventures, and Sierra Ventures.

Before the Series B, the company raised a Series A in August 2023.

Citi Ventures made a separate strategic investment in July 2024, outside the formal round cadence.

Total funding raised across all rounds is $188 million.

Endor Labs provides an application security platform integrated with a team's source-code manager, CI/CD pipelines, and developer IDEs. It identifies open-source packages and AI-generated lines of code that introduce application risk, then provides a remediation path designed to be both fast and safe.

The primary capability is reachability-based software composition analysis (SCA). When Endor scans a repository, it builds a language-specific static call graph that maps which functions in the application call into which functions inside its dependencies, down to the specific vulnerable method. If the vulnerable method is never invoked by the running application, the alert is suppressed entirely.

This approach removes roughly 80% of the noise that traditional SCA tools generate, where every CVE in every transitive dependency triggers an alert regardless of whether the vulnerable code path is ever executed.

Each finding is tagged as Reachable, Potentially Reachable, or Unreachable, allowing a security engineer to sort genuinely exploitable issues from the long tail of theoretical ones.

Alongside SCA, Endor ships an AI-powered static application security testing (SAST) engine that orchestrates multiple specialized AI agents in sequence. One agent parses syntax, a second traces data flows, a third reasons about business logic, and a fourth proposes a ready-to-apply patch. The output lands as a pull-request comment that includes a true/false-positive verdict, the reasoning chain, and a diff the developer can apply in one click.

This multi-agent architecture identifies logic-level flaws, such as broken access control, that signature-based SAST tools miss, and it reduces false positives by up to 95% in pilot deployments.

For teams that cannot upgrade a vulnerable dependency without breaking their build, Endor offers back-ported patches distributed through its own package repository. These patches are cryptographically signed, and all diffs, build steps, and logs are published publicly so security teams can audit what changed.

The newest surface is AURI, a lightweight daemon that plugs into AI coding assistants like Cursor, Claude, and GitHub Copilot, as well as VS Code directly. AURI analyzes code as it is generated on the developer's laptop, cross-checks it against Endor's reachability engine, and surfaces an inline warning or quick-fix before the code is committed to a repository.

AURI is free for individual developers, seeding adoption at the point where AI-generated code is written rather than waiting for it to appear in a security scan days later.

Endor Labs sells to enterprise engineering and security teams on a B2B subscription model. Pricing is structured around deployment scope, number of developers, repositories, or applications covered, rather than per-seat licensing, which ties contract value to the risk footprint the platform is managing.

The go-to-market motion combines top-down enterprise sales with bottom-up developer adoption. AURI, a free tool for individual developers using AI coding assistants, serves as the bottom-up entry point: it builds familiarity with Endor's reachability engine among engineers who can later advocate for the platform inside their organizations.

Enterprise deals typically start with the SCA and SAST modules and expand as teams add secrets detection, container scanning, malicious-package detection, SBOM generation, and artifact signing. Each added module can replace a point tool that previously required a separate vendor relationship and budget line.

The 166% net revenue retention rate tracks this expansion dynamic: the initial contract is rarely the ceiling, because each new module Endor adds is a substitute for a capability the customer is already paying for elsewhere.

Distribution is reinforced by integrations with GitHub Advanced Security and Microsoft Defender, which reduce procurement friction. A security team already operating inside the Microsoft ecosystem can enable Endor's SCA engine without a separate procurement process, lowering the barrier to a first deployment and accelerating the land phase of the land-and-expand motion.

The platform is cloud SaaS by default, with a self-hosted option for customers with strict data residency requirements. Once the call-graph infrastructure is in place, the marginal cost of serving additional repositories or scan volume is low. This supports a consumption-led expansion model in which scan volume and module breadth increase together as customers consolidate more of their AppSec spend onto the platform.

The application security market is consolidating around platforms that combine SCA, SAST, and software supply chain management into a single workflow, driven by higher open-source dependency volume, increased AI-generated code, and regulatory mandates such as the U.S. Executive Order 14028 SBOM requirements and the EU Cyber Resilience Act. In that context, Endor Labs competes across three categories.

Snyk is the closest analog, a developer-first AppSec platform with a large vulnerability database, extensive IDE and CI integrations, and a product-led growth motion that has driven it past $400M in estimated ARR. Snyk has expanded into AI-assisted remediation through acquisition and was named a leader in the 2025 Gartner Magic Quadrant for Application Security Testing.

Competition with Snyk centers on noise reduction and remediation quality. Snyk surfaces more findings, while Endor Labs states that reachability-based triage makes its findings more actionable. Checkmarx and Veracode compete in the same enterprise SAST and SCA space, typically selling to larger organizations through longer procurement cycles and offering deeper compliance reporting capabilities.

