Static Application Security Testing and Dynamic Application Security Testing answer different questions about the same codebase. Running one and ignoring the other leaves a category of vulnerabilities systematically unexamined. Understanding the technical distinction between the two also clarifies when each is worth the operational cost and when combining them is worth the overhead.
What SAST Actually Does
SAST tools analyze source code, bytecode, or compiled artifacts without executing them. The core technique is abstract interpretation or data flow analysis: the tool builds a model of how data moves through the program, from input sources (user-supplied request parameters, environment variables, file reads) to output sinks (database queries, system calls, HTML rendering, external API calls). When a path can carry attacker-controlled data from a source to a sink without adequate sanitization in between, the tool flags it.
This analysis happens before deployment. The tool does not need a running server or a test environment. It scans the code as it exists in the repository, which means it can be integrated directly into CI/CD pipelines and run on every pull request. The practical result is that developers get feedback on introduced vulnerabilities before the code reaches staging or production.
SAST's main limitation is that it reasons about code paths, not runtime behavior. It cannot account for values that arrive from configuration at startup, from external services called at runtime, or from reflection and dynamic dispatch patterns that are difficult to model statically. Complex authorization logic that depends on database state is particularly hard for SAST to evaluate. This leads to both false positives, where the tool flags a code path that is safe in practice because of runtime guards the tool could not see, and false negatives, where vulnerabilities only manifest through specific runtime conditions the static model did not capture.
What DAST Actually Does
DAST tools interact with a running application from the outside, the same way an attacker would. They send crafted HTTP requests and observe responses. They submit SQL metacharacters and watch for database errors. They inject reflected payloads and check whether they appear unsanitized in the response. The key property is that DAST has no access to source code: it finds vulnerabilities by probing behavior, not by analyzing structure.
This means DAST surfaces classes of vulnerabilities that SAST cannot reliably detect. Configuration-level issues such as missing security headers, exposed admin interfaces, or CORS misconfiguration are invisible to a static code analysis tool but straightforward for a DAST scanner to find. Authentication and session management weaknesses, which depend on how the application handles state across requests, are also far easier to test dynamically than to reason about statically.
The trade-off is that DAST requires a running application. This means it cannot run until a build is deployed to a test environment, which pushes discovery later in the development cycle. DAST scans also tend to be slower than SAST scans, because each test requires an HTTP round-trip and often many requests to confirm a finding. For deep scanning of large applications, a full DAST run can take hours.
Vulnerability Classes: Where Each Tool Wins
The cleanest way to think about the division is by whether the vulnerability's root cause is in code structure or in runtime behavior.
SAST wins on: injection vulnerabilities where the data flow is traceable statically (SQL injection with ORM bypass, command injection, LDAP injection), hardcoded secrets, insecure cryptographic algorithm choices, and resource handling errors such as unclosed file handles or missing error propagation that can lead to information leakage.
DAST wins on: HTTP header security (missing Content-Security-Policy, X-Frame-Options, Strict-Transport-Security), authentication bypass via crafted requests, open redirect vulnerabilities, insecure direct object reference where access control depends on request parameters, and server-side request forgery in cases where the SSRF target is only determinable at runtime.
Both tools can detect XSS, but with different accuracy profiles. SAST will find reflected XSS where user input flows to a rendering template without encoding, if the data flow is traceable. DAST will find reflected XSS through actual injection, and will also find DOM-based XSS variants that are difficult to model statically. Running both catches more of the XSS surface than either alone.
Integration Points in a Real Pipeline
The standard pattern is to run SAST on every PR commit and DAST on deployment to a staging environment. This timing makes sense given the tools' requirements: SAST has no runtime dependency, so it can run early and fail the build if a critical finding is introduced. DAST has a runtime dependency, so it runs after the build is deployed, typically as a post-deploy gate before promotion to production.
For teams that cannot afford to run a full DAST scan on every deployment, a tiered approach works: run a fast baseline DAST check on every staging deployment covering the highest-risk endpoints, and run a full deep scan on a scheduled cadence or before major releases. The fast check catches newly introduced DAST-visible issues in the current deployment; the full scan catches issues that require broader coverage.
The False Positive Question
SAST false positive rates vary widely by tool and by how well the tool models the specific language, framework, and codebase patterns in use. Tools that use interprocedural data flow analysis with framework-aware models tend to produce fewer false positives than tools that use syntactic pattern matching. The cost of a false positive is real: a developer investigating a SAST finding that turns out to be a false positive loses time and, over repeated occurrences, loses confidence in the tool's output.
DAST false positive rates are generally lower because the tool is testing actual behavior: if the response confirms the injection, the vulnerability is real. The main DAST false positive category is overly aggressive scanner payloads triggering WAF blocks or application errors that look like vulnerability confirmations but are not. Tuning the scanner to the application's error response patterns typically resolves these.
We are not arguing that one tool's false positive profile is universally better. The point is that they fail in different modes, and knowing the mode helps with triage.
When You Run Only One
Teams with constrained tooling budgets often ask which to prioritize. The answer depends on what you are trying to catch first. If your codebase has active development with many contributors and you want vulnerability detection before code ships, SAST provides earlier feedback at lower operational cost. If you have a more stable codebase and your primary concern is runtime configuration and external-facing behavior, DAST addresses what SAST cannot see.
Both tools leave categories of vulnerabilities undetected if used alone. The security header gap is not visible to SAST; the complex injection data flow is not visible to DAST. A combined approach with clear integration points in the pipeline is more reliable than trying to compensate for one tool's limitations by tuning the other more aggressively.
