HiveTraceGuard-Pro: A Compact Generative Guardrail for Prompt Injection, Jailbreaks, and Adversarial Obfuscation

arXiv:2609.01046 · cs.CR, cs.AI · Submitted 2026-09-01 · Read on arXiv

cs.CR, cs.AI

Submitted: 2026-09-01

Updated: 2026-09-01

Terminology

• Benchmark — 45× in this paper · explained in 2 episodes
• Robustness — 45× in this paper · explained in 5 episodes
• Provenance — 6× in this paper · explained in 4 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Transformer — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Decode — 3× in this paper · explained in 2 episodes
• AUROC — 2× in this paper · explained in 2 episodes
• Allocator — 2× in this paper · explained in 1 episode
• Filler Tokens — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adversarial Examples — 1× in this paper · explained in 2 episodes
• Data Provenance — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Qwen3Guard Technical Report
• YuFeng-XGuard: A Reasoning-Centric, Interpretable, and Flexible Guardrail Model for Large Language Models
• SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning
• Shieldstral
• OpenGuardrails: A Configurable, Unified, and Scalable Guardrails Platform for Large Language Models
• The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm
• RTP-LX: Can LLMs Evaluate Toxicity in Multilingual Scenarios?
• All Languages Matter: On the Multilingual Safety of Large Language Models
• Aegis2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM Guardrails
• Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
• ShieldGemma: Generative AI Content Moderation Based on Gemma
• WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs
• PolyGuard: A Multilingual Safety Moderation Tool for 17 Languages
• ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation
• A Holistic Approach to Undesired Content Detection in the Real World
• HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
• BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset
• SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models
• S-Eval: Towards Automated and Comprehensive Safety Evaluation for Large Language Models
• OR-Bench: An Over-Refusal Benchmark for Large Language Models

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