deploying-ransomware-canary-files

deploying-ransomware-canary-files is a skill for Claude Code from 26zl/cybersec-toolkit. It costs 103 tokens per session (1,023 once invoked), scanned A, original, MIT.

A procedure for placing decoy files in important folders and watching for suspicious changes that may indicate ransomware. Ransomware is malicious software that encrypts files to extort money.

In plain words
What is it for?
Use it to deploy and monitor canary files on file servers, shared drives, home directories, NAS devices, or backup volumes, with alerts sent by email or Slack.
Why use it?
It can provide an early warning when ransomware starts scanning or changing files, but it does not prevent attacks or replace backups and endpoint protection.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Part of the cybersec-toolkit plugin — 197 skills, 2 hooks, 1 MCP server shipped together

Good fit Use it to deploy and monitor canary files on file servers, shared drives, home directories, NAS devices, or backup volumes, with alerts sent by email or Slack.

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Install with agentmods
npx agentmods add skills/26zl/cybersec-toolkit/deploying-ransomware-canary-files
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add 26zl/cybersec-toolkit --skill deploying-ransomware-canary-files
Clone the repo
git clone --depth 1 https://github.com/26zl/cybersec-toolkit

Made for: Claude Code.

Or install cybersec-toolkit, the plugin that ships this one along with the rest of its 197 skills, 2 hooks, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for deploying-ransomware-canary-files

README.md
[![agentmods](https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/deploying-ransomware-canary-files/github.svg)](https://agentmods.dev/skills/26zl/cybersec-toolkit/deploying-ransomware-canary-files)
Your own site
<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/deploying-ransomware-canary-files"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/deploying-ransomware-canary-files/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for deploying-ransomware-canary-files

Your own site · 80×15
<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/deploying-ransomware-canary-files"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/deploying-ransomware-canary-files.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 103 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,023 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00103 $0.01023
Opus 5 $0.00051 $0.00511
Sonnet 5 $0.00021 $0.00205
Haiku 4.5 $0.00010 $0.00102

Measured 7d ago against content hash 60e6da487925, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

deploying-ransomware-canary-files scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/deploying-ransomware-canary-files/SKILL.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deploying Ransomware Canary Files

When to Use

  • Deploying proactive ransomware detection on file servers, NAS devices, or endpoint systems
  • Building an early-warning system that detects ransomware before it encrypts business-critical data
  • Supplementing EDR solutions with lightweight canary file monitoring on systems where agents cannot be deployed
  • Testing ransomware incident response procedures by simulating canary file triggers
  • Monitoring shared drives, home directories, and backup volumes for unauthorized file operations

Do not use as a replacement for endpoint protection, backup strategy, or network segmentation. Canary files are a detection layer, not a prevention mechanism.

Prerequisites

  • Python 3.8+ with pip
  • watchdog library (pip install watchdog)
  • Write access to directories where canary files will be placed
  • SMTP server credentials or Slack webhook URL for alerting
  • Administrative access for placing canaries in system directories

Workflow

Step 1: Generate Canary Files

Create decoy files with realistic names and content that attract ransomware scanners. Files should have names like Passwords.xlsx, Financial_Report_2026.docx, backup_credentials.csv and contain plausible-looking but fake data. Place them in directories ransomware typically targets first: user desktops, Documents folders, network share roots, and backup paths.

Step 2: Deploy Filesystem Monitor

Use Python's watchdog library with a custom FileSystemEventHandler that watches canary file paths. The handler triggers on on_modified, on_deleted, on_moved, and on_created events for canary files. Any legitimate user or process should never touch these files, so any interaction is a high-confidence indicator of ransomware or unauthorized access.

Step 3: Configure Alert Pipeline

Wire the filesystem monitor to multiple alert channels: email via SMTP, Slack webhook POST, syslog forwarding to SIEM, and local log file. Include the triggering event type, file path, timestamp, and process information (when available) in alert payloads.

Read the full file on GitHub · 105 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 105 lines · 103 tokens per session scan A 60e6da487925

Subscribe to this mod's changes

deploying-ransomware-canary-files is a skill published in the GitHub repository 26zl/cybersec-toolkit (54 stars, last pushed today), licensed MIT. It adds 103 tokens to every session and 1,023 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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