Container Scanning and SBOM¶

Overview¶

Scan an image for CVEs, produce a Software Bill of Materials (SBOM), and decide fix vs accept risk for a release gate.

Trivy, Docker Scout, and registry scanners find known vulnerabilities. An SBOM inventories packages for compliance and incident response. Scanning without a triage process becomes noise.

This is a core tutorial in Module 12 · Container Scanning of the REBASH Academy Docker for Cloud & DevOps Engineers series — written for Cloud, DevOps, Platform, and SRE engineers.

Prerequisites¶

Docker Security Hardening

Learning Objectives¶

By the end of this tutorial, you will be able to:

Run Trivy (or Scout) against a local image
Explain CRITICAL/HIGH triage
Generate an SBOM (Syft/Trivy)
List hardening moves that reduce findings

Architecture¶

This topic’s control points and relationships are shown below.

Theory¶

What¶

Vulnerability scanning analyses image contents for known Common Vulnerabilities and Exposures (CVEs). A Software Bill of Materials (SBOM) lists packages and dependencies you shipped. Tools such as Trivy, Docker Scout, Syft, and Grype integrate into CI to gate or inform releases.

Why¶

You cannot patch what you cannot see. Base OS packages and language libraries both introduce risk. SBOMs support incident response (“are we affected?”) and emerging compliance expectations. Failing CI on CRITICAL findings for production images is a common policy.

How it works¶

Scanners index installed packages and match them to vulnerability databases. Results include severity, fixed versions, and sometimes misconfiguration checks (Dockerfile smells). Generate an SBOM at build time and store it with the artefact. Fix order is usually: upgrade base image → upgrade application dependencies → rebuild → accept residual risk with a ticket if needed. Do not ignore OS packages because “we only care about the app language”.

Tool	Role
Trivy	OSS vuln + misconfig + SBOM
Docker Scout	Hub-integrated insights
Syft / Grype	SBOM + scan ecosystem

Key concepts¶

CVE noise — triage by reachability and exploitability when possible
Rebuild cadence — periodic rebuilds pick up base patches
Private base images — control inheritance
Sign + scan — complementary supply-chain controls

Wire scanners into both pull-request and main-branch pipelines so developers see findings early. Keep an allow-list process for accepted risks with expiry dates — permanent mute rules become invisible debt. After a major base-image upgrade, re-scan and redeploy even if application code did not change.

Common pitfalls¶

Scanning once at project start and never again
Suppressing all CVEs to keep CI green
Treating SBOM generation as paperwork without storing it
Scanning only the final stage while shipping a fat single-stage image

Hands-on Lab¶

Objective¶

Build a small lab image, attach a placeholder SBOM JSON, run Trivy when available (or a documented fallback), and validate output with a check script.

Prerequisites¶

Docker Engine or Docker Desktop
python3 for the check script
Optional: Trivy installed (trivy --version)

Lab environment¶

Workspace: ~/rebash-docker/module-12

Terminal

mkdir -p ~/rebash-docker/module-12 && cd ~/rebash-docker/module-12

Real-world scenario¶

Your pipeline must block merges when critical CVEs appear in base images. You build a tiny service image, record an SBOM stub for traceability, scan with Trivy (or a fallback that still produces scan-results.txt), and gate promotion with check-scan.sh.

Step-by-step tasks¶

Task 1 – Build a scannable lab image¶

Create Dockerfile:

Dockerfile

FROM alpine:3.20
RUN apk add --no-cache python3 py3-pip \
    && pip3 install --no-cache-dir flask==3.0.3
WORKDIR /app
COPY app.py .
USER nobody
EXPOSE 5000
CMD ["python3", "app.py"]

Create app.py:

app.py

from flask import Flask
app = Flask(__name__)

@app.get("/health")
def health():
    return {"status": "ok", "service": "rebash-scan-lab"}

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5000)

Build and smoke-test:

Terminal

cd ~/rebash-docker/module-12
docker build -t rebash-scan-lab:1.0.0 .
docker run -d --name rebash-scan-18120 -p 18120:5000 rebash-scan-lab:1.0.0
sleep 2
curl -sS http://127.0.0.1:18120/health | tee health-scan.txt
grep -q '"status":"ok"' health-scan.txt

Expected output

health-scan.txt contains JSON with "status":"ok".

Task 2 – Add SBOM placeholder and scan¶

Create sbom-placeholder.json:

sbom-placeholder.json

{
  "bomFormat": "CycloneDX",
  "specVersion": "1.5",
  "version": 1,
  "metadata": {
    "component": {
      "type": "container",
      "name": "rebash-scan-lab",
      "version": "1.0.0"
    }
  },
  "components": [
    {"type": "library", "name": "flask", "version": "3.0.3"},
    {"type": "library", "name": "alpine", "version": "3.20"}
  ]
}

Scan with Trivy if present; otherwise document packages via docker inspect:

Terminal

cd ~/rebash-docker/module-12
if command -v trivy >/dev/null 2>&1; then
  trivy image --severity HIGH,CRITICAL --format table rebash-scan-lab:1.0.0 | tee scan-results.txt
else
  echo "Trivy not installed — fallback: inspect rootfs layers" | tee scan-results.txt
  docker inspect rebash-scan-lab:1.0.0 --format '{{ "{{" }}join .RootFS.Layers "\n"{{ "}}" }}' >> scan-results.txt
fi
test -s scan-results.txt
test -s sbom-placeholder.json

Expected output

scan-results.txt is non-empty; sbom-placeholder.json validates as JSON.

