Agent skill

Performing File Carving With Foremost

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state.

Apache-2.0Auto-check: notesSecurity

Install Performing File Carving With Foremost

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-file-carving-with-foremost -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-file-carving-with-foremost --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/performing-file-carving-with-foremost .claude/skills/performing-file-carving-with-foremost && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
performing-file-carving-with-foremost
GitHub stars
34k
Token cost
~3.1k tokens
SKILL.md length
480 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state.

  • Works in 5 steps: Install and Configure Foremost → Run Foremost Against the Disk Image → Use Scalpel for High-Performance Carving → …
  • Tasks that involve Digital forensics
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; calls apt-get and python3

What it does

Performing File Carving With Foremost is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state. Use during digital forensics investigations to carve deleted or fragmented files, such as documents, images, and archives, from raw disk images or unallocated space.

Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Digital forensics. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Digital forensics

Example prompts

  • “Use the performing-file-carving-with-foremost skill to recover files from disk images and unallocated space using Foremost's header-footer signature…”
  • “/performing-file-carving-with-foremost”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Install and Configure Foremost
  2. Run Foremost Against the Disk Image
  3. Use Scalpel for High-Performance Carving
  4. Process and Validate Carved Files
  5. Examine and Catalog Evidence Files

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • apt-get
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Performing File Carving With Foremost loads about 3.1k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 480 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~3.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteRuns commands with sudoSKILL.md:55
    sudo apt-get install foremost
  • NoteRuns commands with sudoSKILL.md:132
    sudo apt-get install scalpel

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 480 words, ~3,140 tokens.

Download SKILL.mdSave it as .claude/skills/performing-file-carving-with-foremost/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
performing-file-carving-with-foremost
description
Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state. Use during digital forensics investigations to carve deleted or fragmented files, such as documents, images, and archives, from raw disk images or unallocated space.
domain
cybersecurity
subdomain
digital-forensics
tags
forensics, file-carving, foremost, data-recovery, evidence-recovery, unallocated-space
version
1.0
author
mahipal
license
Apache-2.0
nist_csf
RS.AN-03, DE.AE-02, RS.MA-01
mitre_attack
T1005, T1074, T1119, T1070, T1059

Performing File Carving with Foremost

When to Use

  • When recovering files from unallocated disk space or corrupted file systems
  • For extracting evidence from formatted or wiped storage media
  • When file system metadata is unavailable but raw data sectors contain evidence
  • During investigations requiring recovery of specific file types from raw images
  • As a complement to file system-based recovery for maximum evidence extraction

Prerequisites

  • Foremost installed on forensic workstation
  • Forensic disk image in raw (dd) format
  • Sufficient output storage (potentially larger than source)
  • Custom foremost.conf for specialized file types (optional)
  • Understanding of file signatures (magic bytes) for target file types
  • Scalpel as an alternative for performance-critical carving

Workflow

Step 1: Install and Configure Foremost
bash
# Install Foremost
sudo apt-get install foremost

# Verify installation
foremost -V

# Review default configuration
cat /etc/foremost.conf

# The default foremost.conf supports:
# jpg, gif, png, bmp - Image formats
# avi, exe, mpg, wav - Media and executables
# riff, wmv, mov, pdf - Documents and video
# ole (doc/xls/ppt), zip, rar - Office and archives
# htm, cpp, java - Text/code files

# Create custom configuration for additional file types
cp /etc/foremost.conf /cases/case-2024-001/custom_foremost.conf

# Add custom file signatures
cat << 'EOF' >> /cases/case-2024-001/custom_foremost.conf
# Custom additions for investigation
# Format: extension  case_sensitive  max_size  header  footer
    docx    y    10000000    \x50\x4b\x03\x04    \x50\x4b\x05\x06
    xlsx    y    10000000    \x50\x4b\x03\x04    \x50\x4b\x05\x06
    pptx    y    10000000    \x50\x4b\x03\x04    \x50\x4b\x05\x06
    sqlite  y    50000000    \x53\x51\x4c\x69\x74\x65\x20\x66\x6f\x72\x6d\x61\x74
    pst     y    500000000   \x21\x42\x44\x4e
    eml     y    1000000     \x46\x72\x6f\x6d\x3a    \x0d\x0a\x0d\x0a
    evtx    y    50000000    \x45\x6c\x66\x46\x69\x6c\x65
EOF
Step 2: Run Foremost Against the Disk Image
bash
# Basic carving of all supported file types
foremost -t all \
   -i /cases/case-2024-001/images/evidence.dd \
   -o /cases/case-2024-001/carved/foremost_all/

