Social Media and OSINT Investigative Techniques
Description
This two-day training is designed for Law Enforcement Officers, Police Crime Analysts, and Prosecutors who need the skills to effectively conduct internet-based investigations. Participants will learn how to identify and track offenders through both court-ordered data requests and open-source intelligence (OSINT) techniques, gaining practical knowledge to enhance investigations in today’s digital environment.
The course covers major social media platforms including Facebook, Instagram, TikTok, Snapchat, Twitter, and Reddit, with instruction on how to identify and preserve accounts, obtain records, and analyze data. Students will also learn advanced Google search techniques, methods for creating undercover online identities, and approaches for navigating the Dark Web. A forensic mapping tool will be introduced to analyze Snapchat geolocation data, giving investigators hands-on experience with location-based intelligence.
Additional topics include working with ride-share companies, smart speakers, and major tech providers (Microsoft, Yahoo, Amazon, etc.) to obtain valuable case information. Students will also be introduced to more than 250 free investigative websites and tools for gathering actionable intelligence.
Learning Objectives:
By the end of this course, participants will be able to:
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Identify and preserve social media accounts for investigative purposes.
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Obtain and interpret data from social media companies through court orders or OSINT.
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Analyze and map device location data from platforms such as Snapchat.
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Create and maintain anonymous online profiles for undercover investigations.
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Understand Internet Protocol (IP) addresses and their use in suspect identification.
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Conduct advanced Google searches to uncover hidden information.
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Apply over 250 free websites and online resources to support investigations.
Course Requirements:
Participants must bring a laptop or Windows tablet (no iPads) with internet capability, a mouse, and Google Earth Pro for Desktop installed prior to the class.