Uptycs CNAPP

Discovers and classifies sensitive data in IaaS and PaaS stores such as object storage, databases, and data warehouses, surfacing data exposure risk alongside infrastructure findings.

Instruments workload behavior at the kernel level via eBPF without a traditional user-space agent. Provides syscall-level visibility into process execution, network connections, and file access in running containers and VMs.

Exports compliance evidence pre-mapped to framework control requirements (SOC 2, ISO 27001, PCI DSS), in formats auditors can consume directly: not raw CSV exports requiring manual assembly.

Monitors running pod and container behavior against policy, detecting unexpected process execution, network connections, and privilege escalation at runtime rather than at image scan time.

Analyzes IAM policies across AWS, Azure, and GCP to surface over-permissioned roles, unused permissions, and cross-account trust relationships that create lateral movement opportunities.

Enforces a single policy definition across AWS, Azure, and GCP resource types, translating to provider-native configurations rather than requiring separate policy sets per cloud.

Scans infrastructure-as-code templates (Terraform, CloudFormation, Kubernetes manifests, and Helm charts) for misconfigurations and policy violations before deployment, so issues are caught in the pipeline rather than in production.

Continuously audits cloud and Kubernetes configuration across AWS, Azure, and GCP against security benchmarks, flagging misconfigurations and identity-permission gaps that create exploitable exposures.

Correlates individual misconfigurations and CVEs into chained attack scenarios showing lateral movement paths from exposed entry point to a target asset. Produces a prioritized list of attack paths rather than a flat CVE inventory.

Delivers scan results inside developer IDEs and pipeline stages so developers receive findings before code merges, reducing the cost and cycle time of remediation.

Reads cloud volume snapshots out-of-band to assess workloads for vulnerabilities, secrets, and misconfigurations without agents or touching running instances.

Analyzes container images and dependencies for CVEs, malicious or compromised packages, and SBOM generation across the build pipeline.

Aggregates posture findings and policy enforcement across multiple cloud accounts, subscriptions, and projects from a single control plane, critical for organizations with 10+ cloud accounts.

Evaluates Terraform, CloudFormation, ARM templates, and Pulumi configurations at PR or pipeline time, catching misconfigurations before deployment.

Maps detected misconfigurations to specific control requirements across CIS Benchmarks, NIST 800-53, SOC 2, PCI DSS, HIPAA, and ISO 27001 in a single assessment pass.

Automatically corrects specific misconfiguration types (enabling or enforcing S3 bucket encryption, correcting overly permissive security group rules), with or without approval workflow based on risk tier.

Audits cloud service configurations across AWS, Azure, and GCP against security best practices and benchmarks, flagging misconfigurations such as public storage, permissive network rules, and disabled logging. Coverage breadth and per-service depth vary significantly across products.

Continuously discovers and inventories cloud resources across accounts, subscriptions, and projects so posture assessment runs against a current, complete picture of the environment rather than a stale or partial asset list. Coverage of newer and less common resource types varies across products.

Enforces pod security standards, network policies, and RBAC controls across Kubernetes clusters, blocking non-compliant workload deployments and detecting policy drift.

Scans container image layers for OS package CVEs and application dependency vulnerabilities at build time, registry push, or pre-deployment, before execution.

Captures a continuous record of workload events (process, network, file, syscall) for forensic investigation of incidents in running workloads.

Detects hardcoded credentials, API keys, and tokens left in running workloads and their file systems, so exposed secrets can be rotated before an attacker uses them for lateral movement.

Monitors process execution, network connections, and file system activity in running workloads using a kernel agent, eBPF sensor, or sidecar container to detect behavioral anomalies and known attack patterns.