GitHub Advanced Security + Defender for Cloud: AI-Powered DevSecOps - Microsoft Ignite 2025
Assessment and Baseline (2-3 weeks)
- • Inventory code repositories (GitHub, Azure DevOps, GitLab, Bitbucket)
- • Assess current security posture (existing tools, vulnerability backlog, remediation velocity)
- • Identify critical applications and high-risk code
- • Establish baseline metrics (findings per repo, time to remediate, developer engagement)
- • Define success criteria (target backlog reduction, remediation SLAs, deployment velocity)
GitHub Advanced Security Deployment (3-4 weeks)
- • Enable GHAS for pilot repositories (2-3 critical applications)
- • Configure CodeQL scanning (choose language support, custom queries if needed)
- • Enable secret scanning with partner notifications
- • Activate Dependabot security updates
- • Set up security policies (branch protection, required reviews, status checks)
- • Train developers on GHAS workflows (PR feedback, fixing vulnerabilities, using Copilot suggestions)
Defender for Cloud Integration (4-6 weeks)
- • Deploy Defender for Cloud across Azure, AWS, GCP workloads
- • Enable Defender for DevOps (connects to GitHub, Azure DevOps)
- • Configure runtime monitoring for production applications
- • Set up cloud security posture management (CSPM)
- • Enable attack path analysis and cloud workload protection
- • Configure integration with GitHub (code-to-cloud correlation)
Intelligent Prioritization Setup (2-3 weeks)
- • Define prioritization rules (production exposure, data sensitivity, privilege level)
- • Configure automated issue creation for high-priority findings
- • Set up notification workflows (Slack, Teams, email based on severity)
- • Create security dashboard for leadership visibility
- • Establish SLAs per severity level (Critical: 48 hours, High: 7 days, etc.)
AI-Powered Remediation Enablement (4-6 weeks)
- • Deploy GitHub Copilot enterprise-wide (or to developer pilot group)
- • Enable Copilot Autofix for security vulnerabilities
- • Train developers on using Copilot for security remediation
- • Pilot agentic workflows (AI-generated fix PRs for low-risk vulnerabilities)
- • Measure adoption and effectiveness (fix acceptance rate, time savings)
Scale and Optimize (Ongoing)
- • Expand GHAS to all repositories in phased rollout
- • Refine prioritization rules based on real-world effectiveness
- • Monitor metrics weekly (backlog trends, remediation velocity, deployment impact)
- • Continuously improve Copilot training (feedback on fix suggestions)
- • Expand agentic automation to more vulnerability classes
- • Measure business impact (security incidents prevented, audit efficiency, developer productivity)