ViPER: Vision-Based Packing-Aware Encoder for Robust Malware Detection

Visualization-based malware detection maps raw binary bytes to grayscale images and applies learned visual classifiers, providing an evasion-resistant and disassembly-free alternative to conventional analysis pipelines. However, executable packing remains a critical failure mode: packed binaries...

Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment

Recent advancements in visual context compression enable MLLMs to process ultra-long contexts efficiently by rendering text into images. However, we identify a critical vulnerability inherent to this paradigm: lowering image resolution inadvertently catalyzes jailbreaking. Our experiments reveal...

Beyond Crash: Hijacking Your Autonomous Vehicle for Fun and Profit

Autonomous Vehicles AVs, especially vision-based AVs, are rapidly being deployed without human operators. As AVs operate in safety-critical environments, understanding their robustness in an adversarial environment is an important research problem. Prior physical adversarial attacks on vision-bas...

Spotting brand impersonation with Swin transformers and Siamese neural networks

Every day, Microsoft Defender for Office 365 encounters millions of brand impersonation emails. Our security solutions use multiple detection and prevention techniques to help users avoid divulging sensitive information to phishers as attackers continue refining their impersonation tricks. In thi...