# Jailbreaking as a Reward Misspecification Problem

Source: [Jailbreaking as a Reward Misspecification Problem](<https://www.sota2.com/research/paper/68fa78221e209131cea76ec9>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T04:32:25.977Z

Authors: Zhihui Xie, Jiahui Gao, Lei Li, Zhenguo Li, Qi Liu, Lingpeng Kong

Published: 2024-06-20T15:12:27.000Z

## Abstract

The widespread adoption of large language models (LLMs) has raised concerns about their safety and reliability, particularly regarding their vulnerability to adversarial attacks. In this paper, we propose a novel perspective that attributes this vulnerability to reward misspecification during the alignment process. This misspecification occurs when the reward function fails to accurately capture the intended behavior, leading to misaligned model outputs. We introduce a metric ReGap to quantify the extent of reward misspecification and demonstrate its effectiveness and robustness in detecting harmful backdoor prompts. Building upon these insights, we present ReMiss, a system for automated red teaming that generates adversarial prompts in a reward-misspecified space. ReMiss achieves state-of-the-art attack success rates on the AdvBench benchmark against various target aligned LLMs while preserving the human readability of the generated prompts. Furthermore, these attacks on open-source models demonstrate high transferability to closed-source models like GPT-4o and out-of-distribution tasks from HarmBench. Detailed analysis highlights the unique advantages of the proposed reward misspecification objective compared to previous methods, offering new insights for improving LLM safety and robustness.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Jailbreak Attack on AdvBench (WASR, W-Toxicity Score)](<https://www.sota2.com/research/sota/jailbreak-attack-on-advbench-wasr-w-toxicity-score.md>): Jailbreak Attack; AdvBench; WASR: 92.3.

- [Jailbreaking on AdvBench (WASR & W-Toxicity Score)](<https://www.sota2.com/research/sota/jailbreaking-on-advbench-wasr-and-w-toxicity-score.md>): Jailbreaking; AdvBench; WASR: 50.2.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2406.14393>)

[PDF](<https://arxiv.org/pdf/2406.14393.pdf>)