Task 3 – Gate with check script¶

Create check-scan.sh:

check-scan.sh

#!/usr/bin/env bash
set -euo pipefail
RESULTS="${1:-scan-results.txt}"
SBOM="${2:-sbom-placeholder.json}"
test -s "$RESULTS"
python3 -c "import json; json.load(open('$SBOM'))"
if grep -qiE 'CRITICAL|HIGH' "$RESULTS" 2>/dev/null; then
  echo "Review required: HIGH/CRITICAL findings present"
  exit 2
fi
echo "Scan gate passed (or fallback documented)"

Run the gate:

Terminal

cd ~/rebash-docker/module-12
chmod +x check-scan.sh
./check-scan.sh scan-results.txt sbom-placeholder.json | tee gate-result.txt
test -s gate-result.txt

Expected output

Script exits 0 or 2 with a message in gate-result.txt; SBOM JSON parses successfully.

Validation steps¶

Lab image builds and /health responds
sbom-placeholder.json is valid CycloneDX-shaped JSON
scan-results.txt exists from Trivy or documented fallback
check-scan.sh validates both artefacts
Cleanup removes container and image

Common errors and fixes¶

Error	Cause	Fix
`trivy: command not found`	Trivy not installed	Use the fallback block in Task 2; install Trivy for full CVE output
Flask import error in container	Wrong Python path	Ensure `CMD ["python3", "app.py"]` and packages installed in Dockerfile
Gate exits 2	Real CVEs in base image	Expected on some hosts — document findings; pin a smaller base if needed
Port 18120 in use	Previous lab	`docker rm -f rebash-scan-18120`

Challenge exercise¶

Export a real SBOM with trivy image --format cyclonedx rebash-scan-lab:1.0.0 -o sbom-cyclonedx.json and extend check-scan.sh to require that file when Trivy is available.

Learning outcomes¶

Built a minimal image suitable for vulnerability scanning
Attached SBOM metadata for supply-chain traceability
Ran Trivy or a honest fallback that still produces evidence
Automated a scan gate with a shell check script

Cleanup¶

Terminal

docker rm -f rebash-scan-18120 2>/dev/null || true
docker rmi rebash-scan-lab:1.0.0 2>/dev/null || true
rm -f ~/rebash-docker/module-12/*.txt

Validation¶

Lab commands run under ~/rebash-docker/module-12/
You can explain each Theory section in your own words
You used modern tooling where it applies to this topic
You can describe one production failure mode for this topic

Code Walkthrough¶

Production practice for Container Scanning and SBOM always combines:

Inspect before you change (status, plan, logs, dry-run)
Prefer reversible, documented changes (Git, IaC, drop-ins, version pins)
Capture evidence (command output, pipeline logs) for handovers
Prefer current tools and APIs over legacy shortcuts
Least privilege — escalate credentials only when required

Keep runbooks short enough to follow under pressure. Automate checks; keep humans for judgement.

Security Considerations¶

Treat credentials and tokens for docker as privileged — never commit them
Prefer short-lived auth (OIDC, roles, SSO) over long-lived keys
Validate blast radius before apply/deploy/delete operations
Restrict who can approve production changes
Collect audit logs; limit who can read sensitive traces

Common Mistakes¶

Scanning once at project start and never again

Validate assumptions against the Theory section and official docs before changing production.

Suppressing all CVEs to keep CI green

Lab shortcuts (open security groups, admin roles, skip approvals) must not ship unchanged.

Changing production without a rollback path

Always know how to revert (previous artefact, prior release, state rollback, DNS failback).

Best Practices¶

Encode Container Scanning and SBOM changes as code and review them in pull requests
Pin versions (images, modules, actions, provider plugins)
Separate environments with clear promotion gates
Alert on symptoms with runbooks attached
Destroy lab resources; tag everything with owner and expiry where possible

Troubleshooting¶

Symptom	Likely cause	Fix
Auth / permission denied	Wrong identity, policy, or scope	Check caller identity, roles, and least-privilege policies
Timeout / no route	Network, DNS, security group, or endpoint	Trace path, DNS, and allow-lists before retrying
Drift / unexpected plan	Manual change or wrong state/workspace	Reconcile desired vs actual; avoid click-ops on managed resources
Pipeline/job red	Flaky step, cache, or missing secret	Read failing step logs; bisect recent workflow/config changes
Cost spike	Idle load balancer, NAT, oversized compute	Inventory billable resources; stop/delete labs promptly

Summary¶

Container Scanning and SBOM is essential for Cloud and DevOps engineers working with docker. Practise the lab until the inspection and change path is muscle memory, then continue the track.

Interview Questions¶

What is an SBOM and why store it in CI?
How do you triage a CRITICAL CVE in a base image?
Scanner false positives — how do you handle them?
When should a pipeline fail on findings?
Difference between image scan and runtime detection?

Sample answer — question 2

Confirm the package is present in the final image and whether a fixed base exists.

Sample answer — question 4

Gate production on policy and keep SBOMs as artifacts for incident response.

References¶

Trivy · Docker Scout

Container Scanning and SBOM¶

Overview¶

Prerequisites¶

Learning Objectives¶

Architecture¶

Theory¶

What¶

Why¶

How it works¶

Key concepts¶

Common pitfalls¶

Hands-on Lab¶

Objective¶

Prerequisites¶

Lab environment¶

Real-world scenario¶

Step-by-step tasks¶

Task 1 – Build a scannable lab image¶

Task 2 – Add SBOM placeholder and scan¶

Task 3 – Gate with check script¶

Validation steps¶

Common errors and fixes¶

Challenge exercise¶

Learning outcomes¶

Cleanup¶

Validation¶

Code Walkthrough¶

Security Considerations¶

Common Mistakes¶

Best Practices¶

Troubleshooting¶

Summary¶

Interview Questions¶

Related Tutorials¶

References¶