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Key Facts
- Deploy IdoubleS to generate bespoke threat-, system-, and asset-centric Cyber Threat Models derived from sophisticated cyber threat intelligence and customer's asset data driven by AI. This automated and AI-driven Cyber Threat Modelling utilizes the generation of threat scenarios in a scalable and timely manner. It further saves your costs and resources.
- Implement IdoubleS to build attack graphs on a tactical level for deriving effective SIEM detection rules. This reduces noisy false-positive alerts and saves incident response follow-up endeavors. In addition, your expenses will be reduced and resources will be used more efficiently.
- By deploying IdoubleS, take advantage of automated hypotheses formulation and testing in context of a knowledge graph for a specific threat scenario. IdoubleS guides threat hunters in prioritizing the most important and likely pattern to search for and facilitates in immediately finding evidence of intrusion activity.
Categories
Intrusion detection / prevention Managed security services Open source (software and services) Big data Security Threat analysis Web application security Consulting IT security Security management Risk analysis and management SIEM Security information and event management Artificial intelligence Cyber-physical systems security Cloud (computing) security APT protection
Product information
The IdoubleS platform is an open system that refines sophisticated commercial or open-source cyber threat intelligence, presented in natural language, tailored to a customer's specific environment. This scalable, AI-empowered refinement is automated using natural language processing (NLP) and visualized as a cyber threat model in the form of an attack graph and attack tree.
Attack graph and attack tree provide a comprehensive understanding of how relevant threat actors would attack a company's critical functions. The IdoubleS platform automatically outputs attack graphs in structured STIX machine code, from which several use cases for operationalization in a SOC can be derived.
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