OSINT in the Age of AI: Personal Privacy and Cyber Threat Intelligence

Open-source intelligence (OSINT) has become a critical capability in both personal privacy evaluation and modern cyber threat analysis. While most individuals are unaware of how much information they expose through public records, searchable web footprints, business registries, social platforms, metadata, and breached credentials, the same signals are often the foundation of an attacker's recon process. This talk explores how a person can systematically assess their own digital exposure: what is publicly visible, how it can be correlated, and what traces (e-mail and physical addresses, metadata, credentials, etc.) might be used to profile them. For the second perspective, we shift to how cybersecurity professionals leverage the exact same OSINT techniques in threat intelligence and pentesting workflows. Using real-world tooling like AI-powered web search, programmable search engines for text and images, reverse image search, e-mail discovery platforms, metadata extraction, regex-driven scraping, and breach intelligence, we demonstrate how attackers and red teams map the digital surface of an organization or individual. The goal is to highlight what can be inferred from minimal initial data and how these insights can support malicious processes such as spear-phishing, credential stuffing, impersonation, identity theft, and other stages of an adversary’s attack planning. By presenting OSINT through this dual lens, the session provides both actionable privacy guidance for individuals and practical recon understanding for defenders and testers. Attendees will leave with a clear understanding of their own digital footprint, insight into how attackers interpret and leverage that information, and practical guidance to reduce exposure and strengthen both personal and organizational security.