DSPM FOR APPLICATION ENVIRONMENTS

Achieve real-time data observability without compromising efficiency

Soveren provides critical DSPM features to protect PII and PCI data in production, in-motion and at-rest:
Single-pane-of-glass observability
Build an automated and complete view of your application environments in near real-time and without blind spots.
Leverage Kubernetes and cloud APIs to gain additional critical context, such as ownership, location, labels, namespaces, etc.
Sensitive data and asset mapping
Visualize sensitive data, including shadow data, as it flows between services, data assets, API endpoints, and third-party integrations.
Complete data landscape coverage
Avoid data-at-rest blindness and gain near real-time visibility into the lifecycle of sensitive data in Kubernetes-based environments.
High-precision ML-based data discovery
Automate sensitive data discovery and classification with a 98% detection rate and coverage of 45+ PII, PCI, and PHI data types across 30+ countries.
Detect sensitive data in near real-time as it flows between services and data stores with zero impact on application latency or performance.
Flexible and easy-to-use policy engine
Start immediately with baseline monitoring and alerting of any changes in your data flows that could result in data breaches and privacy violations.
Leverage out-of-the-box policies developed by Soveren or build custom rules tailored to the unique aspects of your business.
Real-time risk detection and notification
Enhance manual security guardrails with continuous identification and alerting of changes, misconfigurations, and violations.
Seamless integrations with security stack
Increase security and engineering efficiency by fitting easily into the operational workflows via integrations with tools like Slack and Jira.
Deep technical context for rapid remediation
Empower engineering teams to quickly resolve issues with alerts that include valuable technical context.
Bridge the gap between security and engineering by pinpointing the root-cause of the problem (e.g., the exact API violating the policy).
And even more...
Prioritize data protection efforts by categorizing the assets based on the sensitivity of the data they process
Find data stores and data flows that you know about and ones that you don’t, and monitor any changes
Proactively remove security, privacy, and compliance risks to prevent them from becoming full-blown incidents
Gain optimized alert prioritization based on correlating Soveren’s data sensitivity context with the security posture from SIEM or CSPM
No PII, PCI, or other sensitive data leaves your environment. Ever.
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Seamless, zero-impact deployment with high-quality, automated data detection

Soveren seamlessly integrates with Kubernetes / AWS and analyzes the traffic with no impact on application performance. It uses proprietary ML techniques to detect and classify sensitive data with high precision, in near real-time and fully automatically, without manual setup.
Data classification engine
Traffic interceptors use packet-capturing technology to mirror the traffic of all services on the kubernetes nodes before passing it to the data-classification engine. It is designed to allow for ease of deployment, zero maintenance effort, and no impact on latency or performance.
Interceptors
The data classification engine is a centralized component of the agent and is separate from the traffic interception. They are designed to ensure an optimal balance between low resource consumption and high detection quality, while adhering to the strictest security requirements.
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Powerful ML models to detect and classify sensitive data

Detects sensitive data with a 98% success rate, including unknown data.
Optimized to minimize the number of false-positive alerts.
Works out of the box with no configuration or manual setup.
Supports detection of 45+ data types and 30+ languages.
Automated learning cycle to continuously improve detection quality.

Soveren seamlessly maps assets and data in production

Native Kubernetes deployment (via Helm) that takes 15 mins or less.
Automatically discovers all services deployed in Kubernetes.
Automatically discovers data stores located in AWS.
Has zero impact on application performance (by mirroring the traffic).
No sensitive data is transmitted outside of your environment.
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