Abstract: Systems, methods, and frameworks for detecting malicious WebAssembly (Wasm) modules under source code obfuscation are provided. The system is configured to accurately identify malicious behavior in Wasm modules irrespective of the specific malicious functionality and in the presence of source code obfuscation techniques. The detection process leverages a Vision Transformer (ViT) model to classify a Wasm module as benign or malicious, enabling robust identification of threats across diverse attack patterns. The system operates with substantially low runtime overhead on computing resources, making it suitable for integration into real-time web application environments.

Abstract: Systems and methods for detecting unrestricted file upload (UFU) vulnerabilities in Node.js (e.g., Node.js web applications) are provided. A lightweight framework can be used, drawing on a comprehensive evaluation of unique UFU-type attack types from multiple sources. By tailoring these attack instances to the Node.js ecosystem, systems and methods of embodiments of the subject invention offer more thorough coverage of potential attack vectors than existing technologies and tools.

Abstract: Systems and methods for continuous and transparent verification, authentication, and identification of individuals are provided. A method can include detecting a signal from a sensor embedded in a wearable device, determining a set of features unique to the wearer of the wearable device, creating a user profile of that individual, detecting a signal from a sensor of an unknown individual, determining a set of features unique to the unknown individual, and comparing the features of the unknown individual to the previously created user profile.