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deploying-decoy-files-for-ransomware-detection

Deploys canary files (honeytokens) across file systems to detect ransomware encryption activity in real time.

Skill by mukul975

IndexedApache-2.0★ 34,941
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Deploys canary files (honeytokens) across file systems to detect ransomware encryption activity in real time. Uses strategically placed decoy documents monitored via file integrity monitoring or OS-level watchdogs to trigger alerts when ransomware modifies or encrypts them. Activates for requests involving ransomware canary deployment, honeyfile setup, deception-based ransomware detection, or file integrity monitoring for encryption.

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Secrets
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Install scripts
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Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/deploying-decoy-files-for-ransomware-detection

What's inside

Skill name
deploying-decoy-files-for-ransomware-detection
Description
Deploys canary files (honeytokens) across file systems to detect ransomware encryption activity in real time. Uses strategically placed decoy documents monitored via file integrity monitoring or OS-level watchdogs to trigger alerts when ransomware modifies or encrypts them. Activates for requests involving ransomware canary deployment, honeyfile setup, deception-based ransomware detection, or file integrity monitoring for encryption.
License
Apache-2.0
Instructions
167 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (4)

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

SKILL.md (first lines)

# Deploying Decoy Files for Ransomware Detection

## When to Use

- Setting up early-warning detection for ransomware on file servers or endpoints
- Supplementing EDR/AV with a deception-based detection layer that catches unknown ransomware variants
- Creating high-fidelity ransomware alerts that have very low false-positive rates (legitimate users have no reason to touch decoy files)
- Testing ransomware response procedures by validating that canary file modifications trigger the expected alerting pipeline
- Protecting high-value file shares (finance, HR, legal) with tripwire files that indicate unauthorized encryption activity

**Do not use** decoy files as the sole ransomware defense. They are a detection mechanism, not a prevention mechanism, and should complement backups, EDR, and access controls.

## Prerequisites

- Python 3.8+ with `watchdog` library for cross-platform file system monitoring
- Administrative access to target file shares or endpoints for canary placement
- File integrity monitoring (FIM) tool or SIEM integration for alert routing
- Understanding of target directory structure to place canaries in high-value locations
- Windows: NTFS change journal or ReadDirectoryChangesW API access
- Linux: inotify support in kernel (standard in modern kernels)

## Workflow

### Step 1: Design Canary File Strategy

Plan file placement for maximum detection coverage:

```
Canary File Placement Strategy:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Naming Convention:
  - Use names that sort FIRST and LAST alphabetically in each directory
  - Ransomware typically enumerates directories A-Z or Z-A
  - Examples: _AAAA_budget_2024.docx, ~zzzz_report_final.xlsx

Placement Locations:
  - Root of every file share (\\server\share\_AAAA_canary.docx)
  - Desktop, Documents, Downloads on each endpoint
  - Department-specific shares (Finance, HR, Legal)
  - Backup staging directories
  - Home directories of high-privilege accounts

File Types:
  - .docx, .xlsx, .pdf (most targeted by ransomware)
  - .sql, .bak (database files, high value)
  - Mix of file types to detect ransomware that targets specific extensions
```

### Step 2: Generate Realistic Canary Files

Create decoy files with realistic content and metadata:

```python
import os
import time

def create_canary_docx(filepath, content="Q4 Financial Summary - Confidential"):
    """Create a realistic .docx canary file using python-docx."""
    from docx import Document
    doc = Document()
    doc.add_heading("Financial Report - CONFIDENTIAL", level=1)
    doc.add_paragraph(content)
    doc.add_paragraph(f"Generated: {time.strftime('%Y-%m-%d')}")
    doc.save(filepath)

def create_canary_txt(filepath):
    """Create a simple text canary with known content for hash verification."""
    content = "CANARY_TOKEN_DO_NOT_MODIFY\n"
    content += f"Created: {time.strftime('%Y-%m-%dT%H:%M:%S')}\n"
    content += "This file is monitored for unauthorized changes.\n"
    with open(filepath, "w") as f:
        f.write(content)
```

### Step 3: Deploy File System Watcher

Monitor canary files for any modification, rename, or deletion:

```python
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler

class CanaryHandler(FileSystemEventHandler):
    def __init__(self, canary_paths, alert_callback):
        self.canary_paths = set(canary_paths)
        self.alert_callback = alert_callback

    def on_modified(self, event):
        if event.src_path in self.canary_paths:
            self.alert_callback("MODIFIED", event.src_path)

    def on_deleted(self, event):
        if event.src_path in self.canary_paths:
            self.alert_callback("DELETED", event.src_path)

    def on_moved(self, event):
        if event.src_path in self.canary_paths:
            self.alert_callback("RENAMED", event.src_path)
```

### Step 4: Configure Alerting and Response

Define automated responses when canary files are triggered:

```
Alert Response Matrix:
━━━━━━━━━━━━━━━━━━━━━
Event: Canary MODIFIED
  → Severity: CRITICAL
  → Action: Alert SOC, identify modifying process (PID), isolate endpoint

Event: Canary DELETED
  → Severity: HIGH
  → Action: Alert SOC, check for ransomware note in same directory

Event: Canary RENAMED (new extension added)
  → Severity: CRITICAL
  → Action: Alert SOC, check extension against known ransomware extensions
  → Automated: Kill modifying process, disable network interface

From mukul975/Anthropic-Cybersecurity-Skills, Apache-2.0.

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Last commit (this folder)
Jun 20, 2026 (4 months ago)
Last release
Jun 22, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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deploying-decoy-files-for-ransomware-detection skill. Agent Mart. https://agentmart.dev/skills/mukul975-deploying-decoy-files-for-ransomware-detection (last updated 2026-10-24)