Detect anomalies that can signal risky behavior or even breach

Advanced, multi-dimensional analysis of cloud and web usage

Machine learning and anomaly detection

The use of cloud and web services is increasing rapidly in organizations everywhere. More importantly, many of these cloud services are becoming mission critical, supporting your core business processes and housing your sensitive business data. With the growing importance of the cloud, it is critical to guard against threats to your cloud services.

The Netskope Security Cloud uses machine learning algorithms and an advanced rule engine to detect anomalies that could indicate unauthorized access, credential abuse, data exfiltration, and more. Netskope adaptive machine learning continuously analyzes user behavior and detects deviations that could indicate malicious activities. Netskope also analyzes cloud and web usage against an extensive set of predefined conditions. You can prioritize anomalies by risk level, filter down to what matters most, and drill down into forensic details for a detected anomaly so you can take the appropriate action.

Machine learning

Netskope adaptive machine learning continuously analyzes multiple dimensions of user behavior to create a baseline of normal user behavior. This baseline is automatically and continuously adjusted based on the changing usage of your cloud and web services. When deviations from the baseline are detected, alerts are generated to trigger further investigation and corrective action.

Analyze multiple dimensions of user behavior, including time, day, location, device, service, activity and object
Unsupervised, adaptive machine learning engine is self-training and self-adjusting

Data anomalies

With more of your sensitive data moving to the cloud and web, it is vital to understand how your data is moving in and out. Netskope identifies data movement anomalies such as bulk downloads, uploads, and deletions as well as the movement of sensitive data between cloud services that could indicate a data exfiltration attempt.

Bulk file uploads, downloads, and deletions
Data exfiltration to unsanctioned cloud services

Location anomalies

The anytime, anywhere nature of the cloud and web provides clear productivity benefits to your organization, but unfettered cloud access opens up your organization to unnecessary risks. Netskope helps you reduce the attack surface by analyzing the geographic locations associated with your cloud and web usage and detecting location-based anomalies that could indicate malicious activity.

Multiple access attempts from users in different, distant locations
Access from known risky countries

Credential anomalies

With visibility into activity-level usage across cloud and web, as well as threat intelligence feeds that allow you to associate your users with known external credential breaches, Netskope provides the ability to detect potential credential misuse and remediate the risk of unauthorized access to your cloud services and websites.

Compromised credentials
Shared credentials
Login failures

Be alerted to anomalies on your dashboard

The Netskope dashboard provides a high-level view of risk across all of your cloud services and websites, including risky services and websites, risky users, malware, compromised credentials and anomalies.

Users affected by known credential breaches

People often reuse their passwords across multiple sites, so it’s important to know if any of your users have been affected by an external credential breach. The compromised credentials dashboard helps you identify any affected users and the source of the compromised credentials.

Drill down into forensic details for each anomaly

From the high-level view of detected anomalies, it’s easy to filter by risk level or anomaly type and drill down into a specific anomaly. This detailed forensic information helps you assess the situation and drive correction action.

Trusted by leading companies

It's very reassuring to know that Netskope's platform is constantly looking at patterns and strange behavior to detect threats from insiders and bad actors. We're simply ill-equipped to handle this without this type of detection technology.
- Security Architect, Global Retailer

Top Use Cases

Insider threats

Use Netskope machine learning and user behavioral analytics to detect unusual data patterns, such as bulk downloads, that could indicate that an employee is amassing sensitive information in advance of leaving the organization. Use Netskope DLP to understand which content is being collected, and use this information to drive further investigation and take appropriate action.

Compromised users

Many people reuse their usernames and passwords, so it is important to know if any of your users have been affected by an external credential breach. You can use this information to raise awareness with your users, or leverage Netskope integrations with single sign-on (SSO) solutions to require a password change or stepped up authentication for any affected users.

Risky locations

Anomalous locations could be another indication of unauthorized access attempts. Use Netskope machine learning and user behavioral analytics to baseline the normal locations from which your users access your cloud services and websites. Reduce the attack surface by detecting access attempts from risky or improbable locations and use this information to inform your security policies.

Netskope Security Cloud — data sheet

Learn about all the features included in the Netskope Security Cloud and how it protects your organization’s SaaS, IaaS, and web use.

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Netskope Advanced Threat Protect — data sheet

Learn how Netskope Advance Threat Protect performs deep analysis to detect and prevent evasive, zero-day threats from the cloud and web.

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