SecOps professionals face an ongoing challenge: manually analyzing massive amounts of security data to identify threats, investigate incidents, and make informed decisions. This manual analysis is time-consuming, prone to human error, and often leads to missed threats and delayed response times.
The Challenge of Manual Data Analysis in SecOps
Traditional security operations rely on manual processes that struggle to keep pace with the volume and complexity of modern security data. The risks include:
- Missing critical threat indicators buried in data
- Delayed incident response due to time-consuming investigations
- Human error in data analysis and correlation
- Analyst fatigue from repetitive, manual tasks
- Inability to identify subtle patterns across disparate data sources
Key Innovation: AI-Powered Natural Language Search
Cyclops now supports natural language search for security data, enabling SecOps professionals to quickly query and retrieve precise information using everyday language. This innovation uses Large Language Models (LLM) to understand context and nuanced queries, making security data more accessible than ever before.
Instead of learning complex query languages or navigating multiple dashboards, analysts can simply ask questions like:
- "Show me all critical vulnerabilities on internet-facing assets without EDR"
- "Which executives have access to sensitive data without MFA?"
- "Find unmanaged devices with high-severity vulnerabilities"
Cyclops' Three-Tiered AI Approach
1. Natural Language Understanding
Advanced LLMs interpret the intent behind queries, understanding context, relationships, and security concepts to deliver accurate results.
2. Automated Data Correlation
AI automatically correlates data across multiple security tools and data sources, connecting the dots between users, assets, vulnerabilities, and threats.
3. QueryIQ (Suggestive Queries)
The platform suggests relevant queries based on your environment and current security posture, helping analysts ask the right questions and discover issues they might not have considered.
Benefits of the New Search Capability
Accelerates Investigative Processes
What once took hours of manual investigation can now be accomplished in seconds, dramatically reducing mean time to detect (MTTD) and mean time to investigate (MTTI).
Provides Faster Access to Critical Insights
Analysts can quickly access the specific information they need without navigating complex interfaces or learning proprietary query languages.
More Intuitive Searching
Natural language search is accessible to all team members, regardless of their technical expertise, democratizing access to security insights across the organization.
Better Risk Prioritization
By making it easier to understand the context and relationships behind security events, the platform helps teams prioritize and address the risks that matter most to their business.
Conclusion
AI-powered natural language search represents a fundamental shift in how security teams interact with their data. By making security data more accessible, contextual, and actionable, Cyclops enables SecOps teams to work faster, smarter, and more effectively than ever before.