Dropzone uses AI to autonomously investigate security alerts by pulling relevant data from various security sources such as SIEM, EDR, Firewall, and Cloud Service Provider APIs. It employs LLMs, security pre-training, log analysis, and organizational context to draw correlations and reach conclusions without human input or prior playbooks.
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Integration With Security Tools
Dropzone integrates with existing cybersecurity tools and data sources, including SIEM, EDR, Firewall, Cloud Service Providers, Identity and Access Management (IAM), Identity Providers (IDP), and SaaS applications. It automatically gathers data from these sources for investigations.
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Llm-Native Cybersecurity Reasoning System
The system uses advanced LLMs as its core, with specialized cybersecurity pre-training. It can process thousands of alerts daily, providing expert-level conclusions and detailed analysis.
04
Automated Report Generation
For each alert, Dropzone generates a full report with a severity conclusion for prioritization, an executive summary, and key insights in plain English. The reports include a complete chain of raw evidence and sources.
05
Organizational Context Learning
Dropzone automatically extracts and learns organizational context from systems, past tickets, and SOC documentation. It categorizes and stores this information in a semantic database, tracking the source of each piece of knowledge.
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