Client
A major telecom operator serving 60M+ subscribers, operating large-scale mobile and broadband networks.
Client Background
The telecom sector is a high-value target for cybercriminals due to the scale of customer data, network infrastructure, and national-level communication systems. The client’s legacy SOC model struggled to handle the increasing volume of threats.
Client Challenge
The operator’s SOC operated on outdated monitoring tools with limited correlation capabilities. Analysts were overwhelmed by false positives, manual triage, and slow investigations.
Network elements, cloud workloads, subscriber platforms, and OSS/BSS systems generated massive telemetry, but the SOC lacked real-time analytics.
Threat detection lagged due to siloed tools, inconsistent playbooks, and lack of behavioral analysis for potential attacks. With emerging 5G expansion, security gaps posed significant operational and regulatory risks.
Xevyte Solution
Xevyte established a next-generation SOC integrating AI-driven detection and automated response.
VIGIL (SIEM) became the central analytics engine, aggregating logs and telemetry across network layers, subscriber data systems, and cloud infrastructure. Machine learning-based behavioral analytics identified anomalies early.
PRAETOR (EDR) protected endpoints across network engineering teams, while AUTON (SOAR) automated triage, enrichment, and incident escalation.
Xevyte implemented threat intelligence feeds, fraud detection models, and proactive threat hunting for telecom-specific attack patterns. Standardized runbooks and structured governance improved SOC maturity significantly.
Business Impact
Key Capabilities Delivered