New TokenBreak Attack Bypasses AI Moderation with Single-Character Text Changes

Cybersecurity researchers have uncovered TokenBreak, an attack that exploits tokenization strategies to bypass content moderation in large language models with minimal changes to input text. This technique can lead to prompt injection and security vulnerabilities, especially against models using BPE or WordPiece tokenization. #TokenBreak #LLMsafety

Keypoints

TokenBreak manipulates text to evade content detection without altering readability.
The attack exploits differences in tokenization strategies like BPE and WordPiece.
Using Unigram tokenization can mitigate the effectiveness of TokenBreak.
The technique increases the risk of prompt injection and malicious attacks on LLMs.
Defense strategies include model selection, training with bypass examples, and logging misclassifications.

Tags: EMAIL, EXPLOIT, PAYLOAD, SPAM, TOOL