Cyera
ProductPaidSecure, manage, and protect sensitive data seamlessly across...
Capabilities12 decomposed
cross-environment sensitive data discovery
Medium confidenceScans and identifies sensitive data (PII, credentials, API keys, secrets) across hybrid and multi-cloud environments including AWS, Azure, GCP, and on-premises systems simultaneously. Uses pattern recognition and contextual analysis to detect data that other tools miss, including credentials in logs, PII in backups, and API keys in code repositories.
automated data risk remediation
Medium confidenceAutomatically remediates identified data security risks by taking corrective actions such as encrypting exposed data, removing credentials, restricting access, or quarantining sensitive files. Prioritizes risks based on exploitability and business impact to prevent alert fatigue.
data retention and lifecycle policy enforcement
Medium confidenceEnforces data retention and lifecycle policies automatically, ensuring data is retained only as long as required and deleted or archived according to policy. Helps organizations comply with data minimization requirements.
shadow data and rogue system detection
Medium confidenceIdentifies unauthorized, unmanaged, or shadow data stores and systems that exist outside official IT oversight. Detects rogue cloud accounts, unauthorized databases, and unmanaged data repositories.
unified data governance policy enforcement
Medium confidenceEnforces data governance and security policies consistently across hybrid and multi-cloud environments through native integrations with identity and access management systems. Enables real-time policy application and compliance verification across all data locations.
sensitive data classification and tagging
Medium confidenceAutomatically classifies discovered data by sensitivity level (PII, PHI, financial data, credentials, etc.) and applies consistent tags and metadata across all environments. Enables downstream governance and remediation decisions based on data classification.
multi-cloud data inventory mapping
Medium confidenceCreates a unified, queryable inventory of all data assets across AWS, Azure, GCP, and on-premises systems with detailed metadata about location, ownership, sensitivity, and access patterns. Provides visual maps and dashboards showing data distribution and relationships.
servicenow integration for ticketing and tracking
Medium confidenceIntegrates with ServiceNow to automatically create, update, and track remediation tickets for discovered data security issues. Enables security teams to manage data risks through existing incident management workflows.
okta identity integration for access control
Medium confidenceIntegrates with Okta to enforce data access controls based on user identity, roles, and risk context. Enables dynamic access decisions and policy enforcement tied to identity and access management.
compliance audit trail and reporting
Medium confidenceGenerates comprehensive audit trails and compliance reports documenting all data discovery, classification, access, and remediation activities. Provides evidence for regulatory audits and compliance certifications.
real-time data access monitoring
Medium confidenceMonitors and logs all access to sensitive data in real-time across all environments, detecting unusual access patterns and potential data exfiltration attempts. Provides visibility into who is accessing what data and when.
data exposure risk scoring and prioritization
Medium confidenceAnalyzes discovered data exposures and assigns risk scores based on data sensitivity, exploitability, business impact, and context. Prioritizes risks to focus remediation efforts on the most critical issues.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓Large enterprises with multi-cloud infrastructure
- ✓Organizations with complex hybrid environments
- ✓Security teams managing regulated data
- ✓Security operations teams managing large numbers of data risks
- ✓Enterprises wanting to reduce manual remediation overhead
- ✓Organizations needing consistent enforcement across environments
- ✓Regulated industries with strict retention requirements
- ✓Organizations managing large data volumes
Known Limitations
- ⚠Requires 3-6 month implementation timeline for large enterprises
- ⚠Needs integration setup across multiple cloud platforms and on-prem systems
- ⚠Pricing scales with data volume, making it expensive for data-heavy organizations
- ⚠Requires careful policy configuration to avoid unintended data modifications
- ⚠Some remediation actions may require approval workflows
- ⚠Effectiveness depends on proper risk prioritization configuration
Requirements
Input / Output
UnfragileRank
UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.
About
Secure, manage, and protect sensitive data seamlessly across environments
Unfragile Review
Cyera delivers a much-needed unified approach to data security by mapping sensitive data across hybrid and multi-cloud environments, then providing automated remediation and governance controls. It's particularly strong for enterprises drowning in shadow data and fragmented security tools, though it requires substantial organizational buy-in to realize its full potential.
Pros
- +Comprehensive data discovery engine that actually finds what you're missing—credentials in logs, PII in backups, API keys in code repos—across AWS, Azure, GCP, and on-prem simultaneously
- +Automated remediation and risk prioritization prevents alert fatigue by focusing teams on genuinely exploitable vulnerabilities rather than theoretical exposures
- +Native integrations with Okta, ServiceNow, and major cloud platforms eliminate manual context-switching and enable real enforcement of data governance policies
Cons
- -Implementation complexity and onboarding timeline can stretch 3-6 months for large enterprises, requiring dedicated resources and buy-in from multiple teams
- -Pricing scales aggressively with data volume and environment complexity, making it a significant investment that may be prohibitive for mid-market companies
Categories
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