# Carve only specific file types
foremost -t jpg,png,pdf,doc,xls,zip \
   -i /cases/case-2024-001/images/evidence.dd \
   -o /cases/case-2024-001/carved/foremost_targeted/

# Use custom configuration
foremost -c /cases/case-2024-001/custom_foremost.conf \
   -i /cases/case-2024-001/images/evidence.dd \
   -o /cases/case-2024-001/carved/foremost_custom/

# Carve from a specific partition offset
# First, find partitions
mmls /cases/case-2024-001/images/evidence.dd
# Then carve from unallocated space only
# Extract unallocated space with blkls
blkls -o 2048 /cases/case-2024-001/images/evidence.dd \
   > /cases/case-2024-001/unallocated.dd

foremost -t all \
   -i /cases/case-2024-001/unallocated.dd \
   -o /cases/case-2024-001/carved/foremost_unalloc/

# Verbose mode for detailed progress
foremost -v -t all \
   -i /cases/case-2024-001/images/evidence.dd \
   -o /cases/case-2024-001/carved/foremost_verbose/ 2>&1 | \
   tee /cases/case-2024-001/carved/foremost_log.txt

# Indirect mode (process standard input)
dd if=/cases/case-2024-001/images/evidence.dd bs=512 skip=2048 | \
   foremost -t jpg,pdf -o /cases/case-2024-001/carved/foremost_pipe/
Step 3: Use Scalpel for High-Performance Carving
bash
# Install Scalpel (faster alternative based on Foremost)
sudo apt-get install scalpel

# Edit Scalpel configuration (uncomment desired file types)
cp /etc/scalpel/scalpel.conf /cases/case-2024-001/scalpel.conf
# Uncomment lines for target file types in the config

# Run Scalpel
scalpel -c /cases/case-2024-001/scalpel.conf \
   -o /cases/case-2024-001/carved/scalpel/ \
   /cases/case-2024-001/images/evidence.dd

# Scalpel with file size limits
# Edit scalpel.conf to set appropriate max sizes:
# jpg  y  5000000  \xff\xd8\xff  \xff\xd9
# pdf  y  20000000 %PDF  %%EOF
Step 4: Process and Validate Carved Files
bash
# Review Foremost audit report
cat /cases/case-2024-001/carved/foremost_all/audit.txt

# The audit.txt contains:
# - Number of files found per type
# - Start and end offsets
# - File sizes

# Validate carved files
python3 << 'PYEOF'
import os
import subprocess
from collections import defaultdict

carved_dir = '/cases/case-2024-001/carved/foremost_all/'
stats = defaultdict(lambda: {'total': 0, 'valid': 0, 'invalid': 0, 'size': 0})

for subdir in os.listdir(carved_dir):
    subdir_path = os.path.join(carved_dir, subdir)
    if not os.path.isdir(subdir_path) or subdir == 'audit.txt':
        continue

    for filename in os.listdir(subdir_path):
        filepath = os.path.join(subdir_path, filename)
        if not os.path.isfile(filepath):
            continue

        ext = subdir
        filesize = os.path.getsize(filepath)
        stats[ext]['total'] += 1
        stats[ext]['size'] += filesize

        # Validate file using 'file' command
        result = subprocess.run(['file', '--brief', filepath], capture_output=True, text=True)
        file_type = result.stdout.strip()

        if 'data' in file_type.lower() or 'empty' in file_type.lower():
            stats[ext]['invalid'] += 1
        else:
            stats[ext]['valid'] += 1

print("=== CARVED FILE VALIDATION ===\n")
print(f"{'Type':<10} {'Total':<8} {'Valid':<8} {'Invalid':<10} {'Total Size':<15}")
print("-" * 55)
for ext in sorted(stats.keys()):
    s = stats[ext]
    size_mb = s['size'] / (1024*1024)
    print(f"{ext:<10} {s['total']:<8} {s['valid']:<8} {s['invalid']:<10} {size_mb:>10.1f} MB")

