SKILLS/analyzing-docker-container-forensics/SKILL.md
Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.
npx skillsauth add pinkpixel-dev/skills-collection-1 analyzing-docker-container-forensicsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
# List all containers (including stopped)
docker ps -a --no-trunc > /cases/case-2024-001/docker/container_list.txt
# Inspect the compromised container
CONTAINER_ID="abc123def456"
docker inspect $CONTAINER_ID > /cases/case-2024-001/docker/container_inspect.json
# Export container filesystem as tarball (preserves current state)
docker export $CONTAINER_ID > /cases/case-2024-001/docker/container_export.tar
# Create an image from the container's current state
docker commit $CONTAINER_ID forensic-evidence:case-2024-001
docker save forensic-evidence:case-2024-001 > /cases/case-2024-001/docker/container_image.tar
# Capture container logs
docker logs $CONTAINER_ID --timestamps > /cases/case-2024-001/docker/container_logs.txt 2>&1
# Capture running processes (if container is still running)
docker top $CONTAINER_ID > /cases/case-2024-001/docker/container_processes.txt
# Capture network connections
docker exec $CONTAINER_ID netstat -tlnp 2>/dev/null > /cases/case-2024-001/docker/container_network.txt
# Copy specific files from the container
docker cp $CONTAINER_ID:/var/log/ /cases/case-2024-001/docker/container_var_log/
docker cp $CONTAINER_ID:/tmp/ /cases/case-2024-001/docker/container_tmp/
docker cp $CONTAINER_ID:/etc/passwd /cases/case-2024-001/docker/container_passwd
# Hash all exported evidence
sha256sum /cases/case-2024-001/docker/*.tar > /cases/case-2024-001/docker/evidence_hashes.txt
# Install dive for image layer analysis
wget https://github.com/wagoodman/dive/releases/latest/download/dive_linux_amd64.deb
sudo dpkg -i dive_linux_amd64.deb
# Analyze image layers interactively
dive forensic-evidence:case-2024-001
# Non-interactive layer analysis
dive forensic-evidence:case-2024-001 --ci --json /cases/case-2024-001/docker/dive_analysis.json
# Extract and examine individual layers
mkdir -p /cases/case-2024-001/docker/layers/
tar -xf /cases/case-2024-001/docker/container_image.tar -C /cases/case-2024-001/docker/layers/
# List the image manifest and layer order
cat /cases/case-2024-001/docker/layers/manifest.json | python3 -m json.tool
# Examine each layer for changes
for layer in /cases/case-2024-001/docker/layers/*/layer.tar; do
echo "=== Layer: $(dirname $layer | xargs basename) ==="
tar -tf "$layer" | head -20
echo "..."
done
# Use container-diff to compare with original base image
# Install container-diff
curl -LO https://storage.googleapis.com/container-diff/latest/container-diff-linux-amd64
chmod +x container-diff-linux-amd64
# Compare committed image with original
./container-diff-linux-amd64 diff daemon://nginx:latest daemon://forensic-evidence:case-2024-001 \
--type=file --type=apt --type=history --json \
> /cases/case-2024-001/docker/container_diff.json
# Docker data directory (default: /var/lib/docker/)
DOCKER_ROOT="/mnt/evidence/var/lib/docker"
# Examine overlay2 filesystem layers
ls -la $DOCKER_ROOT/overlay2/
# Find the container's merged filesystem
CONTAINER_HASH=$(docker inspect $CONTAINER_ID --format '{{.GraphDriver.Data.MergedDir}}' 2>/dev/null)
# Or manually from forensic image:
# Look in /var/lib/docker/containers/<container_id>/config.v2.json
# Analyze container configuration files
cat $DOCKER_ROOT/containers/$CONTAINER_ID/config.v2.json | python3 -m json.tool \
> /cases/case-2024-001/docker/container_config.json
# Check Docker daemon configuration
cat /mnt/evidence/etc/docker/daemon.json 2>/dev/null > /cases/case-2024-001/docker/daemon_config.json
# Examine Docker events log
cat $DOCKER_ROOT/containers/$CONTAINER_ID/*.log > /cases/case-2024-001/docker/container_json_logs.txt
# Check for volume mounts (potential host filesystem access)
python3 << 'PYEOF'
import json
with open('/cases/case-2024-001/docker/container_inspect.json') as f:
data = json.load(f)
inspect = data[0] if isinstance(data, list) else data
print("=== CONTAINER SECURITY ANALYSIS ===\n")
# Check mounts
print("Volume Mounts:")
for mount in inspect.get('Mounts', []):
rw = "READ-WRITE" if mount.get('RW') else "READ-ONLY"
print(f" {mount.get('Source', 'N/A')} -> {mount.get('Destination', 'N/A')} ({rw})")
if mount.get('Source') in ('/', '/etc', '/var', '/root') and mount.get('RW'):
print(f" WARNING: Sensitive host path mounted read-write!")
