HACKING PROJECT · forensics · Advanced
AWS/Azure Disk-Snapshot Forensic Analyzer
Automate forensically sound acquisition and triage of cloud disk snapshots across AWS and Azure while preserving chain of custody.
When a cloud workload is compromised, responders cannot simply pull a physical disk — evidence lives in ephemeral EBS/Managed Disk volumes that autoscaling may destroy within minutes. Most organizations lack a repeatable, forensically sound process to snapshot, copy, and mount cloud volumes read-only across accounts without contaminating the source. This gap leads to lost evidence, broken chain of custody, and IR reports that fail legal scrutiny.
**What you'll build**
Build an automated toolkit that programmatically creates point-in-time snapshots via AWS EBS / Azure Managed Disk APIs, copies them into an isolated forensic account/resource group, attaches them read-only to an analysis instance, and runs a triage pipeline (timeline, hash baselining, artifact carving). All actions are logged with cryptographic hashes and timestamps to preserve chain of custody. The tool integrates KAPE/Plaso-style parsing and outputs a court-defensible evidence package.
**Objective** — Automate forensically sound acquisition and triage of cloud disk snapshots across AWS and Azure while preserving chain of custody.
**Expected outcome** — A CLI/Python toolkit plus documented workflow that acquires a cloud snapshot, mounts it read-only in an isolated forensic account, and produces a hashed evidence package with a super-timeline and triage report.
**Difficulty** — Advanced — requires cloud IAM, cross-account evidence handling, forensic soundness, and multi-provider API automation simultaneously.
**Primary category** — DFIR; Secondary = Cloud Security, Incident Response
**Security domains** — Primary = Digital Forensics; Secondary = Cloud Security, Incident Response, Blue Team
**Technical focus** — Cloud Forensics, Disk/Volume Forensics, Evidence Acquisition, Chain of Custody, Super-Timeline Analysis, IAM/Cross-Account Isolation, Snapshot Automation, Triage Automation
**Core technologies** — Languages: Python, Bash, PowerShell; Frameworks/Libraries: boto3, Azure SDK for Python, dfVFS, pytsk3; Security Tools: Plaso/log2timeline, KAPE, The Sleuth Kit, Velociraptor, dc3dd/ewfacquire; Cloud/Infra: AWS EBS/EC2/KMS/S3, Azure Managed Disks/Blob Storage, isolated forensic account/RG; AI/Data: pandas for timeline enrichment, optional ML anomaly scoring; Databases: SQLite (Plaso store), Elasticsearch (optional timeline indexing)
**Where it's valued** — Cloud-native enterprises, MSSPs/IR consultancies, financial services, healthcare, SaaS providers, regulated industries requiring cloud incident response
**Careers it builds toward** — Cloud Forensics Analyst, DFIR Consultant, Incident Responder, Cloud Security Engineer, SOC Forensics Specialist
**Framework alignment**
• MITRE ATT&CK: Defensive response to T1578 (Modify Cloud Compute Infrastructure incl. T1578.001 Create Snapshot), T1530 (Data from Cloud Storage), T1537 (Transfer Data to Cloud Account); acquisition supports investigation of T1078.004 (Cloud Accounts)
• NIST CSF 2.0: Respond (RS.AN analysis), Recover (RC), Detect (DE) — evidence collection and forensic analysis
• OWASP: N/A (Cloud/Infra forensics; API Top 10 relevant only for the tool's own control plane)
• CIS Controls v8: 8 (Audit Log Management), 3 (Data Protection), 1 (Inventory of Enterprise Assets), 17 (Incident Response Management)
**Innovation** — Improved Existing Solution — cloud forensic acquisition exists (e.g., commercial tools, cloud-native snapshot APIs) but a unified, multi-cloud, chain-of-custody-preserving open toolkit has strong startup and enterprise pull. Scores: Innovation 7/10, Startup 8/10, Enterprise-Readiness 7/10, Patent = Possible.