implementing-honeytokens-for-breach-detection
Lets your agent deploy honeytokens for breach detection. Generates alerts when fake tokens (credentials, documents) are accessed by attackers.
What it does
This tool creates digital 'traps', like fake credentials or special links. If an attacker tries to use these traps, you'll be alerted immediately.
When to use it
- ✓When setting up security systems to detect intruders.
- ✓When you need an early warning about unauthorized access.
- ✓When testing the security of your systems.
Example of what to ask your AI
“Create a fake AWS credential to detect who is trying to access my systems.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool generates special 'tokens' that are placed in strategic locations. When someone (or an attacker) tries to access or use these tokens, a notification is sent to you.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-honeytokens-for-breach-detectionOr download just the file:
curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/implementing-honeytokens-for-breach-detection/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Implementing Honeytokens for Breach Detection
When to Use
- When deploying or configuring implementing honeytokens for breach detection capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- Familiarity with security operations concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Instructions
Deploy honeytokens across critical systems to detect unauthorized access. Each token type alerts via webhook when triggered by an attacker.
import requests
# Create a DNS canary token via Canarytokens
resp = requests.post("https://canarytokens.org/generate", data={
"type": "dns",
"email": "soc@company.com",
"memo": "Production DB server honeytoken",
})
token = resp.json()
print(f"DNS token: {token['hostname']}")
Token types to deploy:
- AWS credential files (~/.aws/credentials) with canary keys
- DNS tokens embedded in configuration files
- Document beacons (Word/PDF) in sensitive file shares
- Database honeytoken records in user tables
- Web bugs in internal wiki/documentation pages
Examples
# Generate a fake AWS credentials file with canary token
aws_creds = f"[default]\naws_access_key_id = {canary_key_id}\naws_secret_access_key = {canary_secret}\n"
with open("/opt/backup/.aws/credentials", "w") as f:
f.write(aws_creds)
FAQ
What are 'honeytokens'?
They are fake data or files created to lure and detect attackers. They look real but act as alarms.
What kinds of traps can I create?
You can create fake AWS credentials, DNS links that alert when accessed, documents with trackers, and even fake database records.
How do I know if I've been breached?
When an attacker interacts with one of the 'tokens' you've deployed, the tool sends an alert to you, indicating something suspicious is happening.
Details
Original description by the author
Deploys canary tokens and honeytokens (fake AWS credentials, DNS canaries, document beacons, database records) that trigger alerts when accessed by attackers. Uses the Canarytokens API and custom webhook integrations for breach detection. Use when building deception-based early warning systems for intrusion detection. '
Popularity
- GitHub stars
- 35k
- Ranking position
- #5892
- License
- Apache-2.0
- Updated
- 8/31/2026
Comments
- …
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