HoneyTrap: A Deceptive Multi-Agent Shield for Safer AI Chats

Kari Jaaskelainen

08 Jan 2026 — 1 min read

Turning jailbreakers into the trapped

Jailbreak prompts can trick chatbots into breaking rules. HoneyTrap flips the script: a deceptive, multi-agent defense that engages attackers, wastes their time, and keeps helpful answers flowing for regular users.

Threat Interceptor: spots risky prompts early.
Misdirection Controller: steers attackers into harmless honeypots.
Forensic Tracker: logs and analyzes attack steps.
System Harmonizer: coordinates safe, consistent replies.

The authors also release MTJ-Pro, a tough multi-turn jailbreak benchmark blending seven advanced strategies, plus two metrics: Mislead Success Rate (how well defense confuses attackers) and Attack Resource Consumption (how much time and compute it drains).

Results across GPT-4, GPT-3.5-turbo, Gemini-1.5-pro, and LLaMA-3.1: attack success drops by 68.77% vs top baselines, while MSR and ARC jump 118.11% and 149.16%. Even against adaptive attackers, HoneyTrap prolongs interactions and raises costs—without hurting normal queries.

Paper: https://arxiv.org/abs/2601.04034v1

Paper: https://arxiv.org/abs/2601.04034v1

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