
Cohesity FortKnoxCohesity
Boost ransomware resilience with award winning, highly secure, cloud-based cyber vaulting.
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Cohesity
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Product details
Cyber vaulting and recovery for the modern era
FortKnox is a SaaS data isolation and recovery solution that improves cyber resilience with an immutable copy of data in a Cohesity-managed cloud vault. FortKnox provides an additional layer of protection against ransomware and other cybersecurity threats while dramatically simplifying operations and lowering costs, preparing organizations to recover confidently from attacks.
Features
- **Comprehensive security: Beyond Zero Trust: **Safeguard data with multilayered Cohesity Threat Defense Architecture—with immutability, WORM, access control, quorum, Cohesity-managed KMS, threat detection, and more.
- **ML-based early threat detection: **Leverage machine learning algorithms to detect anomalous backup snapshots and respond rapidly.
- **Integrate with your security ecosystem: **Extend existing security investments with integrations to SIEM, SOAR, KMS, and more.
- **Rapid implementation and shared responsibility: **Slash complexity and costs of “DIY” approaches and meet demanding SLAs with a single, trusted cloud service for data vaulting and recovery. No additional cloud storage or egress costs.
- **More choice and cost savings: **Cloud providers, recovery SLAs, and budgets vary for every organization. Choose between FortKnox warm and cold vaults on AWS or Microsoft Azure to select the option that best suits your business needs.
- **Ease of use: **Monitor global data vaults and scan for anomalous snapshots with a single UI.
- **Flexible recovery: **Recover data quickly and easily to the original or to an alternate location, including public or private cloud.
- **Confident recovery: **Easily and confidently identify an untainted copy of data for recovery in case backup data is attacked or lost due to disaster.
- **Granular recovery: **Recover whole volumes or specific files and objects quickly and easily, while ensuring the integrity of the data.