GitHub Advanced Security, backed by Microsoft, is the most structurally threatening competitor because it is embedded directly into the platform where many developers work. Microsoft bundles code scanning, secret scanning, and Dependabot into GitHub at a price point that standalone vendors have difficulty undercutting, and it is progressively integrating third-party engines, including Endor Labs' own SCA engine, into Microsoft Defender as a CNAPP upsell.

This creates a dynamic where Endor Labs is both a Microsoft distribution partner and a competitor to GitHub's native security features. The partnership increases Endor's reach into the GitHub ecosystem while also making it easier for Microsoft to replicate or absorb reachability-based SCA capability natively.

JFrog competes on the artifact and binary management side, with security scanning built into its repository platform, and is similarly positioned as a platform that security teams can consolidate onto rather than a point tool.

Sonatype has focused on open-source component intelligence and malicious-package detection, with a vulnerability database built over many years. It competes directly with Endor Labs on SCA and SBOM generation, particularly for regulated industries that need deep provenance tracking.

On the SAST side, Semgrep has built a large open-source community around its rule-based static analysis engine and competes on developer experience and customizability. The emergence of AI-native SAST tools, including Endor Labs' own multi-agent engine, is putting pressure on signature-based approaches across the board, as the false-positive problem that has historically made SAST tools unpopular with developers becomes solvable with reasoning-capable AI agents.

The launch of AI SAST in early 2026 expands Endor Labs into the traditional static analysis budget, which Gartner estimates at over $4 billion globally. Legacy SAST tools have historically suffered from high false-positive rates that reduced developer adoption. Endor's multi-agent approach, which reasons about business logic rather than pattern-matching, supports use as a replacement rather than an add-on.

AURI, the free security layer for AI coding assistants, targets a gap that incumbents have not addressed: the moment when AI-generated code is written on a developer's laptop, before it reaches a repository. With roughly 90% of engineering teams now using AI coding assistants, the volume of unreviewed AI-generated code entering production is increasing faster than scan-based tools can address after the fact.

The freemium distribution model for AURI places Endor's reachability engine at the point of code creation, translating individual developer familiarity into enterprise pipeline as those developers join or advocate within regulated organizations.

Endor Labs' existing module set, secrets detection, container scanning, malicious-package detection, artifact signing, and SBOM generation, expands coverage into spend that currently flows to point tools like Trivy and Syft. Each module is an upsell for a customer already using Endor for SCA, and bundling them into a single platform contract reduces the number of vendor relationships a security team manages.

The strategic investment from Citi Ventures indicates demand in financial services, a vertical with acute software supply chain exposure and regulatory pressure around third-party risk management. Expanding into compliance packs tailored to PCI-DSS 4.0 and FedRAMP requirements increases wallet share in verticals, financial services, defense, and SaaS, where the cost of a supply chain breach can justify premium tooling.

The platform's scale, over 7 million applications protected and more than 1 million weekly scans, provides proof points to accelerate land-and-expand inside Fortune 100 organizations running large internal monorepos.

The EU Cyber Resilience Act, which entered into force in December 2024 and phases into full applicability through 2027, requires software sold in the European Union to document SBOMs, vulnerability-handling processes, and security update procedures. This creates a mandate for capabilities Endor Labs already ships, reachability-based SCA, SBOM generation, and automated remediation, and creates a compliance-driven buying trigger for European software vendors that did not exist two years ago.

Similar software security frameworks emerging in the UK, Japan, and Australia are creating parallel demand outside the U.S. federal market, giving Endor a regulatory tailwind for international expansion that is not dependent on competitive dynamics in any single geography.

Platform absorption: Microsoft's dual role as Endor Labs' distribution partner and a direct competitor through GitHub Advanced Security creates structural dependency risk. As Microsoft expands native security capabilities inside GitHub and Defender, it could add reachability-based SCA natively, reducing the differentiation that supports a separate Endor contract for the large portion of the market already inside the Microsoft ecosystem.

AI code volume: Endor Labs' core value proposition, reducing false-positive noise through call-graph reachability analysis, was built for human-written code with relatively stable dependency graphs. Growth in AI-generated code introduces dependency patterns and code structures that are less predictable, which can strain the accuracy of call-graph construction and create new categories of vulnerability that reachability analysis alone may not surface.

Open-source commoditization: The SCA and SBOM capabilities that anchor Endor's platform are increasingly available through open-source tools like Trivy and Syft, which cloud providers and DevOps platforms embed at no cost. As baseline expectations for dependency scanning shift from paid to free, Endor must show that its reachability-based triage and AI remediation justify a premium contract relative to free alternatives already available in most CI/CD environments.