SAST vs SCA: What's the Difference and Do You Need Both?
Written by the Rafter Team
SAST and SCA are not two flavors of the same scan. Static Application Security Testing (SAST) analyzes the code your team wrote—the SQL query built from unescaped input, the endpoint missing a permission check, the deserialization call fed untrusted data. Software Composition Analysis (SCA) analyzes the open source packages you pulled in from npm, PyPI, or Maven, checking each version against databases of known CVEs and flagging risky licenses. The short answer: SAST secures the code you own, and SCA secures the code you borrowed.
Most applications need both, because most applications are built from both. That split sounds simple, but it's the source of most of the confusion around these two tool categories—people assume SAST and SCA are competing products because they show up in the same "application security" conversation and get bundled into the same vendor pitch decks. In practice they scan disjoint surfaces of your application. Running only one leaves a predictable, and avoidable, blind spot.
A useful gut check: if the fix for a finding is "rewrite this function," it's a SAST problem. If the fix is "bump this package version," it's an SCA problem. The tools rarely overlap on the same line of code.
The Quick Verdict
You need both. SAST and SCA cover different parts of your application, and skipping either one means shipping a category of vulnerability you have no way of catching.
| SAST | SCA | |
|---|---|---|
| Analyzes | Code your team wrote | Open source packages you imported |
| Finds | Injection flaws, broken auth checks, hardcoded secrets, insecure logic | Known CVEs, malicious packages, license violations |
| Data source | Your repository | Package registries and CVE/advisory databases |
| Typical share of codebase covered | 10-30% (your custom logic) | 70-90% (your dependency tree) |
| Fix action | Rewrite or reconfigure the flagged code | Upgrade or replace the dependency version |
| Runs where | Every pull request, in CI | Every pull request, in CI |
If you can only run one scan this week, run whichever one you have zero coverage on today. If you're building a permanent pipeline, the answer isn't SAST or SCA—it's SAST and SCA, plus secret scanning for the credentials that neither one is designed to find.
What Is SAST?
Static Application Security Testing analyzes your source code, without running it, looking for patterns that match known vulnerability classes. A SAST tool parses your codebase into an abstract syntax tree, traces how data flows from input to output, and flags places where untrusted input reaches a dangerous function without being sanitized.
This is the tool category for catching the mistakes developers make in the code they personally write. Common findings include SQL and command injection where user input is concatenated into a query or shell call, cross-site scripting where unescaped data lands in HTML output, hardcoded API keys or passwords sitting in source files, and insecure deserialization where untrusted data is passed straight into a parser.
Because SAST reads your actual source, it can point to the exact file and line number responsible for a finding. That precision is what makes SAST fast to act on—a developer doesn't have to reproduce anything to understand the fix. For a deeper technical walkthrough of how the parsing and data-flow analysis actually works, see How Static Analysis Works and the full SAST and static analysis guide.
SAST has a hard boundary, though: it only sees the code that's checked into your repository. If a vulnerability lives inside a library you imported rather than a function you wrote, SAST has nothing to parse—the flaw is in someone else's source, and most SAST tools don't scan node_modules or vendored packages by design. That boundary is exactly where SCA takes over.
What Is SCA?
Software Composition Analysis identifies every third-party component in your application, builds an inventory of it—often called a software bill of materials, or SBOM—and checks each component's version against databases of publicly known vulnerabilities.
An SCA tool starts by parsing your manifest and lockfiles (package-lock.json, requirements.txt, pom.xml, and equivalents) to determine the exact version of every direct and transitive dependency your project pulls in. It then cross-references those versions against vulnerability databases like the National Vulnerability Database and the GitHub Advisory Database, surfacing any package with a known CVE. Good SCA tools go further and flag license risk too—a GPL-licensed package buried deep in your transitive tree can force disclosure obligations your legal team never signed up for.
The critical distinction from SAST: SCA doesn't care what your code does. It never inspects your business logic or your custom functions. It cares only about which packages are present and which versions are installed, matched against a list of previously disclosed problems in software other people wrote. That's a fundamentally different question than "did we write this code safely," and it requires a fundamentally different tool to answer it—one covered in more depth in the dependency scanning and SCA guide.
Most of the risk here doesn't even live in the packages you chose directly. It lives in the dependencies those packages pulled in without you ever seeing a name. Understanding direct vs. transitive dependencies is table stakes for reading an SCA report correctly, because the vulnerable package four levels deep is usually the one nobody on the team remembers adding.
The Overlap Myth
The most common misconception about SAST and SCA is that they're redundant—that if you already run one, the other is mostly duplicate coverage. The numbers say otherwise.
Modern applications are typically 70-90% open source code by volume. That majority of your codebase is exactly the part SAST cannot see, because SAST scans the repository you wrote and most dependency code lives outside it. SCA is the only tool category checking that majority against known vulnerabilities at all.
