scanning-docker-images-with-trivy

name: scanning-docker-images-with-trivy description: Trivy is a comprehensive open-source vulnerability scanner by Aqua Security that detects vulnerabilities in OS packages, language-specific dependencies, misconfigurations, secrets, and license violati domain: cybersecurity subdomain: container-security tags:

• containers
• docker
• security
• trivy
• vulnerability-scanning version: '1.0' author: mahipal license: Apache-2.0 nist_csf:
• PR.PS-01
• PR.IR-01
• ID.AM-08
• DE.CM-01

Scanning Docker Images with Trivy

Overview

Trivy is a comprehensive open-source vulnerability scanner by Aqua Security that detects vulnerabilities in OS packages, language-specific dependencies, misconfigurations, secrets, and license violations within container images. It integrates into CI/CD pipelines and supports multiple output formats including SARIF, CycloneDX, and SPDX.

When to Use

• When conducting security assessments that involve scanning docker images with trivy
• When following incident response procedures for related security events
• When performing scheduled security testing or auditing activities
• When validating security controls through hands-on testing

Prerequisites

• Docker Engine 20.10+
• Trivy v0.50+ installed
• Internet access for vulnerability database updates
• Container registry credentials (for private registries)

Core Concepts

This section covers core concepts for scanning docker images with trivy.

• Ensure all prerequisites are met before proceeding
• Follow the documented workflow steps in sequence
• Record results and any anomalies encountered during this phase

Scanner Types

Severity Levels

• CRITICAL: CVSS 9.0-10.0 - Immediate action required
• HIGH: CVSS 7.0-8.9 - Fix before production deployment
• MEDIUM: CVSS 4.0-6.9 - Plan remediation
• LOW: CVSS 0.1-3.9 - Accept or fix opportunistically
• UNKNOWN: Unscored - Evaluate manually

Vulnerability Database

Trivy uses multiple vulnerability databases:

• NVD (National Vulnerability Database)
• Red Hat Security Data
• Alpine SecDB
• Debian Security Tracker
• Ubuntu CVE Tracker
• Amazon Linux Security Center
• GitHub Advisory Database

Workflow

1. Prepare the environment — ensure write-blocker is connected and test workstation is ready
2. Document the source — record device serial, model, and pre-acquisition hash
3. Acquire the image — use the appropriate tool with hash verification enabled
4. Verify integrity — compare source and image hashes; document any discrepancies
5. Analyze and report — perform the analysis and document findings with chain of custody

Step 1: Install Trivy

# Linux (apt)
sudo apt-get install wget apt-transport-https gnupg lsb-release
wget -qO - https://aquasecurity.github.io/trivy-repo/deb/public.key | gpg --dearmor | sudo tee /usr/share/keyrings/trivy.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/trivy.gpg] https://aquasecurity.github.io/trivy-repo/deb $(lsb_release -sc) main" | sudo tee -a /etc/apt/sources.list.d/trivy.list
sudo apt-get update && sudo apt-get install trivy

