performing-cloud-forensics-investigation

What this skill does

# Performing Cloud Forensics Investigation

## When to Use
- When investigating a security breach in AWS, Azure, or GCP cloud environments
- For collecting volatile and non-volatile evidence from cloud infrastructure
- When tracing unauthorized access through cloud service API logs
- During incident response requiring preservation of cloud-based evidence
- For analyzing compromised virtual machines, containers, or serverless functions

## Prerequisites
- Administrative access to the cloud account under investigation
- AWS CLI, Azure CLI, or gcloud CLI configured with appropriate permissions
- Understanding of cloud-native logging (CloudTrail, Activity Log, Audit Log)
- Forensic workstation with cloud SDKs installed
- Knowledge of IAM, networking, and compute services in target cloud
- Evidence preservation procedures for cloud environments

## Workflow

### Step 1: Preserve Cloud Evidence and Establish Scope

```bash
# === AWS Evidence Preservation ===
# Snapshot compromised EC2 instance volumes
INSTANCE_ID="i-0abc123def456789"
VOLUME_IDS=$(aws ec2 describe-instances --instance-ids $INSTANCE_ID \
   --query 'Reservations[].Instances[].BlockDeviceMappings[].Ebs.VolumeId' --output text)

for vol in $VOLUME_IDS; do
   aws ec2 create-snapshot --volume-id $vol \
      --description "Forensic snapshot - Case 2024-001 - $(date -u)" \
      --tag-specifications "ResourceType=snapshot,Tags=[{Key=Case,Value=2024-001},{Key=Evidence,Value=true}]"
done

# Capture instance metadata
aws ec2 describe-instances --instance-ids $INSTANCE_ID \
   > /cases/case-2024-001/cloud/instance_metadata.json

# Capture security group rules
aws ec2 describe-security-groups --group-ids $(aws ec2 describe-instances \
   --instance-ids $INSTANCE_ID --query 'Reservations[].Instances[].SecurityGroups[].GroupId' --output text) \
   > /cases/case-2024-001/cloud/security_groups.json

# Capture network interfaces
aws ec2 describe-network-interfaces --filters "Name=attachment.instance-id,Values=$INSTANCE_ID" \
   > /cases/case-2024-001/cloud/network_interfaces.json

# Isolate the instance (replace security group with forensic isolation SG)
aws ec2 modify-instance-attribute --instance-id $INSTANCE_ID \
   --groups sg-forensic-isolation

# === Azure Evidence Preservation ===
# Snapshot a compromised VM disk
az snapshot create --resource-group forensics-rg \
   --name "case-2024-001-osdisk-snapshot" \
   --source "/subscriptions/SUB_ID/resourceGroups/RG/providers/Microsoft.Compute/disks/vm-osdisk"

# === GCP Evidence Preservation ===
gcloud compute disks snapshot compromised-disk \
   --snapshot-names="case-2024-001-forensic" \
   --zone=us-central1-a
```

### Step 2: Collect Cloud API and Access Logs

```bash
# === AWS CloudTrail Logs ===
# Download CloudTrail events for the investigation period
aws cloudtrail lookup-events \
   --start-time "2024-01-15T00:00:00Z" \
   --end-time "2024-01-20T23:59:59Z" \
   --max-results 1000 \
   > /cases/case-2024-001/cloud/cloudtrail_events.json

# Filter for specific user activity
aws cloudtrail lookup-events \
   --lookup-attributes AttributeKey=Username,AttributeValue=compromised-user \
   --start-time "2024-01-15T00:00:00Z" \
   > /cases/case-2024-001/cloud/user_activity.json

# Download S3 access logs
aws s3 sync s3://my-cloudtrail-bucket/AWSLogs/ /cases/case-2024-001/cloud/cloudtrail_s3/

# Query CloudTrail with Athena for large-scale analysis
aws athena start-query-execution \
   --query-string "SELECT eventTime, eventName, userIdentity.arn, sourceIPAddress, errorCode
                   FROM cloudtrail_logs
                   WHERE eventTime BETWEEN '2024-01-15' AND '2024-01-20'
                   AND sourceIPAddress NOT IN ('10.0.0.0/8')
                   ORDER BY eventTime" \
   --result-configuration OutputLocation=s3://forensics-bucket/athena-results/

# === AWS VPC Flow Logs ===
aws logs filter-log-events \
   --log-group-name "vpc-flow-logs" \
   --start-time $(date -d "2024-01-15" +%s000) \
   --end-time $(date -d "2024-01-20" +%s000) \
   --filter-pattern "ACCEPT" \
   > /cases/case-2024-001/cloud/vpc_flow_logs.json

# === Azure Activity Log ===
az monitor activity-log list \
   --start-time "2024-01-15T00:00:00Z" \
   --end-time "2024-01-20T23:59:59Z" \
   --output json > /cases/case-2024-001/cloud/azure_activity.json

# === GCP Audit Logs ===
gcloud logging read 'logName="projects/PROJECT_ID/logs/cloudaudit.googleapis.com%2Factivity"
   AND timestamp>="2024-01-15T00:00:00Z"
   AND timestamp<="2024-01-20T23:59:59Z"' \
   --format=json > /cases/case-2024-001/cloud/gcp_audit.json
```

