Seemplicity Agentic Exposure Action Platform

Aggregates and deduplicates findings from network scanners, endpoint agents, cloud scanners, and third-party tools into one normalized record for cross-estate risk ranking.

Incorporates asset metadata (network exposure, business criticality, data classification) into vulnerability prioritization so that a critical CVE on an isolated internal test system ranks lower than a medium CVE on an internet-facing payment server.

Cross-references the vulnerability inventory against live threat feeds tracking CVEs under active exploitation in the wild, surfacing vulnerabilities with confirmed attacker activity.

Assigns likelihood-of-exploitation scores using threat intelligence, vulnerability characteristics, and active exploit availability, independent of CVSS, which measures severity rather than exploitability.

Creates tickets, assigns owners, and tracks remediation progress in ITSM platforms (ServiceNow, Jira), closing the loop between finding and fix rather than producing a static report.

Enforces remediation deadlines by severity, reports on SLA compliance, and escalates overdue findings through configured approval chains.

Scans cloud resource configurations and container image CVEs alongside traditional OS and application vulnerabilities in a unified risk view.

Time-boxed risk acceptance workflow with documented approvals that keeps exceptions active and tracked as new scan data is ingested, rather than silently closing or re-opening findings.

Discovers assets and their exposures across the external, internal, cloud, and end-user attack surfaces, covering endpoints, network and on-premises infrastructure, identities and entitlements, hosts, containers, IoT and OT, and cloud platforms and applications, either through native discovery or by integrating third-party discovery sources, and reports vulnerabilities, misconfigurations, unmanaged assets, and compliance gaps in one inventory.

Confirms whether prioritized exposures are actually exploitable by running or ingesting adversarial validation results, such as breach and attack simulation or automated penetration testing delivered natively or by an integrated third-party tool, and re-ranks or closes exposures on the outcome so the queue reflects confirmed rather than theoretical risk.

Ranks exposures by their accessibility, visibility, and exploitability combined with asset criticality, business impact, and the security controls already in place, so a medium-severity issue on a critical, reachable, unprotected service outranks a high-severity issue on an isolated or compensated one.

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

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

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.

Groups assets into business processes, applications, or protection surfaces with named owners and criticality, so each exposure management cycle is scoped to what the business must protect and exposure is assessed and reported per scope rather than across the whole estate.

Uses generative AI to produce exposure-specific fix instructions, scripts, or remediation playbooks from the finding and its asset context, so remediation owners receive an actionable plan instead of a generic advisory.