DevSecOps mental model and threat-driven controls
Integrate security into delivery by connecting assets and threats to preventive, detective and recovery controls with reviewable evidence.
Open module →Learn security as an engineering evidence loop: threat → control → evidence → decision. The core labs are account-free and teach reasoning first; optional labs map the concepts to Gitleaks, Semgrep, Trivy, Syft, Grype, Cosign and GitHub Actions.
0 of 12 curriculum modules completed · 0/12 currently published modules complete · 0 with lab + knowledge-check evidence.
Every module connects a security problem to a control, evidence and an operational decision.
Integrate security into delivery by connecting assets and threats to preventive, detective and recovery controls with reviewable evidence.
Open module →Prevent credentials from entering source control, detect historical leaks, and respond correctly when a secret is exposed.
Open module →Use static analysis to find risky code patterns while keeping rule scope, data flow, validation and human review explicit.
Open module →Find known vulnerabilities and configuration risks across dependencies, container images and infrastructure code without confusing presence with exploitability.
Open module →Create and reason about software bills of materials so releases have a durable component inventory that can be rescanned later.
Open module →Use SBOM-driven vulnerability analysis while separating scanner confidence, fix availability, exploitability and exception policy.
Open module →Protect artifact integrity with signatures and provenance so consumers can verify what was built, by whom, and from which source/build process.
Open module →Harden CI/CD with least-privilege tokens, explicit permissions, short-lived OIDC credentials, reviewed dependencies and protected deployment environments.
Open module →Turn scanner output into consistent promotion decisions with explicit policy, evidence retention, accountable exceptions and fail-safe behavior.
Open module →Compose security controls into a source→build→artifact→promote flow that scans once, promotes immutable artifacts and separates build from deploy authority.
Open module →Connect pre-deployment security evidence to runtime detection, admission/verification, incident response and backlog improvement.
Open module →Design and validate a release evidence bundle that proves the expected source, scans, SBOM, vulnerability disposition, artifact identity, signature/provenance, policy decision and deployment verification.
Open module →bash, Python 3, text/JSON files. No cloud account required.
Gitleaks, Semgrep, Trivy, Syft, Grype, Cosign and GitHub Actions concepts.
Use synthetic secrets and disposable artifacts. Never paste real credentials into training scans.
30 questions are selected from an 84-question bank covering threat modeling, secrets, SAST, dependencies/containers/IaC, SBOM/vulnerability management, CI identity/signing/policy and runtime troubleshooting.
The capstone rejects digest drift, missing evidence, expired exceptions and rollback gaps. It validates relationships—not checkbox presence.