// APPLICATION SECURITY

SAST

Static Application Security Testing seamlessly integrated into your development workflow.

CI/CDNative Integration
Shift-LeftSecurity Model
CRESTCertified Engineers
<5%Target False Positive Rate

SAST — Static Application Security Testing

SAST tools are only as good as the rules they run and the workflow they are embedded in. Intelliroot's SAST service goes beyond tool deployment: we select the right tool for your stack, tune rulesets to eliminate the noise that causes developer fatigue, integrate findings into your CI/CD pipeline and issue tracker, and build a triage workflow that ensures high-severity findings are acted upon before code merges. We work with Semgrep, SonarQube, CodeQL, Checkmarx, and Fortify across GitHub Actions, GitLab CI, Jenkins, Azure DevOps, and CircleCI.

DevSecOps is not a product — it is a culture shift. We deliver hands-on developer training so your engineering teams understand the vulnerability classes being caught, can remediate findings confidently, and adopt secure coding practices that prevent vulnerabilities from being introduced in the first place. The end result is a measurable reduction in security debt across every sprint.

Why Automated SAST Belongs in Every Pipeline

Find Flaws Before They Merge

SAST runs on every commit and pull request — catching injection flaws, crypto misuse, and dangerous function calls before they reach staging, let alone production. The cost to fix drops by 100x compared to post-deployment discovery.

Default Tooling Creates More Noise Than Signal

Out-of-the-box SAST configurations generate thousands of false positives. Without expert tuning, developers disable alerts entirely. Our rule curation targets a false positive rate under 5% — keeping the pipeline trusted.

Developer Adoption Requires Training

Tools without understanding create compliance theatre. Our developer workshops translate scanner output into genuine security knowledge — reducing time-to-fix and improving code quality beyond the immediate finding.

Regulators & Auditors Expect It

PCI DSS 6.3.2, ISO 27001 Annex A.8.28, and SOC 2 CC8.1 require automated security testing in the development process. A well-configured SAST pipeline with documented results satisfies these requirements.

What the Engagement Covers

Tool Selection & Configuration

  • Stack-specific tool recommendation (Semgrep, CodeQL, SonarQube, Checkmarx)
  • Ruleset selection and custom rule authoring
  • False positive baseline and suppression strategy
  • Severity thresholds and pipeline gate configuration
  • Licence and deployment model advisory

CI/CD Pipeline Integration

  • GitHub Actions, GitLab CI, Jenkins, Azure DevOps, CircleCI
  • Pull request comment and inline annotation setup
  • Blocking vs advisory gate configuration
  • Incremental scanning for large monorepos
  • Baseline suppression for legacy code isolation

Triage & Findings Management

  • Finding prioritisation framework (CVSS + business context)
  • Jira / GitHub Issues / Azure DevOps integration
  • SLA definitions by severity class
  • Triage workflow documentation for security team
  • Metrics dashboard for MTTR tracking

Developer Training & Enablement

  • Workshop on top vulnerability classes found in your codebase
  • Secure coding cheat sheets per language
  • IDE plugin configuration for local developer scanning
  • Champion programme for security-aware engineers
  • Ongoing rule update and tuning cadence

Our Implementation Approach

01

Discovery & Stack Assessment

Inventory your technology stack, existing security tooling, CI/CD platform, and developer workflow. Identify the repositories and branches that require scanning, any legacy code to isolate, and the teams who will act on findings.

02

Tool Selection & Proof of Concept

Run candidate tools against a representative sample of your codebase. Evaluate finding quality, false positive rate, language coverage, and CI/CD integration complexity. Produce a tool recommendation with supporting evidence.

03

Ruleset Tuning & Baseline Suppression

Configure selected rules for your stack and suppress known-safe patterns and legacy code noise. Establish a clean baseline so developers only see actionable new findings from day one — eliminating the "alert flood" that kills adoption.

04

CI/CD Integration & Pipeline Gating

Embed the SAST scanner into your pipeline with appropriate gate logic: blocking on Critical/High in new code, advisory for Medium, and informational for Low. Configure PR annotations, Slack/Teams notifications, and issue tracker auto-creation.

05

Developer Training Workshop

Deliver a half-day workshop covering the top vulnerability classes identified in your codebase — with secure-by-default coding patterns, live remediation examples, and IDE plugin setup so developers can catch issues before committing.

06

Handover, Metrics & Ongoing Tuning

Document the full configuration, triage workflow, and SLA definitions. Establish a quarterly rule-refresh cadence and provide a metrics dashboard tracking mean time to remediation, finding trends, and pipeline pass rates over time.

Semgrep SonarQube CodeQL Checkmarx CI/CD Integration Shift-Left Security False Positive Reduction Developer Training DevSecOps Finding Prioritisation

Frequently Asked Questions

There is no single best tool — the right choice depends on your languages, CI/CD platform, team size, and budget. Semgrep is highly flexible and open-source-friendly; CodeQL excels for deep dataflow analysis in Java and JavaScript; SonarQube integrates well with enterprise IDEs; Checkmarx suits regulated enterprises needing vendor support. Our tool selection engagement evaluates all options against your specific requirements and produces a documented recommendation.
This is the most common SAST adoption failure. The solution is a three-phase approach: first, suppress findings in legacy code that will not be remediated in the current cycle; second, tune rules to eliminate false positive patterns specific to your framework; third, establish a triage workflow with clear SLAs by severity so developers know exactly what needs to be fixed before merge. We typically reduce actionable finding volume by 70–80% without losing meaningful coverage.
SAST, manual code review, and DAST cover complementary attack surfaces. SAST catches code-level patterns at scale and high speed. Manual code review finds logic flaws, architectural weaknesses, and contextual vulnerabilities SAST misses. DAST tests the running application for runtime vulnerabilities that only manifest during execution. A mature AppSec programme uses all three: SAST in every pipeline, manual review for critical modules, and DAST in staging before every major release.
Yes. Documented SAST pipeline configuration, finding reports, remediation records, and SLA metrics collectively satisfy PCI DSS Requirement 6.3.2 (automated technical security testing in the SDLC) and ISO 27001 Annex A.8.28 (secure coding). We provide an engagement summary document specifically formatted for audit evidence submission.

Deliverables

Tool Selection Report

Evaluated comparison of candidate SAST tools against your stack with a documented recommendation, licensing guidance, and deployment architecture diagram.

Configured Pipeline Integration

Working SAST scanner embedded in your CI/CD pipeline with tuned rulesets, gate logic, PR annotations, and issue tracker integration — ready for day-one use.

Initial Findings Report

Risk-rated report of all findings from the initial full codebase scan, with false positives removed, suppressions documented, and remediation prioritisation guidance.

Triage & Workflow Runbook

Documented triage process, SLA definitions by severity class, escalation paths, and suppression approval workflow for your security and engineering teams.

Developer Training Deck & Cheat Sheets

Workshop slide deck and per-language secure coding cheat sheets covering the top vulnerability classes found — a durable reference for ongoing developer education.

Metrics Dashboard Template

Pre-built dashboard (compatible with your CI/CD platform or Grafana) tracking finding trends, mean time to remediation, and pipeline pass rates across sprints.

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