SIEM Tuning by Live Fire (STLF™)

Most organizations use a Security Information and Event Management (SIEM) solution they trust to monitor their infrastructure for signs of hackers, malware, and insider threats. The SIEM may be managed internally, outsourced to an MSSP (Managed Security Solutions Provider), or a combination of both. Early warning of a security incident is critical and allows incident response teams to quickly contain the threat and investigate the root cause of the breach.

Our comprehensive STLF™ helps organizations locate and close the gaps in their security defenses. Without proper tuning and validation, organizations cannot determine whether their solution is effectively detecting, alerting, and analyzing activity.

STLF is not a penetration test as there is no exploitation component, it is a platform that uses simulations to mimic real-world attacks. The simulated attacks are updated frequently to keep pace with emerging threats.

A final comprehensive report allows you to increase detection capabilities, reduce noise in event logging, lower security management costs, and increase overall visibility.

Components of Tuning

  • ML models dynamically learn from historical data, discerning patterns, and anomalies enabling STLF to adapt to evolving threats, resulting in more accurate and timely threat detection.

  • By profiling typical behavior and deviations from the baselines, STLF can better identify anomalous activities, reducing false positives and enhancing detection precision.

  • Contextual enrichment through the integration of external threat intelligence feeds and data enrichment sources helps STLF contextualize events and alerts.

  • When a security incident is detected, STLF can trigger predefined response actions such as isolating a compromised system, blocking malicious traffic, or initiating an investigation.

  • By assessing deviations from established behavioral norms, STLF can detect insider threats, compromised accounts, and unauthorized access attempts.

  • Scalability, flexibility, and seamless integration with cloud environments enable organizations to monitor and secure their digital assets across on-premises and cloud infrastructures.

  • The integration of NLP techniques into STLF allows for improved log analysis and querying enabling faster data retrieval and more intuitive exploration of security incidents.

  • Adaptive algorithms refine detection rules over time, considering feedback from security analysts and the evolving threat landscape.

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