Flip it around and the same asymmetry holds. Your authentication flow, your payment logic, your access-control checks, and every business rule specific to your product are code you wrote—dependencies can't write your product's unique logic for you. SCA has no visibility into any of it, because there's no package version to check and no CVE database that covers your own bugs. Only SAST can catch a broken authorization check in a route handler you wrote last week.
So the overlap between what SAST and SCA actually catch is close to zero. They aren't two tools competing for the same findings—they're two tools splitting the codebase by origin, and each one is blind to the half the other one owns. Framed this way, "SAST vs SCA" is a bit of a misnomer; it's closer to "SAST for your code, SCA for everyone else's."
There is a narrow zone where the categories brush up against each other. If your own code calls a dependency in a way that triggers a known-vulnerable code path, some advanced SCA tools with reachability analysis will flag it, and a SAST rule tracing that same data flow might independently notice the unsafe call. That's a useful cross-check when it happens, but it's the exception, not the rule—most findings from each tool have no equivalent in the other.
Do You Need Both SAST and SCA?
Yes, and the reasoning doesn't require an edge case to justify it. If you skip SAST, you have no automated check on the code your own developers—or increasingly, AI coding agents—write every day: the logic errors, the missing sanitization, the auth check that got copy-pasted wrong. If you skip SCA, you're flying blind on the 70-90% of your application that came from someone else's repository, including packages with disclosed CVEs that are trivial for an attacker to find and match against your lockfile.
Neither gap is theoretical. Supply chain incidents involving a single vulnerable or compromised package have repeatedly cascaded into thousands of downstream applications, which is the exact failure mode SCA exists to catch early. Meanwhile, injection and access-control flaws—the kind of mistakes that live in code your team wrote, not code you imported—remain consistent fixtures on the OWASP Top 10 year after year, which is the exact failure mode SAST exists to catch early.
A practical pipeline runs both on every pull request, alongside secret scanning:
- SAST on every PR. Scan the diff for injection, broken auth, and insecure patterns before the code merges. See SAST vs DAST for how static analysis fits alongside runtime testing later in the pipeline.
- SCA on every PR. Check any new or updated dependency against CVE and advisory databases before it lands in your lockfile. If you're comparing vendors for this layer, the SCA tools comparison breaks down how Snyk, Dependabot, and Renovate differ in practice.
- Secret scanning on every push. Neither SAST nor SCA is designed to catch a committed API key or database password—that's a distinct pattern-matching problem, and it belongs in the same pipeline as a third, separate check.
- Block merges on critical findings, and let everything lower-severity surface as a comment rather than a hard stop, so the pipeline stays something developers actually keep enabled.
This is also, not coincidentally, what Rafter runs. Rafter is a security review that runs in CI, on the pull request, combining SAST, SCA, and secret scanning into one check—so a vulnerable pattern in your own code and a known-CVE package you just added both get caught before merge, not after. It's built for a world where agents write a growing share of the code, and the review has to keep pace with them: security for a world where agents write the code.
Frequently Asked Questions
What is the difference between SAST and SCA?
SAST analyzes the source code your team wrote, looking for insecure patterns like injection flaws, broken access checks, and hardcoded secrets. SCA analyzes the third-party open source packages your project depends on, checking each version against databases of known vulnerabilities and license restrictions. One scans code you authored; the other scans code you imported.
Is SCA the same as SAST?
No. They're often bundled together in vendor product suites and CI pipelines, which is where the confusion comes from, but they analyze different inputs and catch different vulnerability classes. SAST needs your source code to work; SCA needs your dependency manifest and lockfile. A tool that only does one of these is not a substitute for the other.
Do I need both SAST and SCA?
Yes, if your application has both custom logic and third-party dependencies—which is true of nearly every modern codebase. Skipping SAST leaves the code you wrote unchecked; skipping SCA leaves the 70-90% of your application that's open source unchecked. Most real security incidents trace back to one of these two categories, so covering only one still leaves the other wide open.
Which finds vulnerable dependencies?
SCA. It's the tool category purpose-built to identify every package in your dependency tree—direct and transitive—and match each version against CVE and advisory databases. SAST does not inspect dependency internals and generally won't flag a known-vulnerable package version at all; that detection lives entirely in SCA and tools with dependency-aware reachability analysis.
Can one tool do both SAST and SCA?
Some platforms run both scan types under one product, which is convenient for setup and reporting, but under the hood they're still two separate analysis engines solving two separate problems. Rafter is an example—it runs SAST and SCA (plus secret scanning) as part of the same CI check, so you get one report instead of stitching together two tools' outputs, but each scan type is still doing its own distinct job.
Where does secret scanning fit in—is it SAST or SCA?
Neither. Secret scanning is a third, separate category that looks for committed credentials—API keys, passwords, tokens—using pattern matching and entropy analysis rather than vulnerability databases or data-flow tracing. A complete pipeline runs all three: SAST for your code, SCA for your dependencies, and secret scanning for the credentials that could slip past both.