# macOS
brew install trivy

# Docker
docker pull aquasecurity/trivy:latest

Step 2: Basic Image Scanning

# Scan a public image
trivy image python:3.12-slim

# Scan with severity filter
trivy image --severity CRITICAL,HIGH nginx:latest

# Ignore unfixed vulnerabilities
trivy image --ignore-unfixed alpine:3.19

# Scan local image
docker build -t myapp:latest .
trivy image myapp:latest

# Scan from tar archive
docker save myapp:latest -o myapp.tar
trivy image --input myapp.tar

Step 3: Advanced Scanning Options

# All scanners (vuln + misconfig + secret + license)
trivy image --scanners vuln,misconfig,secret,license myapp:latest

# Generate SBOM in CycloneDX format
trivy image --format cyclonedx --output sbom.cdx.json myapp:latest

# Generate SBOM in SPDX format
trivy image --format spdx-json --output sbom.spdx.json myapp:latest

# JSON output for programmatic processing
trivy image --format json --output results.json myapp:latest

# SARIF output for GitHub Security tab
trivy image --format sarif --output results.sarif myapp:latest

# Template-based output
trivy image --format template --template "@contrib/html.tpl" --output report.html myapp:latest

# Scan specific layers only
trivy image --list-all-pkgs myapp:latest

Step 4: Scanning Kubernetes Manifests

# Scan Dockerfile for misconfigurations
trivy config Dockerfile

# Scan Kubernetes manifests
trivy config k8s-deployment.yaml

# Scan Helm charts
trivy config ./helm-chart/

# Scan Terraform files
trivy config ./terraform/

Step 5: CI/CD Integration

# GitHub Actions
name: Trivy Container Scan
on: push

jobs:
  scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Build image
        run: docker build -t myapp:${{ github.sha }} .

      - name: Run Trivy vulnerability scanner
        uses: aquasecurity/trivy-action@master
        with:
          image-ref: myapp:${{ github.sha }}
          format: sarif
          output: trivy-results.sarif
          severity: CRITICAL,HIGH
          exit-code: 1

      - name: Upload Trivy scan results
        uses: github/codeql-action/upload-sarif@v3
        if: always()
        with:
          sarif_file: trivy-results.sarif

      - name: Generate SBOM
        uses: aquasecurity/trivy-action@master
        with:
          image-ref: myapp:${{ github.sha }}
          format: cyclonedx
          output: sbom.cdx.json

# GitLab CI
trivy-scan:
  stage: security
  image:
    name: aquasecurity/trivy:latest
    entrypoint: [""]
  script:
    - trivy image --exit-code 1 --severity CRITICAL,HIGH
        --format json --output gl-container-scanning-report.json
        $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
  artifacts:
    reports:
      container_scanning: gl-container-scanning-report.json

Step 6: Policy Enforcement with .trivyignore

# .trivyignore - Ignore specific CVEs with expiry
# Accepted risk: low-impact vulnerability in dev dependency
CVE-2023-12345 exp:2025-06-01

# False positive: not exploitable in our configuration
CVE-2024-67890

# Vendor will not fix
CVE-2023-11111

Step 7: Scan Private Registry Images

# Docker Hub (uses ~/.docker/config.json)
trivy image myregistry.azurecr.io/myapp:latest

# ECR
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin <account>.dkr.ecr.us-east-1.amazonaws.com
trivy image <account>.dkr.ecr.us-east-1.amazonaws.com/myapp:latest

# GCR
trivy image gcr.io/my-project/myapp:latest

# With explicit credentials
TRIVY_USERNAME=user TRIVY_PASSWORD=pass trivy image registry.example.com/myapp:latest

Validation Commands

# Verify Trivy installation
trivy version

# Update vulnerability database
trivy image --download-db-only

# Quick scan with table output
trivy image --severity CRITICAL python:3.12

# Verify no CRITICAL vulnerabilities
trivy image --exit-code 1 --severity CRITICAL myapp:latest
echo "Exit code: $?"  # 0 = no vulns, 1 = vulns found

When NOT to Use

• You need to perform manual testing (use performing-* skills)
• Task is about analyzing scan results (use analyzing-* skills)
• You need to implement scanning tools (use implementing-* skills)
• Task is about building scanning infrastructure (use building-* skills)
• You don't have network access to targets
• Task requires compliance validation (use auditing-* skills)

Red Flags

• Performing actions without explicit written authorization from the asset owner
• Testing against production systems without a defined scope and rules of engagement
• Failing to use write-blockers when acquiring forensic evidence
• Not verifying hash integrity before and after imaging
• Modifying original evidence during analysis

Verification

• All steps executed successfully against a test environment before production use
• Output documented with screenshots or logs demonstrating expected behavior
• Hash values computed and verified match between source and image
• Chain of custody log complete with timestamps and examiner names
• Analysis tools and versions documented for reproducibility

References

• Trivy Documentation
• Trivy GitHub Repository
• Trivy GitHub Action
• Aqua Security - Trivy Scanner Guide

Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality

Anti-Rationalization