Pin It on Anyone: Certified Targeted Displacement of Multi-Bit LLM Watermarks Without the Key
On the map: LLM safety and security → Watermarking generated content and models
Abstract (arXiv)
Multi-bit watermarking embeds a message, typically an account identifier, into LLM output so that harmful text can be traced to its origin. We show an attack technique that allows to alter the watermarking message. This allows to, for example, exchange the embedded account ID to an arbitrary different one. The attacker mainly needs access to a few accounts for generating LLM output and model logits, but crucially not the secret key used to watermark. The attacker then rewrites the text, keeping its meaning, so that the watermarking message decoder recovers the watermarking message embedded by the attacker. We are, to our knowledge, the first to propose such an attack, which we call a targeted displacement. Theoretically, we present upper and lower bounds on the probability of our attack succeeding. This bound depends on the number of accounts the attacker has access to, the length of the message and some characteristics of the given text. Our attack can succeed whenever we can bound the ambiguity of the generated text well enough. Empirically, we test our attack technique against five watermarking methods and four LLMs. Attack success tracks our predicted bounds, allowing us to alter watermarking messages in almost all cases with high accuracy, given enough accounts. Our code can be found at https://github.com/Batorskq/PinIt.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Watermarking generated content and models, one of 12 directions in LLM safety and security. Builds on 63 of its 94 references that are in the map. First posted on arXiv 13 Oct 2026.
Builds on
63 of 94 references.
Closest ancestors · 38
Same direction, newest first
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- 2026QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs15 Apr
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- 2026AgentMark: Utility-Preserving Behavioral Watermarking for Agents5 Jan
- 2025WaterMod: Modular Token-Rank Partitioning for Probability-Balanced LLM Watermarking11 Nov
- 2025A Reinforcement Learning Framework for Robust and Secure LLM Watermarking23 Oct
- 2025Transferable Black-Box One-Shot Forging of Watermarks via Image Preference Models23 Oct
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- 2025LLM Watermark Evasion via Bias Inversion27 Sep
- 2025RLCracker: Evaluating the Worst-Case Vulnerability of LLM Watermarks with Adaptive RL Attacks25 Sep
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- 2025SAEMark: Steering Personalized Multilingual LLM Watermarks with Sparse Autoencoders11 Aug
- 2025Enhancing LLM Watermark Resilience Against Both Scrubbing and Spoofing Attacks8 Jul
- 2025MorphMark: Flexible Adaptive Watermarking for Large Language Models14 May
- 2025Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks8 May
- 2025Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?17 Feb
- 2024Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models4 Dec
- 2024Robust Multi-bit Text Watermark with LLM-based Paraphrasers4 Dec
- 2024Can Watermarked LLMs be Identified by Users via Crafted Prompts?4 Oct
- 2024Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach3 Oct
- 2024Discovering Spoofing Attempts on Language Model Watermarks3 Oct
- 2024Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature4 Jun
- 2024Black-Box Detection of Language Model Watermarks28 May
- 2024MarkLLM: An Open-Source Toolkit for LLM Watermarking16 May
- 2024An Entropy-based Text Watermarking Detection Method20 Mar
- 2024Bypassing LLM Watermarks with Color-Aware Substitutions19 Mar
- 2024WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off6 Mar
- 2024No Free Lunch in LLM Watermarking: Trade-offs in Watermarking Design Choices25 Feb
- 2024GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick20 Feb
- 2024Provably Robust Multi-bit Watermarking for AI-generated Text30 Jan
- 2023On the Learnability of Watermarks for Language Models7 Dec
- 2023Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks29 Sep
- 2023Towards Codable Watermarking for Injecting Multi-bits Information to LLMs29 Jul
- 2023Provable Robust Watermarking for AI-Generated Text30 Jun
- 2023Who Wrote this Code? Watermarking for Code Generation24 May
- 2023Robust Multi-bit Natural Language Watermarking through Invariant Features3 May
- 2023Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense23 Mar
Other references · 25
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- 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
- 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,944
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
- 2019The Curious Case of Neural Text Degenerationcited by 2,916
- 2023AWQ: Activation-aware Weight Quantization for LLM Compression and Accelerationcited by 1,298
- 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,254
- 2019Plug and Play Language Models: A Simple Approach to Controlled Text Generationcited by 799
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- 2017A Deep Reinforced Model for Abstractive Summarizationcited by 365
- 2022COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamicscited by 161
- 2020NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraintscited by 149
- 2019Neural Linguistic Steganographycited by 78
- 2023WatME: Towards Lossless Watermarking Through Lexical Redundancycited by 27
- 2024Revisiting the Robustness of Watermarking to Paraphrasing Attackscited by 25
- 2020Near-imperceptible Neural Linguistic Steganography via Self-Adjusting Arithmetic Codingcited by 17
- 2025Adversarial Paraphrasing: A Universal Attack for Humanizing AI-Generated Textcited by 17
- 2024Edit Distance Robust Watermarks via Indexing Pseudorandom Codescited by 13
- 2025Sandcastles in the Storm: Revisiting the (Im)possibility of Strong Watermarkingcited by 4
- 2025CLMTracing: Black-box User-level Watermarking for Code Language Model Tracingcited by 1
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- 2025Breaking Distortion-free Watermarks in Large Language Models