Reverse Image Search engines play a critical role in Open Source Intelligence (OSINT) and media forensics. They help uncover the origins of images, restoring original contexts and verifying authenticity. This capability is essential for distinguishing benign images from manipulated content. However, the robustness of these search engines is increasingly challenged by the application of post-processing operations and advancements in generative AI, which can produce highly realistic synthetic images. This paper analyzes the robustness of current reverse image search engines and highlights several shortcomings, emphasizing the need for enhanced resilience against AI-generated content to maintain their effectiveness in OSINT and media forensics.