Apply AI-driven behavioral analysis to native OS logs for real-time detection of advanced threats. Logster.ai secures your environment by identifying sophisticated attacks the moment they trigger.
Continuously evaluate Windows and Linux telemetry streams using proprietary AI models engineered for security detection. By processing logs in real time, logster.ai identifies anomalies and active attacks as they unfold, stopping threats before they result in significant data loss.
logster.ai ingests native operating system logs such as Sysmon and PowerShell on Windows, and auditd and eBPF on Linux, in a secure streaming manner.
These events are processed in real time by a hybrid detection engine that combines:
This approach allows logster.ai to detect anomalies, attack sequences, and malicious behavior, even when no known signature exists.
Deploy a proprietary detection engine engineered specifically for high-fidelity, real-time security analysis. Logster.ai eliminates third-party dependencies, providing a streamlined, in-house architecture that processes telemetry with maximum efficiency and minimal latency for instant threat visibility.
Key characteristics:
Synthesize advanced machine learning models with curated detection logic to identify sophisticated attack vectors. This dual-layer approach filters out environmental noise while surfacing high-confidence threats, ensuring that your security team focuses only on critical, actionable incidents.
Aggregate and learn behavioral baselines across distributed environments to distinguish normal operations from malicious intent. By analyzing cross-host telemetry, logster.ai identifies lateral movement and coordinated attack patterns that isolated endpoint solutions often fail to detect.
Identify multi-stage attack campaigns by analyzing telemetry sequences and temporal relationships across the kill chain. Logster.ai correlates disparate events over time to expose the underlying intent of an adversary, transforming fragmented logs into a coherent, actionable narrative.
Map emerging threats to specific techniques and tactics using the MITRE ATT&CK framework and our proprietary taxonomy. Logster.ai provides instant classification of attack vectors, enabling your team to determine the exact nature and progression of an incident with unparalleled technical precision.
Calculate granular severity scores by evaluating the complete lifecycle of an attack sequence rather than isolated telemetry events. This contextual weighting ensures that high-impact threats are elevated immediately, allowing your security team to focus resources on the most critical risks facing the infrastructure.
This enables SOC teams to focus on high-risk, high-confidence alerts.
Evaluate process creation, script execution, and command-line arguments to identify sophisticated persistence techniques. Logster.ai scrutinizes execution flow across the OS to expose hidden backdoors and unauthorized lateral movement within your environment.
Detect unauthorized system calls, privilege escalation, and kernel-level anomalies using high-fidelity telemetry. Logster.ai monitors core OS interactions to identify deep-seated exploits and rootkit behaviors that bypass standard application-layer security.
Process telemetry in real time as events arrive to enable immediate threat detection and rapid incident response. Logster.ai eliminates batch-processing delays, ensuring your defensive posture evolves at the speed of an active compromise.
Establish behavioral profiles for every host to identify meaningful deviations from standard operational norms. Logster.ai utilizes host-specific modeling to surface subtle anomalies, ensuring that localized threats are detected without triggering global false positives.
Categorize malicious activities using industry-standard frameworks alongside proprietary classification models. Logster.ai maps telemetry to specific tactics, providing technical clarity on the attack vector and its current stage within the kill chain.
Score alerts by correlating threat severity with model confidence across identified attack sequences. Logster.ai prioritizes high-risk incidents, allowing security teams to address the most certain and impactful threats first to minimize potential downtime.
Provision logster.ai as a cloud-hosted SaaS, a private cloud instance, or a local on-prem inference engine. Our flexible architecture supports air-gapped and sensitive environments, ensuring full data sovereignty without compromising real-time detection capabilities.
Our team is here to help with questions about logster.ai, deployments, and detection capabilities.
