[2604.06285] Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization

Computer Science > Cryptography and Security arXiv:2604.06285 (cs) [Submitted on 7 Apr 2026] Title:Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization Authors:Igor Maljkovic, Maria Rosaria Briglia, Iacopo Masi, Antonio Emanuele Cinà, Fabio Roli View a PDF of the paper titled Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization, by Igor Maljkovic and 4 other authors View PDF HTML (experimental) Abstract:Vision-Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual and visual information in a shared embedding space. Yet, this flexibility also makes them vulnerable to malicious prompts designed to produce unsafe content, raising critical safety concerns. Existing defenses either rely on blacklist filters, which are easily circumvented, or on heavy classifier-based systems, both of which are costly and fragile under embedding-level attacks. We address these challenges with two complementary components: Hyperbolic Prompt Espial (HyPE) and Hyperbolic Prompt Sanitization (HyPS). HyPE is a lightweight anomaly detector that leverages the structured geometry of hyperbolic space to model benign prompts and detect harmful ones as outliers. HyPS builds on this detection by applying explainable attribution methods to identify and selectively modify harmful words, neutralizing unsafe intent while preserving the original semantics of user prompts. Through extensive exper...