Deploy decoy files and monitor changes, renames, and deletions for early signs of ransomware. This skill guides Python monitoring, email, Slack, and syslog alerts, plus simulated file operations to verify that the detection and notification pipeline works.
Deploys and monitors ransomware canary files using Python's watchdog library, placing decoy files mimicking high-value targets (financial records, credentials, database exports) where ransomware enumerates first, and alerting via email, Slack, or syslog on any read/modify/rename/delete. Use for early-warning ransomware detection on file servers, NAS, or endpoints, or to supplement EDR where agents can't be deployed.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Do not use as a replacement for endpoint protection, backup strategy, or network segmentation. Canary files are a detection layer, not a prevention mechanism.
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.
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.
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.
Simulate ransomware behavior by programmatically modifying, renaming, and deleting canary files to verify the detection pipeline fires correctly. Measure time-to-alert and validate alert delivery across all configured channels.
| Term | Definition |
|---|---|
| Canary File | A decoy file placed in a monitored directory that triggers an alert when accessed, modified, or deleted |
| Watchdog | Python library that monitors filesystem events using OS-native APIs (inotify on Linux, FSEvents on macOS, ReadDirectoryChangesW on Windows) |
| Honey File | Synonym for canary file; a fake document designed to attract and detect malicious activity |
| Entropy Check | Measuring randomness in file content to detect encryption (ransomware produces high-entropy output) |
RANSOMWARE CANARY ALERT
========================
Timestamp: 2026-03-11T14:23:07Z
Event: FILE_MODIFIED
Canary File: /srv/shares/finance/Passwords.xlsx
Directory: /srv/shares/finance
SHA-256 Before: a3f2...8b4c
SHA-256 After: 7e91...2d3f
Alert Channels: [email, slack, syslog]
Action: Investigate immediately - potential ransomware activity
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Assess exposure of Windows secrets protected by DPAPI, the operating system’s data protection service, during authorized security tests. Guide examination and decryption of saved credentials and browser data using available user sessions, credentials, or backup keys.
Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.
Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.
Create disk images for investigations using dd or dcfldd on Linux. The workflow covers write protection, bit-for-bit copying, hash checks to verify integrity, and documentation of the acquisition process.
Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.
Inspect suspicious Android APK files without running them. Analyze permissions, app components, suspicious code patterns, and network indicators, then produce a JSON risk report to support malware triage and detection rule development.