# Remove zero-byte files
for subdir in os.listdir(carved_dir):
    subdir_path = os.path.join(carved_dir, subdir)
    if os.path.isdir(subdir_path):
        for filename in os.listdir(subdir_path):
            filepath = os.path.join(subdir_path, filename)
            if os.path.isfile(filepath) and os.path.getsize(filepath) == 0:
                os.remove(filepath)
PYEOF

# Hash all valid carved files
find /cases/case-2024-001/carved/foremost_all/ -type f ! -name "audit.txt" \
   -exec sha256sum {} \; > /cases/case-2024-001/carved/carved_file_hashes.txt

# Check against known-bad hash database
# Check against NSRL known-good database to filter
Step 5: Examine and Catalog Evidence Files
bash
# Extract metadata from carved images (EXIF data including GPS)
exiftool -r -csv /cases/case-2024-001/carved/foremost_all/jpg/ \
   > /cases/case-2024-001/analysis/carved_image_metadata.csv

# Search carved documents for keywords
find /cases/case-2024-001/carved/foremost_all/pdf/ -name "*.pdf" -exec pdftotext {} - \; 2>/dev/null | \
   grep -iE '(confidential|secret|password|account|ssn|credit.card)' \
   > /cases/case-2024-001/analysis/keyword_hits_pdf.txt

# Generate thumbnails for image review
mkdir -p /cases/case-2024-001/carved/thumbnails/
find /cases/case-2024-001/carved/foremost_all/jpg/ -name "*.jpg" -exec \
   convert {} -thumbnail 200x200 /cases/case-2024-001/carved/thumbnails/{} \; 2>/dev/null

# Create evidence catalog
python3 << 'PYEOF'
import os, hashlib, csv, subprocess

catalog = []
carved_dir = '/cases/case-2024-001/carved/foremost_all/'

for subdir in sorted(os.listdir(carved_dir)):
    subdir_path = os.path.join(carved_dir, subdir)
    if not os.path.isdir(subdir_path):
        continue
    for filename in sorted(os.listdir(subdir_path)):
        filepath = os.path.join(subdir_path, filename)
        if not os.path.isfile(filepath):
            continue
        size = os.path.getsize(filepath)
        sha256 = hashlib.sha256(open(filepath, 'rb').read()).hexdigest()
        file_type = subprocess.run(['file', '--brief', filepath], capture_output=True, text=True).stdout.strip()

        catalog.append({
            'filename': filename,
            'type': subdir,
            'size': size,
            'sha256': sha256,
            'file_description': file_type[:100]
        })

with open('/cases/case-2024-001/analysis/carved_file_catalog.csv', 'w', newline='') as f:
    writer = csv.DictWriter(f, fieldnames=['filename', 'type', 'size', 'sha256', 'file_description'])
    writer.writeheader()
    writer.writerows(catalog)

print(f"Catalog created with {len(catalog)} files")
PYEOF

Key Concepts

ConceptDescription
File carvingRecovering files by searching for known header/footer byte sequences in raw data
File signatureUnique byte pattern at the start (header) or end (footer) identifying a file type
Unallocated spaceDisk sectors not assigned to any file; primary target for carving
FragmentationWhen file data is stored in non-contiguous sectors, complicating carving
Header-footer carvingExtracting data between known file start and end signatures
False positivesCarved data matching file signatures but containing corrupt or unrelated content
Slack spaceUnused bytes at the end of a file's last allocated cluster
Sector alignmentFiles typically start at sector boundaries, improving carving accuracy

Tools & Systems

ToolPurpose
ForemostOriginal header-footer file carving tool developed for US Air Force OSI
ScalpelHigh-performance file carver with configurable signatures
PhotoRecSignature-based file recovery supporting 300+ formats
bulk_extractorExtracts features (emails, URLs, credit cards) from raw data
blklsSleuth Kit tool extracting unallocated space from disk images
mmlsPartition table display for identifying carving targets
ExifToolMetadata extraction from carved image and document files
hashdeepRecursive hash computation for carved file cataloging
Show full SKILL.md (157 more words)Show less

Common Scenarios

Scenario 1: Recovering Deleted Evidence Documents Run Foremost targeting doc, pdf, xlsx formats against the unallocated space extracted with blkls, validate carved documents, search content for case-relevant keywords, catalog and hash all recoverable documents, present as evidence.

