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A splunk-based system for detecting log anomalies, failed logins, and suspicious user behavior using queries, alerts, and dashboards.

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hassanmajaro/log-anomaly-detector-using-splunk

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Splunk Log Anomaly Detection System

This project is a complete Splunk-based anomaly detection solution that identifies suspicious behaviors using structured log data, lookup files, dashboards, and alerts.

Features

  • Detect failed login surges by IP
  • Detect logins from new, unknown devices
  • Flag logins at unusual times
  • Visual dashboards for real-time monitoring
  • Reusable lookup tables for behavioral baselining
  • Alert rules for automated responses

Project Structure

  LOG_ANOMALY_DETECTOR/
    ├── alerts/ # Alert configuration guides
    ├── dashboards/ # Splunk XML dashboards
    ├── datasets/ # Sample datasets and lookup tables
    ├── docs/ # (Optional) Architecture diagrams or documentation
    ├── queries/ # SPL detection queries
    ├── .gitignore # Git exclusions
    ├── LICENSE # Project license (MIT recommended)
    └── README.md # Project overview and guide

Sample Datasets

Filename Description
dummydata.csv Simulated user logins, statuses, and messages
known_user_ips.csv Lookup of known User IP pairs for device tracking
train.csv Training or behavioral baseline data
sales_data.xlsx Transactional data for fraud analysis
addtotalsData.csv Aggregated log behavior data
homeworkdataset.csv Sample dataset for exercises
World_Airports.csv IP geolocation enrichment via airport/country mapping

Usage in Splunk

  1. Upload Datasets
    • Go to Settings > Add Data in Splunk
    • Upload datasets from the /datasets folder
  2. Run Detection Queries
    • Copy .spl files from /queries into Splunk Search
    • Run and analyze results
  3. Set Up Alerts
    • Follow steps in /alerts/*.md to configure real-time alerts
  4. Import Dashboards
    • Go to Dashboards > Create New > Import XML
    • Paste content from dashboards/anomaly_overview.xml

Dependencies

  • Splunk Enterpries (or Splunk Cloud)
  • Search & Reporting App (default in Splunk)
  • Lookups enabled

Author

Majaro Hassan

Cybersecurity Enthusiast | Certified Information Security Consultant (CISC) | SOC & SIEM Analyst


License

This project is licensed under the MIT License - see the LICENSE file for details.

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A splunk-based system for detecting log anomalies, failed logins, and suspicious user behavior using queries, alerts, and dashboards.

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