ArmorCode Platform

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.

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.

Proactively rescans the estate within hours of a new critical vulnerability being disclosed in the wild, rather than waiting for the next scheduled scan window.

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

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

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

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.

Classifies aggregated findings with an AI model as real vulnerability, likely false positive, or needs review, and assigns a remediation urgency, so the priority queue is filtered by verdict rather than by tool severity alone.

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.

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

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.

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

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.

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.

Ingests, deduplicates and normalizes signals from security tools across DevSecOps pipelines and runtime environments (SAST, DAST, SCA, container scanning, secrets scanning, runtime and cloud telemetry) into a single finding model with a consistent severity scale across sources.

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

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

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

Compiles vendor, third-party and open-source maintainer reputation to flag risk from unmaintained, deprecated or abandoned software.

Detection of exposed secrets and credentials in build artifacts and software packages, with prioritized remediation that distinguishes active credentials from stale ones.

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