After advocating for a comprehensive shift-left strategy, our team finally enabled GitHub Advanced Security (GHAS) across our primary monorepo—a ~50-repository structure housing our core platform services. The goal was to move beyond periodic scanner runs and embed security directly into the PR workflow. After three weeks of full enforcement, the results have been both enlightening and operationally challenging.
**Initial Setup & Configuration**
We opted for a centralized configuration using a `.github` repository for CodeQL and a single, organization-wide enablement of secret scanning. The most critical step was establishing a severity-based pull request blocking policy. We configured the following branch protection rule:
```yaml
Required status checks:
- CodeQL / Analyze (language1)
- CodeQL / Analyze (language2)
- Secret Scanning
```
**Key Findings & Metrics**
* **Initial Flood of Findings**: The first week generated over 1,200 alerts, predominantly from CodeQL. The breakdown was roughly:
* 65% were from legacy code (pre-existing, never scanned with this depth).
* 30% were from third-party library patterns (CodeQL's security queries).
* 5% were newly introduced in active PRs.
* **Secret Scanning is a Game-Changer**: It immediately flagged 8 live, albeit low-privilege, API keys in configuration files that had been missed in manual reviews. This justified the cost alone.
* **The Triage Burden is Real**: The volume necessitated a dedicated "Security Triage" rotation among senior engineers for the first two weeks. We heavily utilized:
* `gh ghas` CLI for bulk status updates.
* Custom labels (`false-positive`, `accepted-risk`) to manage workflow.
* **Performance Impact**: CodeQL analysis added ~12-14 minutes to our already substantial monorepo build times. We mitigated this by caching the CodeQL database between runs, which shaved off ~8 minutes.
**Current Status & Adjusted Workflow**
By week three, after mass dismissal of acceptable-risk legacy patterns, we've settled into a steady state of ~15-30 new alerts per week. The critical shift is that **zero high or critical-severity issues are now merging**. Our developer workflow has adapted:
1. PR is opened → CodeQL/Secret Scanning triggers.
2. Developers review **their own** security alerts as part of the PR checklist.
3. Any new finding must be addressed or dismissed with a documented comment before merge.
4. A nightly Slack digest from the GHAS API keeps the team aware of the overall alert landscape.
**Pitfalls & Recommendations**
* **Start with a Pilot**: Enable on a single, active repository first to gauge noise levels.
* **Budget for Triage Time**: The initial overhead is significant. Do not roll this out during a critical delivery period.
* **Customize Your CodeQL Queries**: We disabled several generic "bad practice" queries that were too noisy for our context, focusing on true security vulnerabilities.
* **Integrate Findings into Existing Ticketing**: We automated the creation of low-priority issues for older, non-critical alerts to avoid them being forgotten.
The overall ROI is positive, but it's not a "set and forget" tool. It demands process adaptation and ongoing curation. The visibility it provides, however, is unparalleled.
--crusader
Commit early, deploy often, but always rollback-ready.
The initial flood you describe, with 65% of alerts from legacy code, mirrors our experience perfectly. That first wave can be overwhelming for engineering teams not used to this level of scrutiny.
What we found crucial was immediately implementing a triage workflow in parallel with the blocking rules. We used GitHub's "dismissal reasons" and a simple label system to mark legacy findings for later review, which prevented PR gridlock. It allowed us to keep the pipeline moving for new code while creating a backlog for the historical issues.
Did you also see a significant difference in alert velocity between the codebases written in typed versus untyped languages? Our TypeScript services had a dramatically lower rate of new critical findings after the initial purge compared to our older JavaScript modules.