01
Malware prevention
Inspect managed cloud services and inline cloud and website traffic and stop malware by quarantining and replacing suspicious files with inert tombstone files or blocking inline downloads.
02
Advanced threat protection
Leverage three options for prevention, detection, and advanced AI/ML-based threat analysis with the Netskope Security Cloud to ensure defenses match your needs.
03
Detect behavior anomalies
Take advantage of user and entity behavior analytics (UEBA) to baseline your users’ normal activities and detect anomalies, in real time, including within peer groups.
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Netskope Behavior Analytics (UEBA)
Leverage machine learning (ML) behavior analysis across the rich metadata of cloud and web traffic, plus API inspection of managed apps and cloud services to detect anomalies, plus rich contextual sequential anomaly rules including the following:
- ML analysis of streaming and batch metadata for UEBA anomaly detection
- Unsupervised ML analysis developed and trained by the Netskope AI/ML team ready to use in production tenants
- Model development, training, and maintenance includes dynamic peer groups, decay factors, and correlation models
- Sequential anomaly rules include bulk uploads, downloads, deletes, rare events, proximity, failed logins, risky countries, and data exfiltration including between company and personal instances
- User Confidence Index (UCI) scoring determines user risk for events and alerts, plus UCI scores can drive policy actions such as step-up authentication
- AI/ML spans operations, data security, UEBA, malware detection, and URL filtering within Netskope.
04
Prevent cloud phishing
Prevent cloud phishing and cloud-enabled threats with granular policy controls that enable company and personal instances, while blocking rogue account instances, payloads, and data exfiltration.
05
Detect insider threats
Detect insider threats with rich policy context, DLP for content, and behavior analysis for anomalous activity for cloud services and apps.
06
Machine learning anomalies
Leverage machine learning to detect anomalies across large sets of metadata rich with context for cloud services, apps and web traffic.
