implementing-honeypot-for-ransomware-detection

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-honeypot-for-ransomware-detection
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summary

Deploys canary files, honeypot shares, and decoy systems to detect ransomware activity at the earliest possible stage. Configures canary tokens embedded in strategic file locations that trigger alerts when ransomware attempts encryption, uses honeypot network shares that mimic high-value targets, and deploys Thinkst Canary appliances for comprehensive deception-based detection. Activates for requests involving ransomware honeypots, canary files, deception technology for ransomware, or early ransomware alerting.

skill.md
name
implementing-honeypot-for-ransomware-detection
description
'Deploys canary files, honeypot shares, and decoy systems to detect ransomware activity at the earliest possible stage. Configures canary tokens embedded in strategic file locations that trigger alerts when ransomware attempts encryption, uses honeypot network shares that mimic high-value targets, and deploys Thinkst Canary appliances for comprehensive deception-based detection. Activates for requests involving ransomware honeypots, canary files, deception technology for ransomware, or early ransomware alerting. '
domain
cybersecurity
subdomain
ransomware-defense
tags
- ransomware - detection - honeypot - canary - defense - deception
version
1.0.0
author
mahipal
license
Apache-2.0
d3fend_techniques
- File Metadata Consistency Validation - Content Format Conversion - File Content Analysis - Platform Hardening - File Format Verification
nist_csf
- PR.DS-11 - RS.MA-01 - RC.RP-01 - PR.IR-01

Implementing Honeypot for Ransomware Detection

When to Use

  • Deploying early-warning detection for ransomware encryption attempts using canary files
  • Creating honeypot file shares that detect lateral movement and data staging before encryption
  • Supplementing EDR and SIEM-based detection with deception-layer alerts that have near-zero false positives
  • Detecting ransomware variants that evade signature-based detection by triggering on file modification behavior
  • Validating that ransomware detection capabilities work by testing with controlled encryption tools

Do not use as the sole ransomware detection mechanism. Honeypots are a high-confidence supplementary layer, not a replacement for EDR, network monitoring, and backup protection.

Prerequisites

  • File server or NAS infrastructure where canary files can be deployed
  • Windows File Server Resource Manager (FSRM) or equivalent file activity monitoring
  • Thinkst Canary or similar deception platform (optional, for advanced deployment)
  • SIEM platform for centralizing honeypot alerts
  • Administrative access to deploy canary files across file shares
  • Network segment for honeypot systems (if deploying full honeypot servers)

Workflow

Step 1: Deploy Canary Files on File Shares

Place canary files in strategic locations that ransomware will encounter during encryption:

# Deploy canary files across all file shares
# Files are named to appear early in alphabetical and directory order
# Ransomware typically encrypts alphabetically or by directory traversal

$shares = @("\\fileserver01\finance", "\\fileserver01\hr", "\\fileserver01\engineering")
$canaryNames = @(
    "!_IMPORTANT_DO_NOT_DELETE.docx",
    "000_Budget_2026_FINAL.xlsx",
    "_Confidential_Employee_Records.pdf",
    "AAAA_Quarterly_Report.docx"
)

foreach ($share in $shares) {
    foreach ($name in $canaryNames) {
        $targetPath = Join-Path $share $name
        # Create a legitimate-looking file with canary content
        # The file contains a unique token that triggers on access
        $content = "This document contains confidential financial data.`n"
        $content += "Q4 2025 Revenue: $42.3M | Q1 2026 Forecast: $45.1M`n"
        $content += "Prepared by: Finance Department`n"
        Set-Content -Path $targetPath -Value $content
        # Set file as hidden system to avoid user interaction
        $file = Get-Item $targetPath
        $file.Attributes = [System.IO.FileAttributes]::Hidden
    }
}

# Also deploy in subdirectories (ransomware traverses recursively)
$subDirs = Get-ChildItem -Path "\\fileserver01\finance" -Directory -Recurse | Select-Object -First 20
foreach ($dir in $subDirs) {
    $canaryPath = Join-Path $dir.FullName "!_Budget_Summary.xlsx"
    Set-Content -Path $canaryPath -Value "Canary file for ransomware detection"
    (Get-Item $canaryPath).Attributes = [System.IO.FileAttributes]::Hidden
}

Step 2: Configure File Integrity Monitoring on Canary Files

Windows FSRM approach:

