Abstract: Systems and methods provide agentless security assessment for workloads and cloud posture control across multi-cloud environments. Discovery modules are configured with collection intervals to ingest posture control data including assets, identities, configurations, activities, network flows, and build-time artifacts. A multi-cloud configuration inventory maintains current and historical states and produces misconfiguration and identity-activity findings. For workload vulnerability evaluation, an external snapshot manager obtains point-in-time root-disk state without installing an in-workload agent. A file system data processor derives operating system and package metadata, and a detector matches the metadata against a vulnerability feed refreshed on a recurring basis to identify vulnerabilities. Identified vulnerabilities are correlated with misconfiguration and activity findings to generate prioritized risk exposures.

Abstract: Systems and methods for agentless workload vulnerability scanning include creating a snapshot of a workload in a cloud environment and analyzing workload data from the snapshot to identify one or more characteristics of the workload. The characteristics can be used to identify vulnerabilities present in the workload by correlation. These identified vulnerabilities can be persisted in a database and displayed to users for alerting and remediation.

Abstract: Systems and methods for agentless workload vulnerability scanning include creating a snapshot of a workload in a cloud environment and analyzing workload data from the snapshot to identify one or more characteristics of the workload. The characteristics can be used to identify vulnerabilities present in the workload by correlation. These identified vulnerabilities can be persisted in a database and displayed to users for alerting and remediation.