
Sonia Badene enhanced the OpenCTI-Platform by developing advanced natural language query filtering in the backend, focusing on more accurate data extraction from user queries. She refactored the Zod output schema and improved prompt engineering, leveraging few-shot learning techniques in TypeScript and Node to support robust NLQ processing. In the OpenCTI-Platform/connectors repository, Sonia added entity and relation extraction to ImportDocumentAI, enabling richer document imports and more accurate threat intelligence graphs. Her work included refactoring Python-based processing pipelines, improving development environment setup with Docker, and strengthening STIX object creation and validation, demonstrating depth in backend development and data modeling.

OpenCTI-Platform/connectors – August 2025 monthly summary. Delivered a major data-enrichment capability by adding entity and relation extraction to ImportDocumentAI for document imports. This feature refactors processing to support simultaneous extraction of entities and relationships, enabling richer data import and more accurate threat intel graphs. Development environment improvements were implemented to streamline local setup and testing, and robustness was enhanced for STIX object creation and relationship validation across imports.
OpenCTI-Platform/connectors – August 2025 monthly summary. Delivered a major data-enrichment capability by adding entity and relation extraction to ImportDocumentAI for document imports. This feature refactors processing to support simultaneous extraction of entities and relationships, enabling richer data import and more accurate threat intel graphs. Development environment improvements were implemented to streamline local setup and testing, and robustness was enhanced for STIX object creation and relationship validation across imports.
Concise monthly summary for OpenCTI Platform (March 2025). Focus was on enhancing natural language query (NLQ) filtering in the backend to improve data extraction accuracy from natural language inputs and to lay groundwork for broader NLQ capabilities.
Concise monthly summary for OpenCTI Platform (March 2025). Focus was on enhancing natural language query (NLQ) filtering in the backend to improve data extraction accuracy from natural language inputs and to lay groundwork for broader NLQ capabilities.
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