# Configure FSRM to monitor for ransomware file extensions
# and canary file modifications

Install-WindowsFeature -Name FS-Resource-Manager -IncludeManagementTools

# Create file screen for known ransomware extensions
$ransomExtensions = @(
    "*.encrypted", "*.locked", "*.crypto", "*.crypt",
    "*.locky", "*.cerber", "*.zepto", "*.thor",
    "*.aesir", "*.zzzzz", "*.wallet", "*.onion",
    "*.wncry", "*.wcry", "*.lockbit", "*.BlackCat",
    "*.ALPHV", "*.rhysida", "*.play"
)

# Create file group for ransomware extensions
New-FsrmFileGroup -Name "Ransomware_Extensions" -IncludePattern $ransomExtensions

# Create file screen template
New-FsrmFileScreenTemplate -Name "Ransomware_Screen" `
    -IncludeGroup "Ransomware_Extensions" `
    -Active:$false  # Passive mode: alert without blocking

# Apply to all monitored shares
$monitoredPaths = @("D:\Shares\Finance", "D:\Shares\HR", "D:\Shares\Engineering")
foreach ($path in $monitoredPaths) {
    New-FsrmFileScreen -Path $path -Template "Ransomware_Screen"
}

Canary file modification monitoring with PowerShell FileSystemWatcher:

# Real-time canary file monitoring service
$canaryPaths = @(
    "D:\Shares\Finance\!_IMPORTANT_DO_NOT_DELETE.docx",
    "D:\Shares\HR\000_Budget_2026_FINAL.xlsx",
    "D:\Shares\Engineering\_Confidential_Employee_Records.pdf"
)

$watcher = New-Object System.IO.FileSystemWatcher
$watcher.Path = "D:\Shares"
$watcher.Filter = "*"
$watcher.IncludeSubdirectories = $true
$watcher.EnableRaisingEvents = $true

$action = {
    $path = $Event.SourceEventArgs.FullPath
    $changeType = $Event.SourceEventArgs.ChangeType
    $timestamp = $Event.TimeGenerated

    # Check if modified file is a canary
    $isCanary = $false
    foreach ($canary in $canaryPaths) {
        if ($path -eq $canary) { $isCanary = $true; break }
    }

    if ($isCanary -or $changeType -eq "Renamed") {
        $alertMsg = "RANSOMWARE ALERT: Canary file modified! Path: $path | Change: $changeType | Time: $timestamp"
        # Log to Windows Event Log
        Write-EventLog -LogName Application -Source "RansomwareCanary" `
            -EventID 9999 -EntryType Error -Message $alertMsg
        # Send SIEM alert via syslog
        # Trigger automated containment
    }
}

Register-ObjectEvent $watcher "Changed" -Action $action
Register-ObjectEvent $watcher "Deleted" -Action $action
Register-ObjectEvent $watcher "Renamed" -Action $action

Step 3: Deploy Honeypot Network Shares

Create decoy file shares that appear to contain high-value data:

# Create honeypot share on dedicated server
# This server monitors ALL file access and alerts on any activity

New-Item -Path "D:\HoneypotShares\Executive_Compensation" -ItemType Directory
New-Item -Path "D:\HoneypotShares\M&A_Documents" -ItemType Directory
New-Item -Path "D:\HoneypotShares\Board_Meeting_Notes" -ItemType Directory
New-Item -Path "D:\HoneypotShares\Customer_Database_Exports" -ItemType Directory

# Share with broad read access (enticing to attackers)
New-SmbShare -Name "Executive_Compensation" `
    -Path "D:\HoneypotShares\Executive_Compensation" `
    -FullAccess "DOMAIN\Domain Users" `
    -Description "Executive Compensation Files - Restricted"

# Populate with realistic-looking but fake documents
# Use document templates that look legitimate
$docContent = @"
CONFIDENTIAL - Executive Compensation Summary
FY 2026 Base Salary and Bonus Structures
CEO: [REDACTED] | CFO: [REDACTED] | CTO: [REDACTED]
Total Compensation Package: See Appendix A
"@
Set-Content -Path "D:\HoneypotShares\Executive_Compensation\FY2026_Comp_Summary.txt" -Value $docContent

