Software Composition Analysis: Managing Open Source Risk in Your Dependencies

A common pattern in application security assessments is the gap between what engineering teams believe their dependency exposure to be and what it actually is. A team that has carefully reviewed the twenty libraries listed in their package manifest may have three hundred additional transitive dependencies they have never examined. Each of those transitive dependencies has its own version history, its own disclosed vulnerability record, and its own update cadence. For most modern software products, the open source dependency surface area is the largest and least understood component of the application's security profile.

This is not a criticism of engineering practice. The dependency ecosystem that makes rapid software development possible is genuinely complex, and tracking it manually at any meaningful scale is not feasible. Software composition analysis (SCA) tools exist specifically to provide systematic visibility into that surface area: what is present, what versions are in use, what known vulnerabilities exist in those versions, and what licences govern the code being included. For most teams, SCA is the security investment with the fastest return relative to the complexity of the implementation.

What SCA Tools Actually Do

An SCA tool reads the dependency manifest of the application, resolves the full dependency tree including transitive dependencies, and compares the identified packages and versions against databases of known vulnerabilities. The output is a list of dependencies with associated vulnerability records, severity scores, patch availability, and in some cases, information about whether the vulnerable code path is actually reachable in the application. The tool also typically checks licence types, which is relevant for organisations with licence compliance requirements, particularly around copyleft licences in commercial software.

SCA tools run without executing the application and without requiring access to the full source code. They work from the dependency manifest files that already exist in the repository. Integration into a CI/CD pipeline is typically straightforward: the tool runs as a pipeline step, reads the manifest, and outputs findings in a format that can be consumed by the pipeline's enforcement logic. Most SCA tools also support generating a software bill of materials in a standard format, which is increasingly required by enterprise customers and government procurement processes.

The Challenge of Prioritisation

The volume of findings that SCA tools produce for a mature codebase can be substantial. A product with several hundred dependencies will often have dozens or hundreds of known vulnerabilities across them, particularly if the dependency tree has not been actively maintained. Not all of those vulnerabilities represent the same risk. A critical vulnerability in a library that handles authentication requests is a different risk than the same severity rating in a library used only for date formatting in a non-user-facing reporting function.

Effective prioritisation requires combining the severity score with context about how the library is used, whether the vulnerable code path is reachable in the application's deployment configuration, and whether a fix is available. Many teams start with severity as the primary filter and work down from critical findings. That is a reasonable starting point but misses the reachability dimension. Where SCA tools provide reachability analysis, that information should be used to adjust the priority order rather than treating all findings of the same severity as equivalent.

Dependency Hygiene as an Ongoing Practice

SCA is not a one-time exercise. New vulnerabilities are disclosed continuously against packages that are already in use. A dependency that passed a scan in January may have a critical vulnerability published in March. The SCA check in the pipeline handles new code changes, but it does not automatically flag existing code when a new vulnerability is disclosed against a dependency that has not changed. A complete SCA programme includes scheduled scans of the full dependency tree, not just scans triggered by code changes.

Dependency hygiene also means maintaining an active process for updating dependencies before they become a security problem rather than only updating them in response to a disclosed vulnerability. Teams that update dependencies in small, frequent increments find the process significantly less disruptive than teams that allow dependency versions to fall behind and then face large-scale update projects where breaking changes have accumulated. Automated dependency update tooling can help, but it requires a test suite that provides enough coverage to catch regressions introduced by dependency updates before they reach production.

Licence Risk

Alongside vulnerability risk, SCA tools surface licence risk that many engineering teams are not actively managing. Including a library governed by a copyleft licence in a commercial product may trigger licence obligations that affect how the product can be distributed. Including a library with a licence that prohibits commercial use in a commercial application creates legal exposure that has nothing to do with security vulnerabilities. Licence review is a compliance function, but the data to support it comes from the same SCA process that surfaces security findings.

If your team does not have systematic visibility into your open source dependency surface area, that is the right place to start building your DevSecOps programme. We help engineering teams implement SCA programmes that fit into their existing pipeline without adding unnecessary process overhead. Contact us at info@cyberlinx.com.au to discuss your specific situation.