Now You Hear Me: Audio Narrative Attacks Against Large Audio-Language Models
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Abstract (arXiv)
Large audio-language models increasingly operate on raw speech inputs, enabling more seamless integration across domains such as voice assistants, education, and clinical triage. This transition, however, introduces a distinct class of vulnerabilities that remain largely uncharacterized. We examine the security implications of this modality shift by designing a text-to-audio jailbreak that embeds disallowed directives within a narrative-style audio stream. The attack leverages an advanced instruction-following text-to-speech (TTS) model to exploit structural and acoustic properties, thereby circumventing safety mechanisms primarily calibrated for text. When delivered through synthetic speech, the narrative format elicits restricted outputs from state-of-the-art models, including Gemini 2.0 Flash, achieving a 98.26% success rate that substantially exceeds text-only baselines. These results highlight the need for safety frameworks that jointly reason over linguistic and paralinguistic representations, particularly as speech-based interfaces become more prevalent.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 34 of its 56 references that are in the map. First posted on arXiv 30 Jan 2026.
Builds on
34 of 56 references.
References · 34
- 2023Universal and Transferable Adversarial Attacks on Aligned Language Modelscited by 2,914
- 2023Jailbreaking Black Box Large Language Models in Twenty Queriescited by 1,326
- 2023Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!cited by 1,106
- 2024How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMscited by 533
- 2023GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Promptscited by 520
- 2022Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studiescited by 506
- 2023Catastrophic Jailbreak of Open-source LLMs via Exploiting Generationcited by 439
- 2023DeepInception: Hypnotize Large Language Model to Be Jailbreakercited by 337
- 2023Pengi: An Audio Language Model for Audio Taskscited by 217
- 2024AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehensioncited by 215
- 2024Mini-Omni: Language Models Can Hear, Talk While Thinking in Streamingcited by 204
- 2025VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interactioncited by 191
22 more
- 2024GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning Abilitiescited by 151
- 2024WavChat: A Survey of Spoken Dialogue Modelscited by 88
- 2024Fast Adversarial Attacks on Language Models In One GPU Minutecited by 85
- 2024Defending Large Language Models Against Jailbreak Attacks via Layer-specific Editingcited by 77
- 2024Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMscited by 47
- 2024Advancing Large Language Models to Capture Varied Speaking Styles and Respond Properly in Spoken Conversationscited by 45
- 2024Voice Jailbreak Attacks Against GPT-4ocited by 39
- 2024Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attackscited by 35
- 2023Paralinguistics-Enhanced Large Language Modeling of Spoken Dialoguecited by 25
- 2025Multilingual and Multi-Accent Jailbreaking of Audio LLMscited by 25
- 2023EmphAssess : a Prosodic Benchmark on Assessing Emphasis Transfer in Speech-to-Speech Modelscited by 21
- 2024Cognitive Biases in Large Language Models: A Survey and Mitigation Experimentscited by 20
- 2024Frozen Large Language Models Can Perceive Paralinguistic Aspects of Speechcited by 18
- 2024Comparing Discrete and Continuous Space LLMs for Speech Recognitioncited by 15
- 2025Exploring Jailbreak Attacks on LLMs through Intent Concealment and Diversioncited by 9
- 2025`From Prompt to Perturbation': An Adaptive Framework for Voice-Based Jailbreaks on Audio LLMscited by 6
- 2024Beyond Text: Utilizing Vocal Cues to Improve Decision Making in LLMs for Robot Navigation Taskscited by 5
- 2025Audio Jailbreak Attacks: Exposing Vulnerabilities in SpeechGPT in a White-Box Frameworkcited by 4
- 2025CantoASR: Prosody-Aware ASR-LALM Collaboration for Low-Resource Cantonesecited by 3
- 2025GuardVal: Dynamic Large Language Model Jailbreak Evaluation for Comprehensive Safety Testingcited by 2
- 2025CMDAR: A Chinese Multi-scene Dynamic Audio Reasoning Benchmark with Diverse Challengescited by 1
- 2025Optimizing Speech Language Models for Acoustic Consistencycited by 1
Built on by
Citing papers per year: 2026: 5.
5 papers.
- 2026The Interspeech 2026 Audio Reasoning Challenge: Evaluating Reasoning Process Quality for Audio Reasoning Models and Agentscited by 6
- 2026A Systematic Study of Cross-Modal Typographic Attacks on Audio-Visual Reasoningcited by 0
- 2026Audio Jailbreaks in Large Audio-Language Models: Taxonomy, Attack-Defense Analysis, and Cost-Aware Evaluationcited by 0
- 2026Not the Same Protector: Deployment-Dependent Protective Intervention in LLMscited by 0
- 2026Causal Localization of the Refusal Direction in Audio Language Modelscited by 0
- 2026Causal Localization of the Refusal Direction in Audio Language Models6 Sep 2026
- 2026Not the Same Protector: Deployment-Dependent Protective Intervention in LLMs29 Aug 2026
- 2026Audio Jailbreaks in Large Audio-Language Models: Taxonomy, Attack-Defense Analysis, and Cost-Aware Evaluation28 May 2026
- 2026A Systematic Study of Cross-Modal Typographic Attacks on Audio-Visual Reasoning5 Apr 2026
- 2026The Interspeech 2026 Audio Reasoning Challenge: Evaluating Reasoning Process Quality for Audio Reasoning Models and Agents15 Feb 2026