Hopper
vs Modern SCA

More Coverage. Less Setup. Real Results.

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Using Hopper, we were alerted to a critical issue in Java, before our runtime tool, and we were able to fix it in 20 repositories within a few hours, rather than the days or weeks it used to take to remediate.

Omri Vaizman
Senior Software Engineer

Modern SCA tools claim deep analysis but often fall short. They don’t offer function-level reachability analysis for transitive dependencies. Others miss dynamic code patterns like reflection, callbacks, and decorators, and struggle with frameworks like Spring, Django, and ASP.NET. They depend on CI pipeline integration, fail on partial builds, and require manual setup to track new projects or repos. This creates coverage gaps, delays time to value, and demands significant upfront effort just to get meaningful results.

Hopper connects directly to your source code to continuously discover new projects and repositories. It performs accurate function-level reachability, even for transitive dependencies, and supports dynamic code and modern frameworks. You get 10x more accurate OSS visibility, with no CI integration, no DevOps effort, and no blind spots.

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Why Customers Choose Hopper

Instant Deployment with Full Coverage

Hopper connects directly to your Git repositories and automatically scans every project it has access to; no manual onboarding or per-repo configuration required. It delivers results without modifying your CI pipelines or adding integration steps, and works seamlessly across all environments including monorepos, microservices, legacy systems, and serverless applications.

Proven Accuracy Across Dynamic Frameworks

Hopper supports analysis of common application frameworks and code patterns, including Spring, ASP.NET, Django, decorators, lambdas, callbacks, and reflection. We reduce false positives using points-to and dataflow analysis for reliable reachability.

Strategic Remediation with Context and Scale

Hopper guides remediation with root cause analysis, fix effort estimates, and call graphs showing how vulnerabilities are reached. It correlates shared risks across multiple projects and services so teams can fix once and resolve issues everywhere.

Features Comparison Chart

Capability
Hopper
Modern SCA
Analysis Depth
Function-level reachability, direct and transitive
Often lacks precision or framework support, not all solutions cover transitive dependencies
OSS Risk Coverage

Direct, transitive, repackaged, renamed dependencies
 Limited to standard or declared packages; some solutions don’t cover transitive dependencies
Internal Library Support
Scans internal libraries as both standalone projects and dependencies. Provides cross-repository reachability and org-wide impact and remediation insights.
Either lacks internal package awareness or limits analysis to the scanned repo. No cross-project visibility or shared remediation.
Shadow Dependency Detection
Identifies renamed, repackaged, or embedded libraries missed by standard scanners
Often misses or mislabels shaded or bundled libraries
Cross-Project CVE Insights
Maps vulnerabilities across services and projects, highlighting high-impact shared issues
Typically scoped to individual projects or models
Deployment Model
 Agentless, read-only Git-based. Covers containers, serverless, legacy systems, monorepos, and on-prem.
 Often requires CI/CD integration or manual setup per environment
App & Repo Discovery
 Continuous, automatic
 Requires manual repo selection or CI-based scan triggers
Framework & Language Coverage
Full support for Spring, ASP.NET, Django, Flask, FastAPI, NodeJS, and dynamic language features
Partial or inconsistent support in dynamic environments
Remediation Guidance
Contextual, with file/function-level tracing, and fix effort estimates
Upgrade suggestions based on severity or package metadata. No tracing to source or reachable code.
Developer Experience
Minimal noise, trusted output
 Less noisy than legacy SCA, but still high false positives due to transitive dependencies and imprecise reachability via CHA
Time to Value
Immediate results
Slower setup across pipelines