Data Mining, Darknet, and Social Network Monitoring are critical components of modern threat intelligence and security operations. The AIL Project is an open source framework designed to collect, crawl, dig, and analyze unstructured data from various sources. With its extensible Python-based framework, AIL can analyze unstructured data collected via an advanced Crawler manager or from different feeders such as PasteBin-alike sites, Twitter, Discord, Telegram Stream providers, or custom feeders.

AIL supports active crawling of Tor hidden services, protected websites and forums with pre-recorded session cookies. Its modular design allows for easy contribution and extension, enabling the addition of new Analyzer modules, feeders, or streams without the need to know the inner workings. The framework also has integrations with other open source projects such as MISP or cve-search.

This presentation will focus on the latest version of the AIL framework (v5.0) and its new features. Attendees will learn about the following:
- An overview of the modular design of AIL and its extensibility through Analyzer modules, feeders, and exporters.
- Demonstrations of how the new features can be used in practice, including practical examples of investigating Tor hidden services and other sources of data.
- Best practices for data collection and analysis with AIL, including performance optimization techniques and integration with other open source projects such as MISP.

Join us for this exciting presentation and learn how AIL can help you with your data analysis and threat detection needs.

https://github.com/ail-project/

https://github.com/ail-project/ail-framework