AI-powered adversaries are changing the speed and scale of cyberattacks. As attackers become more automated and adaptive, security teams need to identify suspicious activity before it becomes lateral movement, command-and-control activity, or a broader incident.
Cyntros AI uses Adaptive Machine Learning (AML) to detect suspicious network behavior, emerging attack patterns, and activity that existing tools may miss across hybrid, on-premises, and cloud environments.
See How Cyntros Detects the Unknown
Connect with a Cyntros AI security expert to discuss how Adaptive Machine Learning (AML) and agentless network detection can help identify suspicious activity, lateral movement, and emerging threats your existing tools may miss.
Signature- and rule-based tools remain valuable for known threats. But they may not identify new attack techniques or unfamiliar behavior until detection logic is created, tested, and deployed.
AI can help attackers rapidly vary tools, techniques, and attack paths, creating behavior that does not match known indicators or familiar attack patterns.
Critical attacker activity often happens across communications between users, systems, applications, and workloads, activity that may not be fully visible through endpoint telemetry or logs alone.
Cyntros AI uses Adaptive Machine Learning (AML) to establish a live behavioral baseline across users, systems, applications, and network activity. As your environment changes, the baseline evolves with it.
Instead of relying on signatures, predefined rules, or static pre-trained models, Cyntros identifies activity that deviates from normal behavior, including suspicious communications, lateral movement, and emerging attack patterns.
AML helps Cyntros detect suspicious behavior associated with both known vulnerabilities and previously unseen threats, even when activity does not match a familiar attack signature or rule.
Identify suspicious communications, lateral movement, command-and-control activity, and other network behavior that endpoint and log-based tools may not reveal.
Detect suspicious deviations as attacker techniques evolve, without relying on constant rule tuning, signature updates, or static pre-trained models.
Deploy out-of-band without installing endpoint agents or modifying production traffic flows, making it easier to add network-level detection to complex environments.
Traditional security tools are not designed to detect every form of malicious activity on the network. Cyntros AI addresses this gap with a fundamentally different approach, delivering a level of visibility rarely seen in conventional security platforms. 
CEO
Independent Testing Lab
Cyntros AI uses Adaptive Machine Learning to help identify suspicious network behavior, lateral movement, and novel
threats that traditional detection tools may miss.
Copyright © Auria 2025 All Rights Reserved
Copyright © Auria 2025 All Rights Reserved
