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See how to uncover threats faster with automation
Leverage automation and machine learning to detect anomalies that signal malicious activity for cloud accounts and workloads deployed on AWS, Google Cloud, and Azure. With Lacework CWPP, you can:
- Continuously monitor users, apps, processes, and network behavior
- Uncover unknown threats like abnormal logins and escalation of privileges with patented Polygraph anomaly-based approach
- Identify malware and other known threats based on reputation score for files, DNS, and more
TRUSTED BY 900+ GLOBAL INNOVATORS
Delivering behavior-based threat detection
Learning how your environment operates and finding anomalous behavior, you can find potential exploits before an attack or vulnerability is known, widely publicized, or patched.
“I have never seen a solution with the capabilities and comprehensiveness of Lacework. Its unique approach automatically learns what’s normal across our infrastructure and detects behavior that deviates from the norm.”
Quickly find the signal in the noise
With Lacework, get better accuracy and fewer false positives with rules-optional anomaly-based threat detection.
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From signature- to anomaly-based detection
Go beyond threat feeds and uncover signals that indicate compromise from both known and unknown threats
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From burnout to balance
No need to spend time querying, tuning policies, or writing rules. Automate threat detection with behavioral analytics, threat intelligence, and anomaly detection.
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From chaos to clarity
A 90% reduction in alerts means a faster threat response. And with composite alerts, you can find active attacks by correlating disparate signals – even weak ones.
