SAST analyses your own source code for insecure patterns. SCA identifies the third party and open source components you use and matches them to known vulnerabilities and licence risks. SAST finds flaws you wrote. SCA finds flaws you imported. Most teams need both, because each is blind to the other's territory.
What does SAST look at?
OWASP describes source code analysis tools as scanners that examine code for security flaws. Its list of strengths includes scaling well, running repeatedly in continuous integration, finding well known issues such as buffer overflows and SQL injection, and pointing developers to the file and line. Its weaknesses include difficulty finding authentication problems, access control issues and insecure use of cryptography, a high rate of false positives, and trouble with configuration issues that are not in the code. So SAST is strong on code level patterns and weaker on design and logic.
What does SCA look at?
OWASP's Component Analysis page says modern software is assembled from third party and open source components, and that by using them organisations take responsibility for code they did not write. Component analysis identifies risk from those components, and a software only subset is commonly called software composition analysis. An accurate inventory of components is central. SCA reads manifests and lockfiles, builds the dependency graph including indirect dependencies and compares versions with vulnerability data and licence information.
What does each one miss?
- SAST does not see inside a library. A flaw in a package you call is outside the scan unless the scanner also analyses that code.
- SCA does not see the logic you wrote. An injection bug in your handler has no CVE.
- SCA reports a vulnerability in a package even when your code never calls the vulnerable function, which can overwhelm teams with findings that do not matter.
- SAST reports patterns that are not exploitable in context.
A constructed example
A service parses uploaded files with an open source library. SCA flags a deserialisation CVE in version 2.3 of that library. SAST, run on your repository, shows a path where user input reaches your own SQL string. Neither tool sees the other issue. Fix both: upgrade the library and parameterise the query.
How does reachability change the picture?
Reachability analysis checks whether your code actually reaches the vulnerable function in a dependency, which turns a long SCA list into a shorter, ranked one. Safeguard offers reachability analysis alongside dependency scanning, so the findings you work first are the ones your application can actually trigger. It is a prioritisation aid, not a guarantee, so keep a policy for what you do with the unreachable ones.
How do they fit in a pipeline?
Run SCA on every pull request that touches manifests and nightly against the main branch, since new CVEs appear without code changes. Run SAST on every pull request with rules tuned to your languages, and gate only on high confidence findings at first. Store the SBOM as a build artefact so you can answer "are we affected?" for a new disclosure in minutes.
What to do
- Run SCA on all repositories, including indirect dependencies, and store an SBOM per release.
- Run SAST with rules tuned for your languages and frameworks.
- Rank SCA findings by reachability, exploit status and exposure.
- Gate pull requests on high confidence, high severity results first.
- Triage SAST false positives once and record suppressions with reasons.
- Re-run SCA on a schedule, not only on commits.
- Add dynamic and manual testing for logic and access control flaws neither tool finds.
Quick check
If we have SCA, do we still need SAST?
Yes. SCA covers components you import. SAST covers the code you write, which has no CVE entries to match against.
Why does SCA report vulnerabilities that do not affect us?
Because it matches versions, not call paths. Reachability analysis helps separate vulnerable code you call from code you never reach.
Sources
Last reviewed: 18 October 2026.
