Product System

Aegis covers software development, build, testing, release, deployment, operation, and continuous iteration. Through SCA, SAST, IAST, DAST, and other specialized capabilities, it continuously discovers security issues in source code, open-source components, dependencies, the software supply chain, and applications at runtime.

By combining large language models with code context, dependency relationships, vulnerability intelligence, and business impact, Aegis performs in-depth analysis of findings. It helps organizations determine which risks are real, what impact they may have, and what should be addressed first, driving a closed loop from discovery and analysis through remediation and verification.

Traditional software supply-chain security products primarily provide component inventories and vulnerability alerts. Aegis goes further by focusing on whether the software as a whole is secure and how much software risk the organization has actually reduced.

Pharos continuously discovers the enterprise’s internet-facing, cloud, and previously unknown digital assets. It brings domains, IP addresses, ports, services, components, vulnerabilities, and asset changes into a dynamic attack-surface view, helping the enterprise understand its true external digital boundary.

Pharos uses AI to correlate and reason over scattered asset clues, helping determine ownership, identify anomalous exposure and material changes, and clarify which entry points attackers may exploit and which issues should be reduced first.

Pharos goes beyond traditional asset mapping and exposure inventories to address whether an asset belongs to the enterprise, what changed in its exposure, which entry points are most dangerous, and how exposure can be continuously reduced.

Argus integrates EDR, DLP, and UEBA to continuously monitor endpoint activity, data movement, and user actions, protecting enterprise endpoints and critical data. It focuses not on software code itself, but on the data, behavior, and security events produced after software is running.

Argus builds dynamic baselines through behavior learning, identifies anomalies from continuous behavior and contextual changes, and reconstructs scattered endpoint alerts, data events, and user actions into a complete incident narrative. This helps security teams determine what happened, which data was affected, and how to respond.

Traditional data-security products rely mainly on fixed rules and isolated alerts. Argus identifies complex anomalies that individual rules struggle to detect, reduces alert noise, and improves investigation and response efficiency.

Zprobe validates enterprise networks, applications, and business systems. Using AI to reproduce the testing approach of security experts, it proactively discovers potential security issues and confirms whether they can actually be exploited.

After the user defines the testing objective, Zprobe starts with asset and service identification, then progressively performs vulnerability detection, risk validation, and attack-path analysis. It continues deeper based on each finding and ultimately produces reproducible evidence, risk conclusions, and remediation priorities.

Traditional scanners mainly report potential vulnerabilities. Zprobe focuses on whether risk is real and whether defenses are effective. All validation is performed within an explicitly authorized scope. Any operation that may affect the business requires human confirmation and is logged end to end.