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Start with a few checks that match your repository: linting and tests for everyday defects, static analysis for risky code patterns, dependency scanning for known vulnerable packages, and secret scanning for exposed credentials. Run them on pull requests and the default branch, review results before making them merge blockers, and expand into container, infrastructure, or runtime testing only when your project needs that coverage. No single scan proves that software is secure.

What automated code quality and security scanning covers

Quality checks and security checks overlap, but they answer different questions. A formatting check can enforce a consistent style; it cannot tell you whether a dependency has a newly disclosed vulnerability. A security scanner can flag a risky pattern; it cannot establish that the application behaves correctly in every situation.

Check What it looks for What it does not establish
Formatting and linting Style inconsistencies, suspicious constructs, and common coding mistakes. That the application is secure or that its behavior is correct.
Type checking and tests Type mismatches and defects exercised by the tests you run. That untested paths are correct or free of security flaws.
Static application security testing (SAST) Potentially unsafe source-code patterns and, depending on the tool, data flows. All runtime behavior or every vulnerability in every supported language and framework.
Software composition analysis (SCA) Known vulnerability and, where provided, license information for project dependencies. That a matched vulnerable package is reachable or exploitable in your application.
Secret scanning Strings that resemble credentials in files or, with history-aware scanning, Git history. That every kind of credential will be detected or that deleting a string invalidates it.
Infrastructure-as-code (IaC) scanning Risky settings in cloud, deployment, or infrastructure configuration. That the deployed environment matches the files or is otherwise safely configured.
Container scanning Vulnerable components and other risks in a built image, depending on the scanner. That the application or the full deployment is safe.
Dynamic application security testing (DAST) Issues observable by testing a running application from the outside. All code paths, especially unvisited or inaccessible ones, or a substitute for code review and SAST.

Coverage varies by language, framework, file format, rule set, vulnerability database, configuration, and scan mode. “No findings” means the selected scanner detected none in the inputs it examined using its rules and data at that time. It is not a security certification. OWASP recommends incorporating suitable security checks into delivery pipelines, while NIST’s Secure Software Development Framework places automated analysis within a broader secure development process: OWASP CI/CD Security Cheat Sheet and NIST SP 800-218.

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Choose a small set of checks for your repository

Begin with detection categories, not a long list of products. A compact setup that developers can understand and maintain is usually more useful than overlapping scanners whose alerts no one has time to review.

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  • Keep existing quality gates. Run the project’s formatter, linter, type checker, and tests in CI. Add security checks alongside them, rather than treating one category as a substitute for the others.
  • Cover source code. Choose SAST that supports the repository’s languages and frameworks. Check what files and analysis modes it actually covers.
  • Cover dependencies. Prefer a scanner that can read the project’s lockfiles or a software bill of materials (SBOM), and that explains the package, affected version, advisory, and available fix.
  • Cover credentials. Scan current files and consider Git history where supported. A local or pre-commit check can provide fast feedback, but it must not be the only safeguard because hooks can be bypassed.
  • Add other categories when applicable. Scan IaC if the repository defines infrastructure, containers if it builds images, and a running test deployment with DAST if you operate a web application.

Compare candidates against language and package support, local and CI operation, pull-request feedback, configuration and exception controls, report formats, version updates, data handling, job permissions, and any relevant plan limits. Verify current availability and pricing with the vendor rather than assuming that a feature exists for every account or region. Check whether your CI platform already supplies suitable coverage before adding a duplicate.

Set up a first scan and bring the results into CI

1. Inventory the project

List its languages, frameworks, package managers, lockfiles, build and test commands, CI provider, and deployment targets. Note whether it builds containers or uses IaC. Check the current workflow for existing scans so you do not add redundant jobs.

2. Run a scan without blocking changes

Use the scanner’s current official installation and CI instructions. Pin scanner and third-party workflow versions to reviewed versions or immutable commits where supported, and decide how you will update them. For example, the OSV-Scanner V2 usage guide documents scanning a project directory with osv-scanner scan -r ./my-project-dir/, or a lockfile with osv-scanner scan -L package-lock.json; JSON output can be requested with --format json. Confirm current flags and supported inputs in the OSV-Scanner usage documentation and installation instructions.

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As another category-oriented example, Trivy documents filesystem scanning with trivy fs /path/to/project. Its filesystem documentation says vulnerability and secret scanning are enabled by default for filesystem scans, while misconfiguration scanning must be enabled separately with --scanners misconfig. The Trivy filesystem documentation uses a development documentation path, so verify current behavior and flags before relying on them. Secret scanner behavior is described in the Trivy secret scanning guide.

For GitHub repositories, GitHub documents both default and advanced code scanning setup. The default setup automatically configures CodeQL for supported languages; the documented behavior includes scans on pushes to default or protected branches, pull requests targeting those branches except pull requests from forks, and a weekly schedule. Availability and setup options depend on repository and plan, so check the current GitHub code scanning setup documentation. These are examples of particular tools and platform behavior, not a universal stack or coverage guarantee.