# Check privileged mode
host_config = inspect.get('HostConfig', {})
if host_config.get('Privileged'):
print("\nWARNING: Container was running in PRIVILEGED mode!")
# Check capabilities
cap_add = host_config.get('CapAdd', [])
if cap_add:
print(f"\nAdded Capabilities: {cap_add}")
dangerous_caps = ['SYS_ADMIN', 'SYS_PTRACE', 'NET_ADMIN', 'SYS_MODULE']
for cap in cap_add:
if cap in dangerous_caps:
print(f" WARNING: Dangerous capability: {cap}")
# Check PID namespace
if host_config.get('PidMode') == 'host':
print("\nWARNING: Container shares host PID namespace!")
# Check network mode
if host_config.get('NetworkMode') == 'host':
print("\nWARNING: Container shares host network namespace!")
# Check user
user = inspect.get('Config', {}).get('User', 'root (default)')
print(f"\nRunning as user: {user}")
# Check environment variables for secrets
env_vars = inspect.get('Config', {}).get('Env', [])
print(f"\nEnvironment Variables: {len(env_vars)}")
for env in env_vars:
key = env.split('=')[0]
if any(s in key.upper() for s in ['PASSWORD', 'SECRET', 'KEY', 'TOKEN', 'CREDENTIAL']):
print(f" SENSITIVE: {key}=***REDACTED***")
PYEOF
# Compare container filesystem to original image
docker diff $CONTAINER_ID > /cases/case-2024-001/docker/filesystem_changes.txt
# A = Added, C = Changed, D = Deleted
# Analyze changes
python3 << 'PYEOF'
added = []
changed = []
deleted = []
with open('/cases/case-2024-001/docker/filesystem_changes.txt') as f:
for line in f:
line = line.strip()
if line.startswith('A '):
added.append(line[2:])
elif line.startswith('C '):
changed.append(line[2:])
elif line.startswith('D '):
deleted.append(line[2:])
print(f"Files Added: {len(added)}")
print(f"Files Changed: {len(changed)}")
print(f"Files Deleted: {len(deleted)}")
# Flag suspicious additions
suspicious = [f for f in added if any(s in f for s in
['/tmp/', '/dev/shm/', '/root/', '.sh', '.py', '.elf', 'reverse', 'shell', 'backdoor'])]
if suspicious:
print(f"\nSuspicious Added Files:")
for f in suspicious:
print(f" {f}")
# Flag suspicious changes
sus_changed = [f for f in changed if any(s in f for s in
['/etc/passwd', '/etc/shadow', '/etc/crontab', '/etc/ssh', '.bashrc'])]
if sus_changed:
print(f"\nSuspicious Changed Files:")
for f in sus_changed:
print(f" {f}")
PYEOF
# Extract and examine the container export
mkdir -p /cases/case-2024-001/docker/container_fs/
tar -xf /cases/case-2024-001/docker/container_export.tar -C /cases/case-2024-001/docker/container_fs/
# Scan for webshells and malicious files
find /cases/case-2024-001/docker/container_fs/tmp/ -type f -exec file {} \;
find /cases/case-2024-001/docker/container_fs/ -name "*.php" -newer /cases/case-2024-001/docker/container_fs/etc/hostname
# Scan the image for known vulnerabilities
trivy image forensic-evidence:case-2024-001 \
--format json \
--output /cases/case-2024-001/docker/vulnerability_scan.json
# Scan the exported filesystem
trivy fs /cases/case-2024-001/docker/container_fs/ \
--format table \
--output /cases/case-2024-001/docker/fs_vulnerabilities.txt
# Check for secrets in the image
trivy image forensic-evidence:case-2024-001 \
--scanners secret \
--format json \
--output /cases/case-2024-001/docker/secrets_scan.json
| Concept | Description | |---------|-------------| | Image layers | Read-only filesystem layers stacked to form the container image | | overlay2 | Default Docker storage driver using union filesystem for layers | | Container diff | Comparison of runtime filesystem changes against the original image | | Privileged mode | Container with full host capabilities (bypasses most isolation) | | Docker socket | Unix socket (/var/run/docker.sock) controlling the Docker daemon | | Container escape | Technique for breaking out of container isolation to the host | | Volume mounts | Host filesystem paths made accessible inside the container | | Image history | Record of Dockerfile instructions used to build each layer |
