Abstract: Disclosed are systems and methods for continuous exposure management across multiple cloud environments. Posture control data, including configuration, vulnerability, and identity activity information, is continuously collected and aggregated into a unified exposure dataset. A machine-learning correlation model analyzes the dataset to identify combinations of seemingly unrelated low-risk events that collectively form higher-risk exposure conditions. Each exposure condition is assigned a risk score, and potential remediation actions are evaluated using a remediation priority score based on the amount of risk mitigated and the relative remediation effort. Remediation actions are then prioritized to optimize overall risk reduction efficiency. The system continuously updates exposure data and prioritization as new information is received, enabling dynamic and scalable management of cloud security posture and reducing the operational burden of manual prioritization.

Abstract: Systems and methods for favicon comparison-based similar domain detection include receiving a base domain, the base domain being associated with an enterprise; receiving a domain list comprising a plurality of domains; performing a favicon comparison between the base domain and each of the plurality of domains within the domain list; and classifying each of the plurality of domains within the domain list as one of being associated with the enterprise or not being associated with the enterprise based on the favicon comparison.

Abstract: Systems and methods for providing efficient remediations for cloud environment vulnerabilities. The present systems and methods are configured to calculate the most efficient remediations to reduce cloud environments' risks, calculate a cloud environment's biggest risks and weaknesses, and provide a holistic overview of a cloud environment across different service providers. In an embodiment, steps include scanning a cloud environment for posture control data; identifying a plurality of security risk events based on the scanning; calculating a risk score for each of the plurality of security risk events; and determining and recommending one or more remediations based on the risk score of each of the plurality of security risk events and how efficient each remediation is.

Abstract: Systems and methods for providing efficient remediations for cloud environment vulnerabilities. The present systems and methods are configured to calculate the most efficient remediations to reduce cloud environments' risks, calculate a cloud environment's biggest risks and weaknesses, and provide a holistic overview of a cloud environment across different service providers. In an embodiment, steps include scanning a cloud environment for posture control data; identifying a plurality of security risk events based on the scanning; calculating a risk score for each of the plurality of security risk events; and determining and recommending one or more remediations based on the risk score of each of the plurality of security risk events and how efficient each remediation is.