3. Add the checks to pull requests and the default branch

Configure checks to run on proposed changes and on merged code. Keep a full-repository or equivalent scan in the default-branch or scheduled workflow; change-aware scans can speed up pull-request feedback when the tool supports them, but a diff-only scan can miss older issues or findings affected indirectly by a change. Save machine-readable reports or artifacts when they help the team track and investigate results.

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Make CI distinguish three outcomes: scan completed with findings, scan completed without findings, and scan failed to run. A broken scanner job is not a clean scan. Pin and deliberately update scanner versions and external CI actions, and give jobs only the permissions they need. For untrusted contributions, particularly forked pull requests, do not expose write-capable credentials or sensitive secrets to jobs that execute contributor-controlled code. Follow the CI provider’s current event and permission model; OWASP’s CI/CD security guidance discusses pipeline protections and secret handling.

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Triage the first findings and establish a baseline

Classify each result as actionable, a likely false positive, an accepted risk, or something that needs investigation. Start with representative, high-confidence findings so you can confirm that reports point to useful fixes and understand the scanner’s behavior. If a safe test fixture or known test case is available, use it to check detection; never use a real credential as test data.

Investigate a dependency alert

  • Confirm the package identity, version, and lockfile entry, and check the advisory and fixed version reported.
  • Determine whether the application uses the package and whether the affected functionality is reachable. A version match alone does not settle exploitability.
  • Assess severity in the context of exposure and use, then plan a safe upgrade or mitigation and run relevant tests.
  • Assign an owner and a target date. Advisory databases can differ or lag, so treat scanner output as a signal to investigate, not a complete verdict.

Respond to a confirmed secret

Treat an exposed credential as compromised: revoke or rotate it, assess what it could access, and remove it from current files and Git history or other artifacts as appropriate. Deleting the visible string does not invalidate the credential or erase copies already present elsewhere. Store replacement credentials using the team’s approved secrets mechanism; OWASP’s Secrets Management Cheat Sheet covers secret handling considerations.

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Document exceptions narrowly

If a result is a false positive or an accepted risk, record the specific rule or finding, rationale, approver or owner, and a review or expiry date. Prefer a finding-specific exception to suppressing an entire rule family or scanner. Revisit exceptions as code, dependencies, and threat context change. The OSV-Scanner configuration documentation describes configuration and vulnerability ignore options for that tool.

Use the initial results to create a baseline: record inherited findings, owners, and priorities, then track new findings separately. This gives the team a manageable starting point without pretending that old issues have disappeared.

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Decide when a scan should block a merge

Begin in report-only mode if the project already has a large backlog or the team has not yet assessed alert quality. Once the baseline is understood, define a narrow policy for newly introduced findings. For example, require review or block on findings that meet a stated severity and confidence threshold, while tracking inherited issues on a separate remediation plan.

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Severity is not the whole decision: exposure, exploitability, business impact, and compensating controls matter. Set thresholds the team can act on, name who can approve exceptions, and define what happens when a scanner is unavailable. A policy should be explicit and consistent rather than an automatic response to every alert label.

Common failure modes and how to avoid them

Problem Why it happens Practical response
Too many alerts or duplicate advice Overlapping tools, broad rules, or blocking a large inherited backlog can overwhelm reviewers. Baseline first, remove unnecessary overlap, prioritize actionable new findings, and tune rules narrowly.
Scan misses a project area The language, framework, file, lockfile, or scan mode may not be supported or included. Verify supported inputs and coverage; add a suitable category-specific check rather than assuming a project-wide label means every file was analyzed.
Dependency scan has little useful input Lockfiles may be absent, stale, or not included in the scan. Generate and commit the appropriate lockfile where the project workflow permits, and confirm the scanner reads it.
CI appears green despite a scanner problem A job can be skipped, fail to initialize, or report errors separately from findings. Make scan execution failures visible and distinct from a successful scan with no findings.
Exceptions become permanent blind spots Allowlist entries often outlive the context that justified them. Require a rationale, owner, and review or expiry date, and revisit them on schedule.
A privileged job runs untrusted code Workflow events or permissions may expose secrets or write access to attacker-controlled changes. Use least privilege, withhold sensitive credentials from untrusted jobs, and review the provider’s current security model.

Expand scanning as the project changes

Add coverage in response to what you build and deploy, rather than installing every scanner at once.

  • Container images: scan built images when the project publishes or deploys them, since filesystem source scans do not inspect the same artifact.
  • Infrastructure: add IaC checks when the repository defines cloud or deployment resources.
  • Running web applications: run DAST against an authorized, controlled test environment with safe accounts and test data. It can change application state, miss authenticated areas, or produce results that do not match production if the target differs.
  • Release and customer needs: consider SBOM generation or artifact scanning when release, customer, or regulatory requirements call for it.

Automation supports review, testing, threat modeling, and secure design; it does not replace them or prove a project defect-free. NIST’s SSDF Version 1.1 is a broader framework for secure development practices, not a scanner setup recipe.

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