Description

This curriculum spans the full incident lifecycle from initial triage to post-recovery governance, reflecting the structured workflows of a multi-phase internal response program integrated across help desk tiers, forensic recovery teams, and compliance functions.

Module 1: Incident Triage and Classification

Determine whether a data loss event is logical (e.g., accidental deletion) or physical (e.g., drive failure) based on user-reported symptoms and system logs.
Classify incidents by recovery urgency using SLA-defined criteria such as data criticality, number of affected users, and regulatory exposure.
Document chain-of-custody requirements when handling devices containing sensitive data to preserve legal admissibility.
Decide whether to escalate to specialized recovery teams based on preliminary diagnostics from built-in tools like CHKDSK or SMART status.
Assess user credibility and consistency in describing the incident to rule out social engineering or policy violations.
Initiate data freeze procedures on network shares or cloud storage to prevent overwrites during investigation.
Select appropriate triage tools (e.g., PowerShell scripts, Sysinternals) based on OS and environment constraints.
Establish communication protocols with stakeholders to manage expectations without promising recovery outcomes.

Module 2: Data Recovery Tooling and Environment Setup

Choose between commercial recovery tools (e.g., R-Studio, UFS Explorer) and open-source alternatives based on license cost, feature depth, and support availability.
Configure forensic workstations with write-blockers to prevent unintended modifications during disk imaging.
Validate tool compatibility with file systems (NTFS, APFS, ext4) and storage media (SSD, HDD, NVMe) before deployment.
Isolate recovery environments from production networks to prevent malware propagation or data leakage.
Standardize imaging procedures using tools like dd or FTK Imager to create bit-for-bit copies for analysis.
Maintain version-controlled toolkits to ensure consistency and auditability across recovery operations.
Configure virtual machines to safely test recovery tools on suspect media without risking hardware damage.
Integrate scripting (PowerShell, Bash) to automate repetitive recovery tasks and reduce human error.

Module 3: Logical Data Recovery Techniques

Recover deleted files by analyzing file system metadata (e.g., MFT entries on NTFS) before clusters are overwritten.
Reconstruct fragmented files using file carving techniques when directory entries are missing or corrupted.
Recover data from formatted drives by identifying residual file system structures and validating data integrity.
Address TRIM commands on SSDs that erase deleted block data, requiring earlier backups or cache analysis.
Use volume shadow copies (VSS) on Windows systems to restore previous versions of files when enabled.
Recover data from encrypted drives by obtaining and validating credentials or recovery keys before decryption.
Handle file system corruption by repairing structures with vendor tools or manual hex editing when automated repair fails.
Recover data from compressed or sparse files by decompressing in isolated environments to prevent expansion issues.

Module 4: Physical Media Assessment and Handling

Identify signs of physical damage (e.g., clicking sounds, overheating) and determine if in-house recovery is safe or requires lab referral.
Decide whether to power down a failing drive immediately or attempt a quick image based on failure mode analysis.
Use cleanroom procedures when handling exposed disk platters to prevent contamination and further damage.
Assess SSD wear leveling and bad block mapping to determine recoverable data regions.
Document media condition using diagnostic tools (e.g., HDAT2, CrystalDiskInfo) for vendor claims or insurance purposes.
Handle RAID arrays by identifying member disk status and avoiding automatic rebuilds that may overwrite recoverable data.
Transport damaged media using anti-static, shock-resistant packaging with proper labeling for external labs.
Establish protocols for drive disposal after recovery to ensure data sanitization and compliance with retention policies.

Module 5: Cloud and SaaS Data Recovery

Access native recovery features in cloud platforms (e.g., Microsoft 365 Retention Policies, Google Workspace Vault) based on subscription tier.
Authenticate and authorize access to cloud accounts using admin credentials without violating user privacy policies.
Recover deleted emails or files from cloud trash or recycle bins within retention window constraints.
Use API-based tools to extract large datasets from cloud services while respecting rate limits and audit logging.
Reconstruct shared file access history from audit logs to identify last known good state before deletion.
Coordinate with SaaS providers for backend recovery options when self-service tools are insufficient.
Validate recovered cloud data integrity by comparing checksums or metadata with known baselines.
Implement temporary access controls during recovery to prevent concurrent modifications by end users.

Module 6: Email and Messaging Recovery

Recover deleted emails from PST, OST, or MBOX files using forensic email analysis tools.
Extract messages from corrupted Outlook profiles by rebuilding OST files or converting to PST.
Recover archived emails from backup systems or journaling servers based on organizational retention rules.
Handle encrypted email content by obtaining decryption keys or leveraging S/MIME or PGP key stores.
Reconstruct chat history from messaging platforms (e.g., Teams, Slack) using eDiscovery tools or export APIs.
Address message threading issues when recovering partial conversations from fragmented data sources.
Preserve message metadata (headers, timestamps) to support compliance or legal investigations.
Manage mailbox size limits during recovery by splitting large PST files or using incremental exports.

Module 7: Data Validation and Integrity Verification

Compare recovered file hashes (SHA-256) with pre-loss backups or known good copies to verify authenticity.
Validate file structure integrity using format-specific tools (e.g., Office Repair, PDF validators) post-recovery.
Test recovered databases for consistency using built-in utilities (e.g., DBCC for SQL Server).
Identify and document corrupted files that cannot be repaired for stakeholder disclosure.
Reconstruct directory hierarchies when folder metadata is lost using file naming patterns or timestamps.
Validate timestamps and ownership metadata to ensure recovered files reflect accurate provenance.
Use checksum logs from backups to cross-reference recovered data completeness.
Report data gaps and integrity risks in recovery reports for audit and compliance purposes.

Module 8: Recovery Governance and Compliance

Enforce data handling policies in accordance with GDPR, HIPAA, or CCPA during recovery operations.
Document all recovery steps and tools used to support audit trails and regulatory reporting.
Restrict access to recovered data based on role-based permissions and data classification.
Obtain user or legal authorization before recovering personal or sensitive data in regulated environments.
Integrate recovery activities into incident response plans with defined escalation paths.
Report data breaches involving unrecoverable critical data to compliance officers per policy.
Archive recovery logs and case files for retention periods aligned with organizational policy.
Conduct post-recovery reviews to identify process gaps and update standard operating procedures.

Module 9: Help Desk Integration and Escalation Protocols

Define tiered support roles for data recovery, specifying when L1 agents must escalate to L2/L3 specialists.
Integrate recovery workflows into ticketing systems with custom fields for data loss type, media, and urgency.
Train frontline staff to collect essential recovery information (e.g., time of deletion, file paths) during initial contact.
Establish SLAs for recovery response and resolution times based on business impact tiers.
Coordinate with IT operations to schedule recovery during maintenance windows to minimize disruption.
Develop knowledge base articles for common recovery scenarios to reduce resolution time and improve consistency.
Monitor recovery success rates and mean time to recovery (MTTR) for performance reporting.
Conduct tabletop exercises to test escalation paths and recovery readiness across teams.