Recovering Deleted Files With Photorec

---
name: recovering-deleted-files-with-photorec
description: Use when recover deleted files from disk images and storage media using
  PhotoRec's file signature-based carving engine regardless of file system damage.
  Use when working with recovering deleted files with photorec.
domain: cybersecurity
tags:
- forensics
- file-recovery
- photorec
- file-carving
- data-recovery
- evidence-recovery
subdomain: digital-forensics
version: '1.0'
author: oyi77
license: Apache-2.0
nist_ai_rmf:
- MEASURE-2.7
- MAP-5.1
- MANAGE-2.4
atlas_techniques:
- AML.T0070
- AML.T0066
- AML.T0082
nist_csf:
- RS.AN-01
- RS.AN-03
- DE.AE-02
- RS.MA-01
category: cybersecurity
---

# Recovering Deleted Files With Photorec

## Overview

Cybersecurity skill for recovering deleted files with photorec. Follows industry best practices and security standards.

## When to Use
**Trigger phrases:**
- "recovering deleted files with photorec"
- "Recover deleted files from disk images and storage media using PhotoRec's file s"

- When recovering deleted files from a forensic disk image or storage device
- When the file system is corrupted, formatted, or overwritten
- During investigations requiring recovery of documents, images, videos, or databases
- When file system metadata is unavailable but raw data sectors remain intact
- For recovering files from memory cards, USB drives, and hard drives


## When NOT to Use

- When you lack proper authorization for testing
- For production systems without change management
- When the task requires legal or compliance expertise beyond technical scope


## Prerequisites
- PhotoRec installed (part of TestDisk suite)
- Forensic disk image or direct device access (read-only)
- Sufficient output storage space (potentially larger than source)
- Write-blocker if working with original media
- Root/sudo privileges for device access
- Knowledge of target file types for focused recovery

## Workflow

```python
# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}
```

1. **Define Objectives** — Clarify the goals and scope for deleted files.
2. **Gather Resources** — Collect tools, data, and access needed for deleted files.
3. **Execute Process** — Carry out deleted files operations methodically.
4. **Verify Quality** — Check results against acceptance criteria.
5. **Document Outcomes** — Record findings, decisions, and next steps.

## Tools

- **photorec** — Primary tool for this skill
- **Analysis Platform** — Data processing and visualization
- **Collaboration Tools** — Team coordination and knowledge sharing


## Process

1. **Prepare** — Gather requirements, verify prerequisites, set up environment
1. **Execute** — Run recovering deleted files with photorec workflow with configured parameters
1. **Verify** — Validate output meets requirements, document results

## Verification

- [ ] All deleted files procedures executed completely and documented
- [ ] Findings validated against multiple data sources
- [ ] False positives identified and filtered
- [ ] Results documented with evidence and timestamps
- [ ] Recommendations provided with risk-based prioritization

## Anti-Rationalization Table

| Rationalization | Reality |
|---|---|
| "We are too small to be targeted" | Automated attacks target everyone. Size does not matter. |
| "Security slows us down" | A breach slows you down 100x more. Build security in from the start. |
| "We will fix it after launch" | Vulnerabilities in production are exploited within hours. Fix before deploy. |