Speculative Safety Honeypot: Toward Proactive Defense Against Multi-turn Agent Attacks

arXiv:2609.39549 · cs.CR, cs.AI, cs.CL · Submitted 2026-09-30 · Read on arXiv

cs.CR, cs.AI, cs.CL

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Speculative Safety Honeypot — 22× in this paper
• Benchmark — 14× in this paper · explained in 2 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Verification — 8× in this paper · explained in 2 episodes
• Fidelity — 7× in this paper · explained in 2 episodes
• Indirect Prompt Injection — 6× in this paper
• Speculative Decoding — 6× in this paper · explained in 2 episodes
• Clustering — 5× in this paper · explained in 2 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Core — 3× in this paper · explained in 2 episodes
• Multi-Agent System — 3× in this paper · explained in 5 episodes
• Pruning — 3× in this paper · explained in 4 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Attack Success Rate — 2× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 2× in this paper · explained in 3 episodes
• Supervised Fine-Tuning — 2× in this paper
• AI Agents — 1× in this paper · explained in 2 episodes
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Adversarial scenarios — 1× in this paper · explained in 1 episode
• Agent Interactions — 1× in this paper · explained in 1 episode
• Agentic Coding — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Agentic Workflows — 1× in this paper · explained in 1 episode
• Alternation — 1× in this paper · explained in 1 episode
• As Large Language Model — 1× in this paper
• Attack Success Rate (ASR) — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• KV cache — 1× in this paper · explained in 3 episodes
• Multi-agent system (MAS) — 1× in this paper · explained in 2 episodes
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Systematic Bias — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Dynamic Speculative Agent Planning
• Defending Against Indirect Prompt Injection Attacks With Spotlighting
• STAC: When Innocent Tools Form Dangerous Chains for LLM Agents
• Prompt Injection Attacks on Agentic Coding Assistants: A Systematic Analysis of Vulnerabilities in Skills, Tools, and Protocol Ecosystems
• SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning
• LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts
• PromptArmor: Simple yet Effective Prompt Injection Defenses
• MultiLoRA: Democratizing LoRA for Better Multi-Task Learning
• TOUCAN: Synthesizing 1.5M Tool-Agentic Data from Real-World MCP Environments
• Qwen3 Technical Report
• Defense Against Indirect Prompt Injection via Tool Result Parsing

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