SecureVisio

SecureVisio’s SIEM engine collects, normalizes, and correlates log data from across your entire IT infrastructure in real time. Log sources are ingested i.a. via Syslog, Windows Event Forwarding, NetFlow, RESTful APIs, ODBC, file agents, and email protocols — covering virtually any source without requiring agents on Windows systems.

The normalization engine supports CEF, LEEF, JSON, XML, URI, Syslog, and REGEX formats, with a graphical parser builder and multi-stage parsing for complex nested log formats. Parser versioning with rollback ensures that updates never disrupt production detection logic.

Correlation rules are evaluated at ingestion time and can reference parsed event fields, UEBA anomaly scores, vulnerability findings, CMDB asset metadata, Active Directory attributes, IoC databases, and MITRE ATT&CK technique mappings simultaneously — in the same rule, without external API calls. This native contextual enrichment is what separates SecureVisio from conventional SIEM architectures.

SecureVisio’s UEBA layer builds and maintains behavioral profiles for both user accounts and IT entities — with separate baselines for privileged versus standard accounts, and for workstations, servers, domain controllers, web servers, and systems outside the domain. Time-range awareness distinguishes normal working hours activity from off-hours anomalies.

Behavioral anomalies are written back into the main event stream as first-class events, making them directly available to the correlation engine and playbook triggers. This feedback loop between UEBA and SIEM is a core architectural differentiator: anomaly scores are not isolated in a separate dashboard — they actively drive detection and response.

UEBA telemetry operates without volume constraints. Behavioral models are built on unfiltered data, ensuring accurate baselines that minimize both false positives and missed detections.

SecureVisio’s SOAR module implements incident and vulnerability response processes. Every incident generated by the correlation engine enters an automated workflow that enriches data, tracks status and SLA timers, escalates when thresholds are breached, and assigns tasks to the right team members based on asset type, data classification, process criticality, and incident priority.

Playbooks are built through a graphical interface and support multi-step action plans, conditional branching, user interaction prompts, automatic scenario switching, and hundreds of pre-built integrations with external systems for enrichment, pivoting, and active response — including host network isolation, kernel-level process blocking, and enforcement of security policies on endpoints.

SecureVisio’s vulnerability management module goes beyond importing CVSS scores. Every vulnerability is prioritized across eight contextual dimensions: the security zone of the affected asset, the estimated probability of attacker presence in the environment, asset type and criticality, the sensitivity of data processed by the asset, services running on the asset, CVSS parameters, configuration compliance status, and estimated breach probability from the asset’s current zone.

This means a medium-severity vulnerability on a domain controller with access to sensitive data is correctly weighted above a critical-CVSS finding on an isolated development system with no external exposure. The result is a prioritization output that reflects real operational risk — not just raw severity scores.

SecureVisio maintains a continuously updated record of all IT assets, security zones, network connections, services, and business processes. Automatic discovery rules detect new assets and connections as they appear in log data, with operator verification before documentation is updated — keeping the asset inventory accurate without manual effort.

The interactive logical network map visualizes security zones, devices, and permitted communication patterns. The automated cyber risk analysis engine uses CMDB, attack vectors, safeguard assessments, and asset context to produce dynamic risk scores for assets and business processes. Risk findings are a direct input to correlation and vulnerability prioritization, and can be used to drive incident priority and response escalation.