Shypd.aiThe largest open index of AI toolsEyeballer is an open-source convolutional neural network for analyzing pentest screenshots. It helps identify potentially vulnerable web-based hosts from large sets of screenshots, streamlining target identification.
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Eyeballer is a convolutional neural network designed by Bishop Fox for analyzing penetration testing screenshots. It helps security professionals identify "interesting" targets from a vast collection of web-based hosts, particularly useful in large-scope network penetration tests. Users can employ their favorite screenshotting tools like EyeWitness or GoWitness, then process the outputs through Eyeballer to categorize them. The tool labels screenshots into categories such as "Old-Looking Sites" (indicating potential vulnerabilities), "Login Pages" (suggesting further functionality and credential enumeration opportunities), "Webapp" (signifying a larger attack surface), "Custom 404's" (to filter out uninteresting pages), and "Parked Domains" (to remove invalid attack surfaces from scope). Eyeballer provides results in both human-readable HTML and machine-readable CSV formats, offering performance metrics like Overall Binary Accuracy and All-or-Nothing Accuracy.
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