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Adversaries look through public information like research papers or company blogs to figure out what kind of AI a company is using. Think of it like a burglar reading a homeowner's public social media posts to learn what brand of security system they installed so they can find a way to bypass it.
Adversaries perform reconnaissance by analyzing publicly available technical documentation, such as research papers and engineering blogs, to map an organization's AI infrastructure. This intelligence allows them to identify specific AI assets and tailor their attack vectors, such as building more accurate proxy models for adversarial testing.
Adversaries conduct open-source intelligence (OSINT) gathering by querying academic repositories, pre-print servers, and technical publications to reconstruct the target organization's AI architecture. By identifying the specific model architectures and proprietary data integration methods disclosed by the organization's researchers, the adversary gains the necessary technical parameters to optimize evasion or extraction attacks, including the development of high-fidelity proxy models for local adversarial simulation.