This pre-conference training introduces a structured OSINT approach to identifying and assessing synthetic (“deepfake”) media. 

It provides participants with practical methods to trace the origin, context, and credibility of suspicious visual content - skills that are essential for investigative verification and misinformation prevention. The approach is not solely focused on technical model analysis, but also demonstrates how open-source intelligence methods can detect, interpret, and respond to synthetic or manipulated media in real-world information environments. Participants will also gain an understanding of the legal and procedural implications of deepfakes in investigative and judicial contexts.

The training builds progressive competencies by enabling participants to:

• Understand how deepfakes emerge, spread, and influence online ecosystems.
• Apply structured source, metadata, and visual analysis to verify images and video content.
• Examine the online ecosystems and communities in which manipulated media is created, shared, and exploited, including their relevance to cybersecurity and corporate security investigations.
• Develop a systematic workflow for assessing authenticity and contextualizing emerging threats.

By combining investigative reasoning, structured OSINT techniques, and practical media analysis, the training supports practitioners in journalism, law enforcement, and digital forensics. The final modules include guided hands-on exercises, collaborative case analysis, and discussions on prevention, reporting, and practical response options to help participants make informed decisions when dealing with manipulated media.