Endor Labs

Opens PRs with upgraded dependency versions that resolve CVEs. Quality differentiation is whether the fix resolves transitive chains or only direct dependencies, and whether the PR is merge-safe without manual review.

Scans images stored in registries (ECR, GCR, Artifact Registry, Docker Hub), for vulnerable OS packages and application dependencies at push time or on schedule, without requiring a running container.

Determines whether a vulnerable function is actually reachable and called in the codebase: not merely present in the dependency tree. Reduces actionable CVEs to those with real exploit paths; requires static code analysis on top of dependency scanning.

Identifies hardcoded credentials, API keys, tokens, and private keys in source files. Operates on the repository and commit history, not at runtime.

Traverses the full dependency graph to surface CVEs in indirect dependencies, packages required by your direct dependencies. Direct-only scanning misses the majority of vulnerable code paths in modern polyglot projects.

Blocks or flags PRs in CI/CD pipelines based on policy-defined thresholds, configurable by severity, CVSS score, exploitability, fix availability, or CVE age. Prevents vulnerable code from merging without requiring zero-tolerance policies.

Identifies OSS licenses in the dependency tree and flags conflicts with the project's target license or policy (GPL contamination, copyleft obligations, export-controlled components). Separate from vulnerability detection.

Defines open source policies (banned licenses, blocked packages, version floors, severity gates) as version-controlled rules applied automatically at scan time across repositories.

Exports the dependency inventory as a machine-readable Software Bill of Materials in SPDX or CycloneDX format, consumable by downstream vulnerability scanners, compliance tools, and procurement workflows.

Identifies packages with known-malicious behavior (typosquatting, dependency confusion, backdoored releases), distinct from packages with CVEs in legitimate code.

Scores open source dependency health using release cadence, maintainer count, contributor reputation, and popularity, flagging abandoned packages beyond known CVEs.

Prioritizes dependency vulnerabilities using exploitation signals such as EPSS probability and the CISA Known Exploited Vulnerabilities catalog, ranking findings by real-world exploitation likelihood rather than CVSS severity alone.

Identifies open source and third-party components in compiled binaries and closed-source artifacts where no package manifest exists.

Scores aggregated findings using multiple contextual factors (exploitability, reachability, internet exposure, threat intelligence, and business criticality) rather than individual tool severity ratings, producing a single actionable priority queue across all AppSec signals.

Scores dependency vulnerabilities by whether the vulnerable function is reachable in the actual application execution path, not just present in the dependency tree, reducing the actionable finding list to confirmed code-level exposures.

Pushes prioritized findings to developer ticketing (Jira, GitHub Issues, Linear), and IDEs with remediation context, removing the security team from the routing path.

Groups findings from multiple tools that refer to the same underlying vulnerability in the same code location, presenting one actionable finding instead of multiple redundant alerts.

Maps aggregated AppSec findings and scan coverage to regulatory and framework controls (PCI DSS Requirement 6, ISO 27001 Annex A.8.28, SOC 2), and generates audit-ready evidence and compliance reports across the application portfolio.

Maintains a registry of all applications in scope, their associated scan coverage, and their AppSec tool assignments, surfaces applications with no active scanning.

Evaluates all applications against organization-wide AppSec policies (minimum scan coverage requirements, severity thresholds, mandatory compliance checks), and flags non-compliant applications.

Integrates and triggers AppSec scanners across the pipeline, controlling which tests run at each stage (pull request, build, release) according to organizational policy rather than leaving each tool to run on its own schedule.

Links each finding to the specific code, component, or pipeline that introduced it and traces it from source through build to the deployed runtime, so teams can fix the underlying cause and see which projects contribute the most risk.