Panther Unveils Security Data Lake Search and Splunk Integration to Redefine Detection and Response at Scale
Panther Labs, a cybersecurity innovator for detection and response at scale, today announced the launch of its new Security Data Lake Search and Splunk Integration capabilities. These offerings mark a critical leap forward in managing security risks in today’s cloud-first landscape.
As organizations race to implement machine learning capabilities, they’re increasingly reliant on decentralized, cloud-based data stores and workflows to power the development of new software, such as AI tools. These workflows magnify security challenges, with organizations continuing to report severe security incidents due to cloud misconfigurations, especially in public cloud environments.
The enhancements Panther is launching today will redefine security detection, analysis, and response for the cloud-first, AI-powered future. By combining the economic efficiency of modern security data lakes with the familiarity of traditional SIEM interfaces, Panther will enable security teams to more easily identify and respond to threats, hardening their security posture for decentralized, high-scale cloud workflows.
Panther’s Security Data Lake Search is the industry’s first search experience designed to capitalize on the efficiency and performance of modern data lakes. With traditional solutions, high-volume log sources are too costly and unwieldy to ingest and search at scale, forcing organizations to choose between cost and performance. With Panther’s Security Data Lake Search, security teams can harness the full potential of mission-critical cloud logs in their detection and investigation workflows, with deployment options that reduce total cost of ownership (TCO) and maximize ROI. These enhancements offer unparalleled search performance across vast data lakes, without relying on SQL, enabling fast, efficient investigations.
Panther’s Splunk Integration combines Panther’s industry-leading, cloud-native detection capabilities with Splunk’s extensive analytics platform, giving organizations enhanced visibility of critical cloud workflows. By using Panther’s real-time detections on streaming cloud logs and configuring Splunk as an alert destination, security teams are empowered to implement rapid, cloud-scale detection and response workflows.
Together, Panther’s Security Data Lake Search and Splunk Integration unlock the full potential of high-volume, high-value cloud log streaming data. With cloud-native search capabilities and high-performance detections built on existing Splunk infrastructure, security teams can now ingest all of their logs and operate with the agility necessary to drive better security outcomes.
"We built Panther out of necessity to derive signal from noisy cloud logs and overcome the challenges traditional SIEMs face in cloud-native environments. Today we are releasing the first security analyst-grade search experience to the security data lake, fully unlocking its cost, performance, and governance benefits for security teams," said Jack Naglieri, CEO and founder of Panther Labs. “We know, however, that many organizations have significant investments with traditional SIEMs like Splunk. That’s why we’re also introducing an alerting integration with Splunk to give more mature teams the best of both worlds - high-scale augmentation of their existing workflows and rules without added friction.”
A customer at Zapier, the renowned automation platform, praised Panther's new capabilities: "With Panther's new Search and Splunk integration, we've transformed our approach to security data. We can now tap into a breadth of log data with finesse and agility, enhancing our threat detection without disrupting our existing workflows."
Panther has demonstrated significant value for a wide range of enterprise customers, with an average reduction in TCO by over 50%. As security risks from cloud-based workflows continue to escalate, Panther's platform is crucial for organizations aiming to bolster their compliance and reduce risk exposure efficiently.