SAST exists because security vulnerabilities introduced in code are cheapest to fix at the moment they are written. A flaw caught by a developer in their IDE, before the code is committed, costs minutes to fix; the same flaw caught in a pre-production pentest costs hours of back-and-forth and a release delay; the same flaw caught in production after a breach can cost the business enormously. SAST shifts detection as far left — as early in the lifecycle — as possible, so that the majority of code-level flaws are found and fixed by the developer who wrote them, at the moment they are cheapest to address.
What SAST detects is distinct from other testing approaches. Because it analyses the code without executing it, SAST can find classes of vulnerabilities that are difficult to detect dynamically: injection flaws (SQL, OS command, LDAP, XPath), insecure cryptographic usage, hard-coded credentials and secrets, path traversal, insecure deserialization, and many specific insecure coding patterns. It also has a structural advantage — it can trace data flow from source to sink, identifying that user input reaches a dangerous function even across many calls, which a dynamic test might not exercise. The trade-off is that SAST cannot find vulnerabilities that depend on runtime configuration or environment.
The historical weakness of SAST has been false positives, and addressing this is the single most important factor in a successful adoption. Early SAST tools flagged large volumes of issues that were not real vulnerabilities, which eroded developer trust and led to the tool being ignored — the so-called alert fatigue applied to code review. Modern SAST platforms have substantially reduced false positives through better data-flow analysis and triage, but no tool is perfect, and a deployment that does not actively manage false positives will fail. This is why triage — human review and suppression of false positives — is a core part of running SAST well, and why managed services that include triage add significant value.
Integration into the development workflow determines whether SAST is actually used. SAST that runs only in a nightly batch scan, producing a report that no one reads, does not change behaviour. SAST that runs at commit, gates the pull request, and comments directly on the offending lines — so the developer sees the finding at the moment they are working on the code — gets fixed. The most effective deployments embed SAST in the CI pipeline, fail builds on new high-severity findings, and present results in the developer's existing tools rather than a separate dashboard. Adoption is a workflow problem as much as a technology one.
Passeca delivers SAST through Aikido, embedding static analysis in CI/CD and pull requests with false-positive triage as part of the service — which is the part most organisations struggle to resource internally. Aikido combines SAST with SCA (software composition analysis), so that both the code the team wrote and the open-source libraries they depend on are covered in a single workflow. The same platform supports DAST (dynamic testing) and cloud posture, giving a unified view across the application security programme. Passeca implements, tunes, and operates the platform as part of a Secure SDLC engagement.