
Decoy File Deployment for Ransomware Detection
FreeEnhance ransomware detection with strategic canary file deployment.
Free · Opens the source repo
What Decoy File Deployment for Ransomware Detection does
The Decoy File Deployment for Ransomware Detection skill provides a robust mechanism for detecting ransomware activity through the use of canary files, also known as honeytokens. This skill allows users to deploy decoy files across various file systems, strategically placing them in high-value locations to monitor for unauthorized modifications or encryption. By leveraging file integrity monitoring and OS-level watchdogs, the skill triggers alerts in real-time when these decoy files are altered, providing an early warning system against potential ransomware attacks.
The deployment process involves a well-planned strategy for canary file placement, ensuring maximum coverage across file shares and endpoints. Users can create realistic canary files with appropriate content and metadata to blend in with legitimate documents, making them less likely to be targeted by users. The skill supports both Python and Bash environments, allowing for flexible integration into existing workflows. It is designed for use in environments where protecting sensitive data is critical, such as finance, HR, and legal sectors.
This skill is particularly beneficial for organizations looking to supplement their existing endpoint detection and response (EDR) solutions with a deception-based layer that can detect unknown ransomware variants. By generating high-fidelity alerts with low false-positive rates, users can confidently validate their ransomware response procedures and ensure that their security posture is robust against evolving threats.
However, it is essential to note that this skill should not be the sole defense against ransomware. It is intended to work alongside traditional security measures such as backups, EDR, and access controls, providing an additional layer of detection rather than prevention.
When to use it
Use this skill when establishing an early-warning detection system for ransomware across file servers or endpoints, particularly in high-value areas.
When not to use it
This skill is not a standalone ransomware prevention mechanism and should not replace traditional security measures like backups or endpoint protection.
What you can build with it
Early Warning Detection
Deploy canary files across your network to receive alerts on unauthorized encryption activity before data loss occurs.
Ransomware Response Testing
Validate your incident response procedures by ensuring that modifications to canary files trigger the expected alerts.
Protection of Sensitive Data
Use decoy files in high-value directories to monitor for unauthorized access and protect critical business information.
How to install Decoy File Deployment for Ransomware Detection
View source1. Install with the skills CLI
npx skills add mukul975/anthropic-cybersecurity-skills/deploying-decoy-files-for-ransomware-detection --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by mukul975Deploying 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
watchdoglibrary 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:
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:
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
Event: Multiple canaries triggered within 60 seconds
→ Severity: EMERGENCY
→ Action: Network-wide isolation, activate incident response plan
Step 5: Validate Detection Coverage
Test that canary files detect actual ransomware behavior:
# Simulate ransomware encryption (safe test - modifies canary content)
echo "ENCRYPTED_BY_TEST" > /path/to/canary/_AAAA_budget.docx
# Simulate ransomware rename (adds extension)
mv /path/to/canary/report.xlsx /path/to/canary/report.xlsx.locked
# Verify alerts were generated in SIEM/alerting system
Verification
- Confirm all canary files are present and unmodified using stored hash baselines
- Verify that modifying any canary file generates an alert within the expected timeframe (under 30 seconds)
- Test that alert routing to SOC/SIEM is functional with a controlled modification
- Validate that automated response actions (process kill, network isolation) execute correctly
- Check that canary files survive normal backup and restore operations
- Ensure legitimate users and processes are excluded from false-positive alerts (backup agents, AV scans)
Key Concepts
| Term | Definition |
|---|---|
| Canary File | A decoy file placed in a directory that is monitored for any access or modification, serving as a tripwire for unauthorized activity |
| Honeytoken | A broader category of deception artifacts (files, credentials, database records) designed to alert when accessed |
| File Integrity Monitoring | Continuous monitoring of file attributes (hash, size, permissions, timestamps) to detect unauthorized changes |
| ReadDirectoryChangesW | Windows API for monitoring file system changes in a directory; used by the watchdog library on Windows |
| inotify | Linux kernel subsystem for monitoring file system events; provides near-instant notification of file changes |
Tools & Systems
- watchdog (Python): Cross-platform file system event monitoring library supporting Windows, Linux, and macOS
- Canarytokens (Thinkst): Free hosted service for generating various types of canary tokens including files, URLs, and DNS tokens
- OSSEC/Wazuh: Open-source HIDS with built-in file integrity monitoring and alerting capabilities
- Elastic Endpoint: Uses canary files internally for ransomware protection and key capture
- Sysmon: Windows system monitor that logs file creation events (Event ID 11) for canary file monitoring
Frequently asked questions about Decoy File Deployment for Ransomware Detection
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