Use Netskope One SASE to address insider risk by adding safeguards from the inside out. Start by using data protection to manage access to critical assets and control movement. Use contextual, behavior-driven controls to enable dynamic authorization policies based on risk factors and signals from the environment. Apply behavioral analytics, machine learning, and visualizations to focus on what’s going on, and what’s changing. These are key capabilities of the Netskope One Platform.
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Check application configurations, identify publicly shared cloud storage, monitor sensitive data movement, and coach users.
Stop cloud phishing, command and control, and unauthorized access to stop attackers from impersonating valid users.
Monitor risky/malicious behaviors with Netskope UEBA to detect insiders, compromised accounts, and data exfiltration.
Use User Confidence Index (UCI) risk scoring with adaptive policy controls.
Check application configurations, identify publicly shared cloud storage, monitor sensitive data movement, and coach users.
Stop cloud phishing, command and control, and unauthorized access to stop attackers from impersonating valid users.
Monitor risky/malicious behaviors with Netskope UEBA to detect insiders, compromised accounts, and data exfiltration.
Use User Confidence Index (UCI) risk scoring with adaptive policy controls.
One out of every seven users take data with them when they leave using personal app instances.
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Data protection in the Netskope One Platform provides both inline-based controls for data movement and API-based controls to monitor data at rest.
User and Entity Behavior Analytics (UEBA) with AI/ML models dynamically identifies user and application risk factors to generate real-time user risk scores that influence adaptive policy decision.
Netskope Advanced Analytics provides a deep understanding of activity in the organization’s cloud, with pre-build and customizable dashboards designed to stay ahead of threats.
Data protection in the Netskope One Platform provides both inline-based controls for data movement and API-based controls to monitor data at rest.
User and Entity Behavior Analytics (UEBA) with AI/ML models dynamically identifies user and application risk factors to generate real-time user risk scores that influence adaptive policy decision.
Netskope Advanced Analytics provides a deep understanding of activity in the organization’s cloud, with pre-build and customizable dashboards designed to stay ahead of threats.
External threats have to break into your network, but insiders—employees, contractors, and vendors—already have legitimate credentials and access. Traditional security tools cannot easily distinguish between a software engineer doing normal work and a departing employee quietly downloading proprietary source code. Managing this requires looking past simple access permissions to analyze real-time intent and behavior context.
Industry data shows that 20% of users upload an unusually high volume of data to personal apps during their final days of employment. Netskope uses Instance Awareness to differentiate between your corporate cloud storage and an employee’s personal account. It can apply elevated scrutiny and stricter real-time DLP blocks to users in a “departing” lifecycle stage, automatically catching exfiltration to personal emails or cloud instances before they leave.
Widespread “Shadow AI” adoption has introduced massive accidental insider exposure. Employees frequently paste sensitive data, source code, or regulated PII into unauthorized public LLMs to help them work faster. Netskope addresses this by placing inline AI Guardrails that scan prompts and uploads in real time, stopping data policy violations without needing to issue a blanket block on the AI tools entirely.
Not all insider risk is malicious; most of it is accidental or negligent. Instead of silently blocking a user and generating a critical alert for your security analysts, Netskope pops up an in-context notification directly to the user. For instance, if an employee tries to share a confidential file publicly, the prompt explains the risk and guides them toward a secure alternative. This actively trains your workforce and cuts down repeat violations.
Static rules create thousands of false positives. Netskope applies machine learning and User and Entity Behavior Analytics (UEBA) to establish a baseline of “normal” behavior for every specific user. It flags anomalies—like an abrupt spike in bulk data movement, sudden late-night access, or impossible travel logins. These risk signals populate a dedicated Insider Threat Dashboard, allowing your SOC to quickly identify and triage true anomalies, reducing threat hunting times by over 70%.
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