Prove What's Exploitable. Before Attackers Do.

Singularity Cloud Native Security uses the Offensive Security Engine to mimic a real outside attacker in order to validate which exposures are truly exploitable, not just theoretically vulnerable. It then uses Attack Path Analysis to map how those exposures connect to form complete kill chains, and DSPM to identify whether sensitive data is in the line of attack. 

This evidence-based approach increases analyst efficiency by up to 66% and focuses remediation on the exposures that pose real risk.

Attack Path Analysis maps how individual cloud exposures, such as misconfigurations, excessive permissions, and vulnerabilities, connect to form exploitable paths from initial access to critical assets. 

It matters because isolated findings lack context. A misconfiguration that leads nowhere is low priority, but the same misconfiguration connected to sensitive data through a chain of exploitable resources is critical. Attack Path Analysis provides that distinction.

DSPM (Data Security Posture Management) automates the discovery and classification of sensitive data across cloud environments and AI training pipelines. Singularity Cloud Native Security integrates DSPM with Attack Path Analysis so teams can see not just where exposures exist, but whether sensitive data is in the blast radius. This links data security directly to exploitability, enabling smarter remediation prioritization.

AI-SPM (AI Security Posture Management) provides visibility into AI models, services, and data flows deployed across your cloud environment. As organizations adopt AI tools and services, AI-SPM gives security teams the visibility to govern that usage, identify misconfigurations and data exposure risks specific to AI workloads, and ensure AI deployments align with security and compliance policies.

Most cloud security tools generate thousands of findings without distinguishing between theoretical and proven risk. Singularity Cloud Native Security uses the Offensive Security Engine to validate actual exploitability and Verified Exploit Paths to show evidence of real attack vectors. 

This focus on proven risk over theoretical findings has driven a 66% improvement in analyst efficiency through reduced manual validation and automated remediation, with customers reporting up to 50% reduction in time spent finding security issues.