Software Composition Analysis (SCA) is a critical layer in any AppSec strategy. It scans open-source dependencies to detect known vulnerabilities — but its effectiveness is often undermined by noise.
That noise? False positives.
And the weapon against it? Reachability analysis.
What is SCA Reachability?
Reachability analysis determines whether a vulnerable function in a dependency is actually invoked by your code.
Think of it this way:
- 📦 SCA finds a vulnerable library in your codebase.
- 🔬 Reachability checks if your application ever calls the vulnerable code path.
If not, the risk is much lower — and the finding may be deprioritized or even suppressed.
🚨 Without reachability, teams waste time triaging vulnerabilities that pose no real threat.
The False Positive Problem in SCA
False positives are the Achilles’ heel of traditional SCA tools. They flag vulnerabilities without considering whether those vulnerable functions are even used.
📊 Key Statistics:
- Up to 95% of SCA alerts are not exploitable because the vulnerable code paths are never invoked (Coana).
- 72% of security professionals say false positives hurt team productivity.
- 62% would rather reduce false positives than find more vulnerabilities.
- 59% say false positives take longer to triage than true positives (Finite State Report).
The conclusion? False positives aren’t just a nuisance — they’re a blocker to effective AppSec at scale.
How Reachability Improves SCA Accuracy
Reachability provides contextual assurance that helps teams act on real threats.
| Without Reachability | With Reachability |
|---|---|
| All vulnerabilities flagged | Only exploitable CVEs flagged |
| No prioritization | Sorted by actual code usage |
| Developer friction | Actionable, relevant findings |
Benefits:
✅ Fewer false positives
✅ Better signal-to-noise ratio
✅ Faster remediation
✅ Greater trust between AppSec and engineering
How Scandog Enhances SCA with Reachability
At Scandog, we take SCA to the next level by:
- 🧠 Correlating SCA findings with real code paths
- 🔍 Detecting reachable vulnerable methods
- 📊 Visualizing usage paths across services
- ⚙️ Generating auto-remediation tickets only for exploitable issues
- 🔗 Integrating SCA insights into your overall ASPM view
Our platform supports:
- GitHub, GitLab and Azure DevOps workflows
- JavaScript, Go, Rust, Java, Python, Node.js, C, C++, C# ecosystems
- Tools like Snyk, Trivy, OWASP depscan, Grype, cdxgen, syft
✨ With Scandog, you secure what matters — and ignore what doesn’t.
Final Thoughts
SCA without reachability is like a smoke detector that beeps constantly — eventually, everyone ignores it.
With reachability analysis, security becomes clear, credible, and contextual. You can reduce false positives, focus remediation, and build trust between AppSec and engineering.
Ready to cut through the noise?
👉 Book a demo
FAQs
What is reachability in SCA?
Reachability determines whether vulnerable code is actually called by your application, helping to filter out non-exploitable findings.
Does reachability remove all false positives?
It dramatically reduces them, especially in complex dependency chains, but should be part of a broader context-aware strategy.
How does Scandog implement reachability?
Scandog combines static analysis, call graph tracing, and SCA metadata to enrich findings with usage information.
