Apply an agentless, cloud-native DLP solution to prevent data leakage across myriad services

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The dangers of digital data are resonating across the globe. According to Cyber CRX, over 80% of organizations believe they have experienced at least one cloud data breach due to digital transformation.

Why the fear? Data democratization, the use of cloud technologies such as microservices, and constant sharing of data in and outside of the organization have generated a huge data sprawl. This has left security leaders with poor visibility as to where sensitive data (e.g. PII, PHI, PCI, trade secrets) resides, how it moves across different clouds, and who is accessing it. That, coupled with growing industry and compliance regulations involving data privacy, data sovereignty, and data security, have increased the need for a data-centric solution.

Current solutions have much to be desired

Unfortunately, traditional, agent-based data leakage prevention (DLP) solutions, which are designed to protect on-premise data, have their limitations. They rely on the network or the endpoints, neither of which is involved in most cloud data breaches.

Cloud provider solutions also fall short of the mark. Despite offering DLP capabilities, they cover only a fraction of all available services, do not trace the lineage of data when it travels beyond the cloud, and fail to provide a centralized view of data. 

The need for a cloud-native, data-centric security solution that adapts DLP principles to today’s complex cloud environments is clearer than ever. And to be most effective, the solution needs to ensure that your data never leaves your cloud, onboards quickly, and does not impact your production environment.

Organizations that experienced a breach and expect another within a year
SC Media
Average cost of a public cloud breach
Number of days, on average, to identify and contain a data breach
IBM Security

Gain visibility and classify data and find shadow data with sensitive information without impacting your production environment

  • Discover and classify active and shadow data assets in AWS, Azure, GCP, and Snowflake to find PII, PCI, and other buried “crown jewels”
  • Accelerate compliance readiness with automated classifiers for all major regulations, including FTC, GLBA, and SOX
  • Define custom classifiers to find sensitive information across managed and unmanaged data assets

Strengthen your data security posture to reduce data exposure caused by public cloud environment

  • Assess your data security posture across all data assets to tighten access permissions, fix misconfigurations, and govern active identities
  • Protect sensitive data against loss, theft, misuse, and unauthorized access

Apply an agentless cloud DLP with real-time data detection and response (DDR) to stop data exfiltration and reduce dramatically your MTTD/MTTR1

  • Detect and respond to data security and compliance issues, including the creation of external data flows with sensitive information, as soon as they occur 
  • Integrate security alerts into your cyber operations teams to automate your response and increase your visibility
  • Leverage a threat model built on a proprietary database of historical breaches to assess each event in real time and to determine data exfiltration potential
MTTD: mean time to detect
MTTR: mean time to respond

Dig Security uses agentless technology to discover, classify, and secure your data with zero impact on your production environment

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