See all network activity in and out of a particular pod, service, or application. Investigate suspicious traffic over a given time to easily audit container network anomalous behavior and investigate security events.
Using our full-AI behavioral analysis, you can easily secure workloads and applications running in hybrid and public cloud environments, thus mitigating risks from breaches, data leakage, and zero-day threats.
or communication with unexpected destinations, our behavioral analysis can help to detect attack attempts and make them easier to contain.
to dynamically deliver anomaly detection that automatically grows and scales with your cloud environments. Using Sharelock, you can easily secure workloads and applications running in hybrid and public cloud environments, thus mitigating risks from breaches, data leakage, and zero-day threats.
Secure network leveraging the power of our full-AI anomaly detection system.
Detect malicious network behavior, and anomalous communications, and prevent threats, vulnerability exploits, and malware activities in your cloud environments.
Separate sensitive data from less sensitive data, create separate segments for different types of workloads or activities.
Detects and correlates internal network traffic anomalies to easily monitor container network anomalous behavior and prevent attacks.
Sharelock builds an evolving understanding of your cloud environment.
By learning all the interactions happening in your network, it detects and responds to unpredictable and new cyber threats. Sharelock brings self-learning AI to your cloud, analyzing data in milliseconds, in real-time, as it happens to detect anomalies and prevent to attacks in real-time.
Automatically kill malicious containers or processes to block attacks. Audit users, commands, files, and net activity to know what happened. Capture system activity, including commands, network connections, and file activity. Enrich events using container, Kubernetes, or cloud metadata. Easily forward events to your security tools.
