XM Cyber Continuous Exposure Management Platform

Executes simulations using non-destructive payloads and read-only techniques that cannot cause data loss, service disruption, or lateral damage in production environments.

Provides specific detection rule recommendations, log source requirements, and control configuration changes for each identified gap: not just a list of undetected techniques.

Runs attack technique sequences on a scheduled or continuous basis against production controls, surfacing control drift between point-in-time assessments without human intervention.

Maps executed attack techniques to the MITRE ATT&CK framework and reports coverage across the attack lifecycle, enabling threat-informed gap analysis and detection engineering.

Executes cloud-specific attack techniques including IAM privilege escalation, SSRF to metadata services, storage bucket enumeration, and cross-account role assumption to surface cloud exploit paths.

Dynamically discovers and chains exposures (unpatched CVEs, misconfigurations, and credential weaknesses) into multi-step exploit paths without predefined scripts, sequencing weaknesses in the order an attacker would based on live environment state.

Ranks remediation by the impact of validated attack paths and blast radius rather than raw CVSS scores, directing effort toward the weaknesses that actually enable compromise.

Re-tests specific validated weaknesses after remediation to confirm each fix closed the attack path, closing the validation loop between testing and remediation.

Ingests estate context such as asset discovery, attack surface management, and vulnerability data, natively or through integrations, to scope and prioritize validation against the assets and exposures that matter most.

Safely exploits discovered weaknesses to produce empirical evidence of exploitability for each finding, replacing theoretical vulnerability data with confirmed attack outcomes and reducing false positives.

Reports which executed techniques triggered alerts in existing security controls and which did not, mapping undetected techniques to the specific control or detection rule that should have fired.

Trends control efficacy and validated exposure across runs and baselines results against industry peers, giving executives and asset owners scorecards that show whether security posture is improving rather than a one-time list of findings.

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

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.

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.

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.

Enriches cloud misconfigurations, vulnerable workloads, and runtime detections with threat intelligence on active exploitation, prioritizing exposures attackers use over theoretical severity alone.

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

Continuously inventories exposures across internet-facing assets, cloud, SaaS, and identity, including shadow IT, misconfigurations, and excessive permissions beyond CVE scanning.

Confirms whether a discovered vulnerability is exploitable in the specific environment through automated exploitation testing or manual validation, distinguishing confirmed risk from theoretical risk.

Models how exposures chain across assets and identities to reach critical systems, mapping attack paths and blast radius to separate reachable crown-jewel risks from dead ends.

Ranks exposures by combining exploitability signals with asset business criticality, so that a medium CVE on a critical customer-facing service ranks above a high CVE on an isolated dev instance.

Creates and tracks remediation tasks across teams and ticketing systems, measuring exposure reduction over time rather than simply listing open findings.

Generates trend reports on exposure posture (new exposure, remediated exposure, outstanding exposure by severity), in business language suitable for security program reviews.

Maps the discovered exposure inventory against active threat actor targeting and in-the-wild exploitation data to surface vulnerabilities under active attack.

Tracks the life cycle of exposures through a centralized, aggregated view supported by automated workflows.

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.

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.

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.