LogRhythm Empowers AI-Ready Organizations

LogRhythm announced its 9th quarterly update, aiming to improve security teams’ efficiency by providing high-quality data to enhance AI tools against cyber threats. The latest release simplifies data retention and compliance, boosting analysts’ productivity.

“Our continuous updates demonstrate our dedication to delivering intuitive tools that enhance security teams’ efficiency,” said CEO Chris O’Malley.

LogRhythm emphasizes data quality as crucial for AI effectiveness. Many vendors focus on AI but overlook the importance of reliable data. LogRhythm’s Machine Data Intelligence [MDI] Fabric, which has been refined over 20 years, organizes diverse log sources into structured, searchable datasets. This ensures accurate data, enhancing analysts’ efficiency and precision in their investigations.

“Our enhancements aim to improve analyst efficiency and security team capabilities,” stated CISO Andrew Hollister. “Simplifying compliance reporting and enabling precise investigations empower teams to adapt to evolving threats.”

LogRhythm Axon helps streamline compliance reporting and log data management. Log streaming to AWS S3 offers a cost-effective way to retain searchable data for compliance and forensic needs. The new release includes out-of-the-box compliance frameworks and advanced real-time correlation for better analytics and investigations.

LogRhythm’s new Open Collection Architecture allows instant JSON data integration from third-party sources. The JSON normalization wizard simplifies customizations, and improved log source parsing enhances data correlation and analysis.

Phil Swain, CISO at Extreme Networks, praised the updates, highlighting the importance of accurate data in AI and network security. “LogRhythm’s regular updates help us maintain and improve our security posture.”

According to Dallas Hammer, CISO at NDM Technologies the JSON Policy Builder and Lumberjack JSON Listener make collecting and normalizing log sources easier, allowing their SOC to focus on detection rather than collection.

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