REVIEW 1 cited by
[WIP] Jailbreak Paradox: The Achilles' Heel of LLMs
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
We introduce two paradoxes concerning jailbreak of foundation models: First, it is impossible to construct a perfect jailbreak classifier, and second, a weaker model cannot consistently detect whether a stronger (in a pareto-dominant sense) model is jailbroken or not. We provide formal proofs for these paradoxes and a short case study on Llama and GPT4-o to demonstrate this. We discuss broader theoretical and practical repercussions of these results.
Forward citations
Cited by 1 Pith paper
-
A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection
RTST, a two-agent moderator with an explainable Behavior ledger and per-prompt weight updates, reduced attack success rate from 12-63% to 0-17% on three jailbreak benchmarks with Gemini 2.5 Flash.
Discussion (0). Sign in to comment.