Show HN: Logatory – local-first log analysis and threat detection, no SIEM (github.com)

Logatory, a new tool for local log analysis and threat detection, has been introduced as a compelling alternative to traditional Security Information and Event Management (SIEM) systems. Operating entirely on local infrastructure, Logatory provides features such as PII (Personally Identifiable Information) redaction, rule-based threat detection, and anomaly detection, all accessible via a web dashboard or terminal. By employing deterministic pseudonyms for sensitive data, it allows organizations to correlate events without compromising privacy. The tool supports various log formats, including Syslog and Docker logs, making it versatile for different environments. This launch is significant for the AI/ML community as it demonstrates a shift towards decentralized and privacy-conscious analytics in cybersecurity. Logatory's integration of machine learning via an LLM (Large Language Model) enables automated insights, helping users interpret findings and summarize errors. Its anomaly detection leverages statistical methods to automatically learn from historical data, enhancing detection capabilities without extensive configuration. Furthermore, the platform includes a plugin system, allowing for custom rules, thereby adapting to specific security needs. Overall, Logatory empowers organizations to enhance their security posture while retaining control over their data.