A quarterly PCI compliance audit revealed multiple critical findings, including unencrypted data storage, lack of network segmentation, and insufficient access controls.

• Reviewed the detailed audit report findings.

• Conducted gap analysis against PCI-DSS requirements.

• Performed network scanning to verify reported vulnerabilities.

• Analyzed AWS Config rules and Security Hub findings.

Security was treated as a periodic audit concern rather than being built into the development and operations process. No continuous compliance monitoring was in place.

• Implemented immediate remediation for critical findings:

• Encrypted sensitive data at rest and in transit

• Implemented proper network segmentation with security groups

• Enforced least privilege access controls

• Created a 90-day remediation plan for all findings.

• Engaged with auditors to demonstrate progress.

Compliance is an ongoing process, not a point-in-time activity.

• Implement compliance as code using tools like Chef InSpec or AWS Config.

• Conduct regular internal audits before external assessments.

• Integrate security and compliance checks into CI/CD pipelines.

• Maintain a continuous compliance monitoring program.

• Train development and operations teams on security requirements.

During pre-release security scanning, multiple critical vulnerabilities were found in production container images, including remote code execution flaws in base images.

• Ran detailed vulnerability scans using Trivy and Clair.

• Analyzed the dependency tree to identify vulnerable components.

• Checked for available patches and updates for affected packages.

• Reviewed the process for keeping base images updated.

The team was using outdated base images with known vulnerabilities. No process existed for regularly updating and patching base images.

• Updated all base images to the latest secure versions.

• Removed unnecessary packages to reduce the attack surface.

• Implemented vulnerability scanning in the CI/CD pipeline.

• Created a process for regular base image updates.

Container security requires ongoing maintenance, not just initial hardening.

• Use minimal base images like distroless or Alpine.

• Implement automated base image updates with testing.

• Scan images at build time and prevent vulnerable images from being pushed.

• Maintain a catalog of approved base images with regular updates.

• Use runtime security tools to detect and prevent exploitation of vulnerabilities.

A security audit discovered that application pods were logging sensitive information, including database credentials and API keys. These logs were being collected by the centralized logging system and were accessible to multiple teams.

• Examined application logs for sensitive data patterns.

• Reviewed application code for logging practices.

• Checked Kubernetes Secret usage in the application.

• Analyzed log collection and access controls.

• Verified compliance requirements for sensitive data handling.

The application was improperly handling environment variables containing secrets. During startup and error conditions, the application was dumping all environment variables to logs, including those containing sensitive credentials injected from Kubernetes Secrets.

• Short-term: Implemented log redaction in the logging pipeline:

# Fluent Bit configuration for log redaction
[FILTER]
    Name    modify
    Match   *
    Regex   (?i)(password|secret|key|token|credential)[\"\']?\s*[=:]\s*[\"\']?[^\"\'\s]+[\"\']?
    Replace REDACTED

• Long-term: Fixed the application code to properly handle secrets:

// Go example - Before
log.Printf("Environment: %v", os.Environ())
// Go example - After
func sanitizeEnvironment() map[string]string {
    sanitized := make(map[string]string)
    for _, env := range os.Environ() {
        parts := strings.SplitN(env, "=", 2)
        key := parts[0]
        value := parts[1]
        // Redact sensitive values
        if strings.Contains(strings.ToLower(key), "password") ||
           strings.Contains(strings.ToLower(key), "secret") ||
           strings.Contains(strings.ToLower(key), "key") ||
           strings.Contains(strings.ToLower(key), "token") {
            sanitized[key] = "REDACTED"
        } else {
            sanitized[key] = value
        }
    }
    return sanitized
}
log.Printf("Environment: %v", sanitizeEnvironment())

• Implemented log scanning for sensitive data.

• Added security context to prevent access to logs containing secrets.

Application logging requires careful handling of sensitive data to maintain security and compliance.

• Implement secure coding practices for handling secrets.

• Use log redaction at multiple levels (application, collection, storage).

• Conduct regular security reviews of logging practices.

• Train developers on proper secret handling.

• Implement automated scanning for secrets in logs and code.

A security incident was detected where an attacker gained access to a production system. Investigation revealed that the entry point was a vulnerable dependency in a container image that had been deployed to production.

• Isolated the affected containers and preserved evidence.

• Performed forensic analysis on the compromised containers.

• Scanned all container images for known vulnerabilities.

• Reviewed the CI/CD pipeline for security controls.

• Traced the provenance of the affected container image.

The container image included a vulnerable version of a popular open-source library. The vulnerability was published in the CVE database, but the team had no process for scanning images or updating dependencies. The CI/CD pipeline allowed images to be deployed without security validation.

• Short-term: Removed all affected containers and deployed clean versions with patched dependencies.

• Long-term: Implemented comprehensive container security scanning:

# Trivy scanner in GitHub Actions
name: Container Security Scan
on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]
jobs:
  scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Build image
        run: docker build -t myapp:${{ github.sha }} .
      - name: Scan image
        uses: aquasecurity/trivy-action@master
        with:
          image-ref: myapp:${{ github.sha }}
          format: 'sarif'
          output: 'trivy-results.sarif'
          severity: 'CRITICAL,HIGH'
          exit-code: '1'
          ignore-unfixed: true
      - name: Upload scan results
        uses: github/codeql-action/upload-sarif@v2
        with:
          sarif_file: 'trivy-results.sarif'

• Implemented Software Bill of Materials (SBOM) generation:

# Generate SBOM with Syft
syft packages docker:myapp:latest -o spdx-json > sbom.json
# Store SBOM with image metadata
docker buildx build --tag myapp:latest \
  --label org.opencontainers.image.created="$(date -u +%Y-%m-%dT%H:%M:%SZ)" \
  --label org.opencontainers.image.revision="$(git rev-parse HEAD)" \
  --label org.opencontainers.image.sbom="$(cat sbom.json | base64)" \
  .

• Added admission control to block vulnerable images:

# Kubernetes OPA Gatekeeper policy
apiVersion: constraints.gatekeeper.sh/v1beta1
kind: K8sImageVulnerabilities
metadata:
  name: block-high-vulnerabilities
spec:
  match:
    kinds:
      - apiGroups: [""]
        kinds: ["Pod"]
    namespaces:
      - "production"
  parameters:
    maxSeverity: "MEDIUM"

Container security requires a comprehensive approach to the entire supply chain.

• Implement vulnerability scanning in CI/CD pipelines.

• Generate and store SBOMs for all container images.

• Use minimal or distroless base images to reduce attack surface.

• Implement automated dependency updates.

• Use admission controllers to enforce security policies.