OX AINAPP

Ingests and normalizes findings from multiple AppSec tools (SAST, DAST, SCA, container scanning, secrets scanning) into a single unified finding model with a consistent severity scale across sources.

Groups findings from multiple tools that refer to the same underlying vulnerability in the same code location, presenting one actionable finding instead of multiple redundant alerts.

Scores aggregated findings using multiple contextual factors (exploitability, reachability, internet exposure, threat intelligence, and business criticality) rather than individual tool severity ratings, producing a single actionable priority queue across all AppSec signals.

Scores dependency vulnerabilities by whether the vulnerable function is reachable in the actual application execution path, not just present in the dependency tree, reducing the actionable finding list to confirmed code-level exposures.

Links each finding to the specific code, component, or pipeline that introduced it and traces it from source through build to the deployed runtime, so teams can fix the underlying cause and see which projects contribute the most risk.

Pushes prioritized findings to developer ticketing (Jira, GitHub Issues, Linear), and IDEs with remediation context, removing the security team from the routing path.

Evaluates all applications against organization-wide AppSec policies (minimum scan coverage requirements, severity thresholds, mandatory compliance checks), and flags non-compliant applications.

Maps aggregated AppSec findings and scan coverage to regulatory and framework controls (PCI DSS Requirement 6, ISO 27001 Annex A.8.28, SOC 2), and generates audit-ready evidence and compliance reports across the application portfolio.

Maintains a registry of all applications in scope, their associated scan coverage, and their AppSec tool assignments, surfaces applications with no active scanning.

Integrates and triggers AppSec scanners across the pipeline, controlling which tests run at each stage (pull request, build, release) according to organizational policy rather than leaving each tool to run on its own schedule.

Verification of build integrity and artifact provenance through signing, attestation, and change attribution.

Assessment and policy enforcement of CI/CD pipeline configuration, access, and integrity.

Risk context for open-source dependencies including reachability, exploitability, and upgrade impact.

Live visibility into code, components, pipelines, and developer activity across the software development lifecycle.

Detection and provenance tracking of AI and ML components, models, and LLM usage within the software supply chain.

Governs third-party software consumption to apply consistent software supply chain security policy.