A security tool that visualizes and analyzes Windows Active Directory event logs to investigate malicious logon activity.
LogonTracer is a security investigation tool that visualizes and analyzes Windows Active Directory event logs to detect malicious logon activity. It correlates hosts, IP addresses, and accounts from authentication events and displays them as interactive graphs, helping security analysts identify compromised credentials and suspicious authentication patterns. The tool applies advanced algorithms like PageRank and Hidden Markov Models to automatically detect anomalies in logon behavior.
Security analysts, incident responders, and cybersecurity professionals who need to investigate potential account compromises and malicious logon activity in Windows Active Directory environments.
LogonTracer provides specialized visualization and analysis of Windows authentication logs that traditional SIEM tools often lack, making complex logon relationships immediately understandable. Its open-source nature and self-hostable deployment give security teams full control over sensitive log data while providing advanced detection algorithms typically found in commercial security products.
Investigate malicious Windows logon by visualizing and analyzing Windows event log
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Employs PageRank, Hidden Markov Models, and ChangeFinder algorithms to automatically identify malicious hosts and accounts, as detailed in the 'Additional Analysis' section of the README.
Analyzes key Windows security events including logon successes/failures, Kerberos, and NTLM authentication, based on the cited FIRST conference research in the README.
Uses Cytoscape to create interactive graphs that visually correlate hosts, IP addresses, and accounts, making complex authentication patterns immediately apparent from the sample image.
Displays event logs in chronological order for timeline-based analysis, aiding in reconstructing attack sequences during incident response, as shown in the timeline screenshot.
Leverages Neo4j for storing and querying logon data, enabling efficient relationship analysis and scalable handling of large log volumes, as noted in the architecture section.
Requires separate installation and configuration of Neo4j graph database, adding significant setup overhead compared to standalone forensic tools, as highlighted in the installation wiki.
Limited to parsing Windows Active Directory event logs (e.g., 4624, 4625), making it ineffective for environments with mixed operating systems or cloud-native authentication.
Users must understand Windows security events, Neo4j Cypher queries, and statistical algorithms to properly interpret the visualization and detection results, which can be daunting for newcomers.
Primarily designed for post-incident investigation of collected logs, lacking built-in real-time monitoring or alerting features for proactive defense, as it processes logs after import.