Enterprise-grade Software Composition Analysis. Scan 100 dependency levels deep. 80% fewer false positives. Autonomous remediation with Griffin AI.
From SBOM generation to automated remediation - complete visibility into your software supply chain
Scan 100 dependency levels deep - 40 more than Snyk. Discover vulnerabilities hidden in transitive dependencies that competitors miss.
Continuous monitoring with Griffin AI. Detect vulnerabilities, malware, and supply chain attacks the moment they're discovered.
80% fewer false positives. Know which vulnerabilities are actually exploitable in your code with advanced call graph analysis.
Griffin AI autonomously fixes vulnerabilities. No manual PR reviews. Upgrade dependencies safely with compatibility testing.
Everything you need for software composition analysis and supply chain security
🔍 SBOM Generation - CycloneDX, SPDX 2.3, SPDX 3.0 formats
🛡️ Vulnerability Scanning - CVE, GitHub Advisory, OSV database
📊 License Compliance - MIT, Apache, GPL detection and policy enforcement
🔗 Supply Chain Security - Dependency confusion, typosquatting detection
🎯 Reachability Analysis - Call graph analysis for exploitability
⚡ Automated Fixes - Griffin AI autonomous remediation
📈 Risk Scoring - CVSS, EPSS, KEV, business impact scoring
🔄 CI/CD Integration - GitHub Actions, GitLab CI, Jenkins, Azure DevOps
From startups to Fortune 500 - secure your software supply chain
SOC 2, PCI-DSS, HIPAA, FedRAMP compliance with automated SBOM generation and vulnerability tracking
Shift-left security with IDE extensions, pre-commit hooks, and automated CI/CD scanning
Focus on what matters with reachability analysis, EPSS scoring, and exploitability detection
Deep, reachable, lockfile-aware analysis with PR-level feedback — not a 50,000-alert dashboard.
Call-graph-aware verdict on whether a vulnerable function is actually invoked from your code path. Triage the queue by what's real, not what's theoretical.
First-class support for npm, PyPI, Maven, Gradle, Go modules, Cargo, RubyGems, Composer, NuGet, and Hex. One consistent finding shape regardless of language.
Up to 100-level deep transitive dependency walking, well beyond the industry norm of 7 to 12 levels. The vulnerable library hiding four sub-dependencies down does not stay hidden.
Findings are sorted by real-world exploit probability via EPSS and known active exploitation via KEV. The top of the queue is always the work that matters most.
Comments back on the PR that introduced the regression. Offers a one-click revert plus a safe-upgrade suggestion the author can take without leaving their review.
Reads package-lock.json, yarn.lock, poetry.lock, go.sum, Gemfile.lock, and friends to pin exact version sets per environment. No drift between scan and runtime.
Setup: AppSec is drowning in 50,000 SCA alerts.
Reachability passes filter out findings where the vulnerable code is never invoked. The remaining alerts are then ranked by EPSS and KEV so engineers see the top of the list first.
Outcome: 80% alert reduction and 5x throughput on real fixes.
Setup: a PR adds a new dependency that pulls in a KEV CVE.
The CI check fails fast when reachability is positive on a KEV-listed CVE, and auto-approves the PR when the same finding is provably not reachable.
Outcome: blocked regressions without slowing safe merges.
Setup: leadership wants a clean exit from a deprecated major version.
SCA lists every dependency pinned to the EOL major across services, with concrete upgrade-path suggestions and a per-team task breakdown.
Outcome: a credible migration plan, not a vague roadmap line item.
Setup: classified or regulated environment, no outbound SaaS.
The same SCA engine runs on an air-gapped offline mirror with the same advisory data, reachability passes, and verdicts. No SaaS call required.
Outcome: identical security verdicts inside and outside the perimeter.
Every scan walks the full graph, matches advisories, runs reachability, prioritises, and lands the answer in the right place.
Discovers package.json, requirements.txt, pom.xml, go.mod, Cargo.toml, Gemfile, composer.json, *.csproj, and mix.exs across every branch.
Walks up to 100 levels deep, honouring each ecosystem's resolver semantics and lockfile pinning rules.
Queries NVD, OSV, and GHSA in parallel; cross-checks malicious-package signatures along the way.
Static call-graph analysis decides whether each vulnerable symbol is reachable from your application's entry points.
Layers EPSS exploit probability and KEV active-exploitation flags onto every reachable finding.
Findings are ranked, then surfaced as inline PR comments with revert and safe-upgrade buttons on the offending diff.
For supported ecosystems, SCA opens a follow-up PR with the safe upgrade and runs the test suite before requesting human approval.
Join Fortune 500 companies using Safeguard SCA for comprehensive software composition analysis