Corelight Open NDR vs PySAD

Corelight Open NDR turns network and cloud traffic into evidence for security operations. Its detection combines machine learning, behavioral analytics, curated signatures and threat intelligence, with real-time detection and anomaly explanations. Automated triage and integrated response workflows provide context for containing threats. The platform brings network security monitoring, intrusion detection, static file analysis and intelligent packet capture together. It handles network traffic, packets, flow logs, cloud network traffic, protocol logs and files. Deployment options include physical, software, virtual, cloud and flow-log sensors across on-premises, air-gapped, hybrid and multicloud environments. Cloud-native sensors support AWS, Azure and Google Cloud; software sensors support Linux-based systems. Physical and software sensors are built for environments at 100+ Gbps scale. Native integrations cover SIEM, XDR, SOAR and cloud platforms, including Splunk, CrowdStrike, Microsoft, Elastic and AWS. A Logs API and MCP server support programmatic access. Pricing is on request, with capacity-based licensing. Corelight serves large enterprises and government agencies in more than fifteen countries.

PySAD is a free, open-source Python framework for online anomaly detection in streaming data. Its models update when each new data instance arrives, supporting sequential detection for univariate and multivariate data. The project describes 16 online detectors, including xStream, LODA, RS-Hash, Half-Space Trees, and Robust Random Cut Forest. It also provides stream simulators, evaluators, preprocessors, statistic trackers, postprocessors, and probability calibrators. Integrations allow batch anomaly detectors from PyOD to run in a streaming setting. Experiments can use supervised, semi-supervised, or unsupervised settings. The documentation says streaming methods may retain one instance or a small recent window to meet memory and processing constraints. Installation is available through pip or the GitHub source; the current README lists Python 3.10 or newer on Linux, macOS, and Windows. PySAD is self-hosted and distributed under a BSD 3-Clause license. Its plan costs nothing, and 17 labelled benchmark datasets are downloaded on first use.