# Enable detailed audit logging on honeypot share
$acl = Get-Acl "D:\HoneypotShares"
$auditRule = New-Object System.Security.AccessControl.FileSystemAuditRule(
    "Everyone", "ReadAndExecute,Write,Delete", "ContainerInherit,ObjectInherit",
    "None", "Success,Failure"
)
$acl.AddAuditRule($auditRule)
Set-Acl "D:\HoneypotShares" $acl

# Enable object access auditing via GPO
auditpol /set /subcategory:"File System" /success:enable /failure:enable

Step 4: Deploy Thinkst Canary Tokens

For organizations using Thinkst Canary or the free canarytokens.org service:

# Generate canary tokens via API (Thinkst Canary)
# These trigger alerts when documents are opened or URLs are accessed

# Word document token
curl -X POST "https://CONSOLE.canary.tools/api/v1/canarytoken/create" \
  -d "auth_token=YOUR_API_TOKEN" \
  -d "memo=Finance_Share_Canary" \
  -d "kind=doc-msword" \
  -o /tmp/canary_budget_report.docx

# PDF document token
curl -X POST "https://CONSOLE.canary.tools/api/v1/canarytoken/create" \
  -d "auth_token=YOUR_API_TOKEN" \
  -d "memo=HR_Share_Canary" \
  -d "kind=pdf-acrobat-reader" \
  -o /tmp/canary_employee_handbook.pdf

# Windows folder token (alerts when folder is browsed)
curl -X POST "https://CONSOLE.canary.tools/api/v1/canarytoken/create" \
  -d "auth_token=YOUR_API_TOKEN" \
  -d "memo=Executive_Folder_Browse" \
  -d "kind=windows-dir"

# Deploy Canary appliance (emulates a file server)
# Configure via web console to appear as:
# - Windows file server with SMB shares
# - Contains realistic-looking directories
# - Any access triggers immediate alert with source IP and activity details

Step 5: Integrate Alerts with SIEM and Automated Response

# siem_integration.py - Forward honeypot alerts to SIEM and trigger containment

import json
import requests
import logging
from datetime import datetime

SIEM_WEBHOOK = "https://siem.company.com/api/alerts"
NAC_API = "https://nac.company.com/api/v1/quarantine"
EDR_API = "https://edr.company.com/api/v1/isolate"

def send_ransomware_alert(source_ip: str, canary_path: str, action: str):
    """Send high-priority alert to SIEM and trigger automated containment."""
    alert = {
        "timestamp": datetime.utcnow().isoformat(),
        "severity": "CRITICAL",
        "category": "Ransomware - Canary File Triggered",
        "source_ip": source_ip,
        "canary_file": canary_path,
        "action_detected": action,
        "automated_response": "Host isolation initiated",
        "mitre_technique": "T1486 - Data Encrypted for Impact",
    }

    # Send to SIEM
    try:
        requests.post(SIEM_WEBHOOK, json=alert, timeout=5)
    except requests.RequestException as e:
        logging.error(f"SIEM alert failed: {e}")

    # Automated containment - isolate host via NAC
    try:
        requests.post(f"{NAC_API}/{source_ip}",
                      json={"action": "quarantine", "reason": "Ransomware canary triggered"},
                      timeout=5)
    except requests.RequestException as e:
        logging.error(f"NAC quarantine failed: {e}")

    # Automated containment - isolate host via EDR
    try:
        requests.post(EDR_API,
                      json={"ip": source_ip, "action": "isolate"},
                      timeout=5)
    except requests.RequestException as e:
        logging.error(f"EDR isolation failed: {e}")

    logging.critical(f"RANSOMWARE CANARY ALERT: {source_ip} modified {canary_path} ({action})")

Key Concepts

TermDefinition
Canary FileA decoy file placed in strategic locations that triggers an alert when modified, renamed, or deleted by ransomware
Honeypot ShareA decoy network share designed to attract attackers, where any access is suspicious and triggers alerts
Canary TokenA trackable token embedded in a document or URL that reports back when accessed, revealing the accessor's IP and time
FSRMFile Server Resource Manager - Windows Server role that monitors file operations and can screen for ransomware extensions
Deception LayerSecurity architecture layer using decoy assets to detect threats with near-zero false positive rates
File System WatcherSystem service that monitors real-time file system changes (creation, modification, deletion, rename)