Scenario 2: Image Recovery from Formatted Media Carve JPEG, PNG, GIF, BMP from a formatted USB drive image, extract EXIF metadata including GPS coordinates and camera information, generate thumbnails for rapid visual review, identify evidence-relevant images, document recovery chain.

Scenario 3: Email Recovery from Damaged PST Use custom foremost.conf with PST and EML signatures, carve email artifacts from damaged Outlook data file, attempt to open carved PST fragments in a viewer, extract individual EML messages, search for relevant communications.

Scenario 4: Database Recovery for Financial Investigation Configure Foremost to carve SQLite databases from unallocated space, recover application databases that were deleted, query recovered databases for financial records, cross-reference with known transaction data, document findings for prosecution.

Output Format

File Carving Summary:
  Tool: Foremost 1.5.7
  Source: evidence.dd (500 GB)
  Target: Unallocated space (234 GB)
  Duration: 1h 45m

  Files Carved:
    jpg:    2,345 files (1.8 GB) - Valid: 2,100 / Invalid: 245
    png:      234 files (456 MB) - Valid: 210 / Invalid: 24
    pdf:      156 files (890 MB) - Valid: 134 / Invalid: 22
    doc:       89 files (234 MB) - Valid: 67 / Invalid: 22
    xls:       45 files (123 MB) - Valid: 38 / Invalid: 7
    zip:       67 files (567 MB) - Valid: 52 / Invalid: 15
    exe:       34 files (234 MB) - Valid: 30 / Invalid: 4
    sqlite:    12 files (89 MB)  - Valid: 10 / Invalid: 2

  Total Files: 2,982 (3.4 GB recovered)
  Evidence-Relevant: 45 files flagged for review
  Audit Log: /cases/case-2024-001/carved/foremost_all/audit.txt
  File Catalog: /cases/case-2024-001/analysis/carved_file_catalog.csv

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/performing-file-carving-with-foremost of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

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Categories

Questions about Performing File Carving With Foremost

What does Performing File Carving With Foremost do?

Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state. Performing File Carving With Foremost is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state.

When should I use Performing File Carving With Foremost?

Performing File Carving With Foremost fits situations like: tasks that involve Digital forensics.

How do I install Performing File Carving With Foremost in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-file-carving-with-foremost -a claude-code`. Or copy the skill folder (skills/performing-file-carving-with-foremost in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/performing-file-carving-with-foremost in your project. Claude Code loads it when a task matches its description.

How do I install Performing File Carving With Foremost in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-file-carving-with-foremost -a codex`. Or copy the skill folder (skills/performing-file-carving-with-foremost in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/performing-file-carving-with-foremost in your project. Codex loads it when a task matches its description.

Can I use Performing File Carving With Foremost in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-file-carving-with-foremost -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performing-file-carving-with-foremost, .gemini/skills/performing-file-carving-with-foremost, .github/skills/performing-file-carving-with-foremost and .opencode/skills/performing-file-carving-with-foremost in your project.

What does Performing File Carving With Foremost need to run?

Going by SKILL.md and its folder, Performing File Carving With Foremost needs Python for the scripts in its folder and the command-line tools its instructions call (apt-get and python3). Our summary lists: Python 3.

Does Performing File Carving With Foremost access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Performing File Carving With Foremost safe to install?

Our automated static check of SKILL.md found notes only (runs commands with sudo), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Performing File Carving With Foremost use?

Performing File Carving With Foremost is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Performing File Carving With Foremost use?

About 3.1k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 385 tokens, read only when the agent opens those files.

What are the alternatives to Performing File Carving With Foremost?

Skills that share tags, products or a category with Performing File Carving With Foremost: Oss Forensics (Tommy-yw/RunbookHermes, 546 stars), Ctf Malware (ljagiello/ctf-skills, 3.4k stars), Dfir (transilienceai/communitytools, 563 stars) and TShark Traffic Analysis (AgentSecOps/SecOpsAgentKit, 220 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Performing File Carving With Foremost?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.