### Step 3: Analyze IAM and Access Patterns

```bash
# Analyze compromised credentials usage
python3 << 'PYEOF'
import json
from collections import defaultdict

with open('/cases/case-2024-001/cloud/cloudtrail_events.json') as f:
    data = json.load(f)

# Analyze by source IP
ip_events = defaultdict(list)
error_events = []
critical_actions = []

for event in data.get('Events', []):
    ct = json.loads(event.get('CloudTrailEvent', '{}'))
    source_ip = ct.get('sourceIPAddress', 'Unknown')
    event_name = ct.get('eventName', 'Unknown')
    user_arn = ct.get('userIdentity', {}).get('arn', 'Unknown')
    error = ct.get('errorCode')
    timestamp = ct.get('eventTime', '')

    ip_events[source_ip].append(event_name)

    if error:
        error_events.append({'time': timestamp, 'action': event_name, 'error': error, 'ip': source_ip})

    # Flag critical actions
    critical = ['CreateUser', 'CreateAccessKey', 'AttachUserPolicy', 'CreateRole',
                'PutBucketPolicy', 'StopLogging', 'DeleteTrail', 'CreateKeyPair',
                'RunInstances', 'AuthorizeSecurityGroupIngress']
    if event_name in critical:
        critical_actions.append({'time': timestamp, 'action': event_name, 'user': user_arn, 'ip': source_ip})

print("=== SOURCE IP ANALYSIS ===")
for ip, events in sorted(ip_events.items(), key=lambda x: len(x[1]), reverse=True):
    print(f"  {ip}: {len(events)} events ({len(set(events))} unique actions)")

print(f"\n=== ACCESS ERRORS ({len(error_events)} total) ===")
for e in error_events[:10]:
    print(f"  [{e['time']}] {e['action']} -> {e['error']} from {e['ip']}")

print(f"\n=== CRITICAL ACTIONS ({len(critical_actions)} total) ===")
for a in critical_actions:
    print(f"  [{a['time']}] {a['action']} by {a['user']} from {a['ip']}")
PYEOF
```

### Step 4: Acquire and Analyze VM Disk Image

```bash
# Create a forensic analysis instance from the snapshot
SNAPSHOT_ID="snap-0abc123def456789"

# Create volume from snapshot in isolated forensic VPC
FORENSIC_VOL=$(aws ec2 create-volume --snapshot-id $SNAPSHOT_ID \
   --availability-zone us-east-1a \
   --tag-specifications "ResourceType=volume,Tags=[{Key=Case,Value=2024-001}]" \
   --query 'VolumeId' --output text)

# Attach to forensic analysis instance (read-only mount)
aws ec2 attach-volume --volume-id $FORENSIC_VOL \
   --instance-id i-forensic-workstation \
   --device /dev/xvdf

# On the forensic instance, mount read-only
sudo mount -o ro /dev/xvdf1 /mnt/evidence

# Perform standard disk forensics on the mounted volume
# Extract logs, analyze file system, check for persistence
ls /mnt/evidence/var/log/
cp -r /mnt/evidence/var/log/ /cases/case-2024-001/cloud/vm_logs/
cp -r /mnt/evidence/etc/crontab /cases/case-2024-001/cloud/persistence/
cp -r /mnt/evidence/home/*/.ssh/ /cases/case-2024-001/cloud/ssh_keys/
cp -r /mnt/evidence/home/*/.bash_history /cases/case-2024-001/cloud/bash_history/
```

### Step 5: Generate Cloud Forensics Report

```bash
# Compile findings into structured report
python3 << 'PYEOF'
report = """
CLOUD FORENSICS INVESTIGATION REPORT
======================================
Case: 2024-001
Cloud Provider: AWS (Account: 123456789012)
Region: us-east-1
Investigation Period: 2024-01-15 to 2024-01-20

EVIDENCE PRESERVED:
- EC2 Instance Snapshot: snap-0abc123def456789 (i-0abc123def456789)
- CloudTrail Logs: 2024-01-15 to 2024-01-20
- VPC Flow Logs: 2024-01-15 to 2024-01-20
- Instance