Tools & Systems

  • Thinkst Canary: Commercial deception platform providing canary appliances (emulate servers) and canary tokens (trackable documents)
  • Canarytokens.org: Free service from Thinkst for generating basic canary tokens (Word docs, PDFs, URLs, DNS)
  • OpenCanary: Open-source honeypot daemon that emulates common services (SMB, RDP, SSH) and logs access attempts
  • FSRM (File Server Resource Manager): Windows Server built-in tool for file screening, quota management, and ransomware extension detection
  • Elastic Endpoint: Uses canary files internally for ransomware protection, triggering behavioral alerts on canary modification

Common Scenarios

Scenario: Early Detection of BlackByte Ransomware via Canary Files

Context: A retail company deploys canary files across 200 file shares and 3 honeypot shares. At 3:00 AM on a Saturday, the canary monitoring system generates 47 alerts in rapid succession as canary files across 12 shares are modified within 90 seconds.

Approach:

  1. Canary file alert triggers automated containment: source workstation (10.2.8.55) quarantined via NAC within 30 seconds
  2. SIEM correlation shows the source workstation had EDR alerts for PsExec execution 2 hours earlier (missed by overnight SOC)
  3. Additional canary alerts from 3 other workstations indicate the ransomware is spreading via scheduled tasks
  4. IR team isolates the affected VLAN, preventing encryption of the remaining 188 file shares
  5. The 12 affected shares are restored from immutable backups within 4 hours
  6. Estimated damage prevented: $2.3M in downtime and recovery costs based on the 95% of shares protected

Pitfalls:

  • Placing canary files only in root directories where ransomware may skip them by targeting subdirectories first
  • Using obvious canary names that sophisticated ransomware may recognize and avoid
  • Not testing canary alerting end-to-end, discovering during an actual incident that alerts are not reaching the SOC
  • Generating excessive canary alerts during legitimate file migrations or antivirus scans, causing alert fatigue

Output Format

## Ransomware Honeypot Deployment Report

**Organization**: [Name]
**Deployment Date**: [Date]

### Canary File Deployment
| Share | Files Deployed | Naming Convention | Alert Method |
|-------|---------------|-------------------|--------------|
| [Share path] | [Count] | [Pattern] | [FSRM/Watcher/Token] |

### Honeypot Shares
| Share Name | Location | Apparent Content | Monitoring |
|-----------|----------|-----------------|------------|
| [Name] | [Server] | [Description] | [Audit/Canary] |

### Alert Integration
- SIEM: [Connected/Not Connected]
- Automated Containment: [EDR Isolation/NAC Quarantine/None]
- Alert SLA: [Expected response time]

### Testing Results
| Test Date | Test Type | Canary Triggered | Alert Received | Containment Executed | Time to Alert |
|-----------|----------|-----------------|----------------|---------------------|---------------|
how to use implementing-honeypot-for-ransomware-detection

How to use implementing-honeypot-for-ransomware-detection on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add implementing-honeypot-for-ransomware-detection
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-honeypot-for-ransomware-detection

The skills CLI fetches implementing-honeypot-for-ransomware-detection from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
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│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/implementing-honeypot-for-ransomware-detection

Reload or restart Cursor to activate implementing-honeypot-for-ransomware-detection. Access the skill through slash commands (e.g., /implementing-honeypot-for-ransomware-detection) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.663 reviews
  • Soo Anderson· Dec 28, 2024

    implementing-honeypot-for-ransomware-detection is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Shikha Mishra· Dec 20, 2024

    I recommend implementing-honeypot-for-ransomware-detection for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Hana Sethi· Dec 4, 2024

    Solid pick for teams standardizing on skills: implementing-honeypot-for-ransomware-detection is focused, and the summary matches what you get after install.

  • Mia Ndlovu· Nov 23, 2024

    implementing-honeypot-for-ransomware-detection has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Anaya Haddad· Nov 19, 2024

    Keeps context tight: implementing-honeypot-for-ransomware-detection is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Yash Thakker· Nov 11, 2024

    implementing-honeypot-for-ransomware-detection fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakshi Patil· Nov 3, 2024

    Useful defaults in implementing-honeypot-for-ransomware-detection — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chaitanya Patil· Oct 22, 2024

    Registry listing for implementing-honeypot-for-ransomware-detection matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Mia Desai· Oct 14, 2024

    implementing-honeypot-for-ransomware-detection fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakura Kapoor· Oct 10, 2024

    We added implementing-honeypot-for-ransomware-detection from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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