Reveal Security utilizes patented Identity Journey Analytics™ and unsupervised machine learning to detect insider threats and identity-based attacks across applications and cloud services by analyzing user behavior patterns. This technology addresses the challenge of identifying malicious activities post-login, significantly reducing false positives and improving response times for security operations teams.
Funding
$26.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
DLFounders
Product
Problem
Organizations face challenges in detecting malicious activities that occur after a user has already logged in, making them vulnerable to insider threats and identity-based attacks. Existing security systems often struggle to identify anomalous behavior within applications and cloud services, leading to delayed responses and potential data breaches. Traditional rule-based detection systems and next-generation SIEM/UEBA solutions generate excessive alerts, overwhelming security operations teams.
Solution
Reveal Security offers a platform that leverages patented Identity Journey Analytics and unsupervised machine learning to detect insider threats and identity-based attacks across applications and cloud services. By analyzing the typical behaviors of human and machine identities, the platform identifies anomalies that are highly correlated to malicious activities. This approach provides accurate detection and context, reduces false positives, and enables prompt responses before business impact. The platform delivers visibility across business processes by analyzing identity behavior and journeys across applications, converting complex application-specific logs into actionable insights.
Target Audience
The primary target audience includes security operations teams, CISOs, and IT professionals seeking to improve their ability to detect and respond to insider threats and identity-based attacks within applications and cloud environments.
Features
- Patented Identity Journey Analytics using unsupervised machine learning to learn typical user behaviors.
- Anomaly detection based on deviations from learned behavior patterns, indicating potential threats.
- Support for human users, privileged users, APIs, and service accounts.
- Visibility across applications and cloud services, providing a complete picture of user activity.
- Automated analysis of application-specific logs, eliminating the need for deep application expertise.
- Rapid deployment with immediate results, demonstrating business value within days.
- Reduction in alerts by up to 99% through accurate detection and filtering of false positives.