| Tool | Purpose | |------|---------| | docker inspect | Detailed container configuration and state information | | docker diff | Show filesystem changes made in a running/stopped container | | dive | Interactive Docker image layer analysis tool | | container-diff | Google tool for comparing container image contents | | Trivy | Vulnerability scanner for container images and filesystems | | docker-explorer | Forensic tool for offline Docker artifact analysis | | Sysdig | Container runtime security monitoring and forensics | | Falco | Runtime threat detection for containers and Kubernetes |
Scenario 1: Web Application Container Compromise Export the container filesystem, identify webshells in web root, analyze access logs for exploitation attempts, check for added files and modified configurations, examine network connections for C2 communication, review container capabilities for escalation paths.
Scenario 2: Supply Chain Attack via Malicious Image Analyze image layers with dive to identify which layer added malicious content, compare with the official base image using container-diff, check image history for suspicious RUN commands, scan for embedded backdoors and cryptocurrency miners, trace the image pull from registry logs.
Scenario 3: Container Escape Investigation Check if container ran privileged or with dangerous capabilities, examine host filesystem mount points for unauthorized access, review Docker socket mount enabling Docker-in-Docker abuse, analyze host system logs for container escape indicators, check for kernel exploit artifacts.
Scenario 4: Cryptojacking in Container Environment Identify high-CPU containers, export and analyze the container image for mining binaries, check for unauthorized images in the registry, review container creation events for rogue deployments, examine network connections for mining pool communications.
Docker Container Forensics Summary:
Container: abc123def456 (nginx-app)
Image: company/web-app:v2.1
Status: Running (started 2024-01-10 09:00 UTC)
Host: docker-host-01.corp.local
Security Configuration:
Privileged: No
Capabilities Added: NET_ADMIN (WARNING)
Volume Mounts: /var/log -> /host-logs (RW)
Network Mode: bridge
User: root (WARNING)
Filesystem Changes:
Added: 23 files (5 suspicious)
Changed: 12 files (2 suspicious)
Deleted: 0 files
Suspicious Findings:
/tmp/reverse.sh - Reverse shell script (Added)
/var/www/html/.hidden/shell.php - PHP webshell (Added)
/etc/crontab - Modified (persistence cron entry added)
/root/.ssh/authorized_keys - Modified (unauthorized key added)
Vulnerability Scan:
Critical: 3 (CVE-2024-xxxx in base image)
High: 12
Medium: 34
Evidence: /cases/case-2024-001/docker/
testing
When the user wants a full ASO health audit, review their App Store listing quality, or diagnose why their app isn't ranking. Also use when the user mentions "ASO audit", "ASO score", "why am I not ranking", "listing review", or "optimize my app store page". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
testing
Clarify requirements before implementing. Use when serious doubts arise.
tools
Complete reference and build guide for ASI:One (ASI1) — the AI platform by Fetch.ai built for agentic, Web3-native applications. Use this skill IMMEDIATELY and ALWAYS when the user mentions ASI1, ASI:One, Fetch.ai AI API, building with ASI1, integrating ASI:One, asking about ASI1 models, tool calling with ASI1, ASI1 image generation, ASI1 agentic LLM, Agentverse, uagents, Agent Chat Protocol, structured output with ASI1, or OpenAI-compatible wrappers for ASI1. Also trigger when the user says things like "use ASI1 instead of OpenAI", "build an app with ASI:One", "ASI1 API", or references docs.asi1.ai. This skill covers everything needed to build production apps - setup, all models, all API features, tool calling, image gen, agentic orchestration, structured data, session management, streaming, LangChain integration, uagents / Agent Chat Protocol, and TypeScript/Node.js patterns.
data-ai
When the user wants to analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.