AprielGuard: A Guardrail for Safety and Adversarial Robustness in Modern LLM Systems

Large Language Models (LLMs) have rapidly evolved from text-only assistants into complex agentic systems capable of performing multi-step reasoning, calling external tools, retrieving memory, and executing code. With this evolution comes an increasingly sophisticated threat landscape: not only traditional content safety risks, but also multi-turn jailbreaks, prompt injections, memory hijacking, and tool manipulation.

In this work, we introduce AprielGuard, an 8B parameter safety–security safeguard model designed to detect:

• 16 categories of safety risks, spanning toxicity, hate, sexual content, misinformation, self-harm, illegal activities, and more.
• Wide range of adversarial attacks, including prompt injection, jailbreaks, chain-of-thought corruption, context hijacking, memory poisoning, and multi-agent exploit sequences.
• Safety violations and adversarial attacks in agentic workflows, including tool calls and model reasoning traces.

AprielGuard is available in both reasoning and non-reasoning modes, enabling explainable classification when needed and low-latency classification for production pipelines.

• Model: https://huggingface.co/ServiceNow-AI/AprielGuard
• Technical Paper: https://arxiv.org/abs/2512.20293

Table of Contents

1. Motivation
2. AprielGuard Overview
3. Taxonomy
4. Training Dataset
5. Model Architecture
6. Training Setup
7. Evaluation
8. Conclusion
9. Limitations

Motivation

Traditional safety classifiers primarily focus on a limited classification spectrum (e.g., toxicity or self-harm), assume short inputs, and evaluate single user messages. Modern deployments, however, feature:

• Multi-turn conversations
• Long contexts
• Structured reasoning steps producing chains of thought
• Tool-assisted multi-step workflows (agents)
• A growing class of adversarial attacks exploiting reasoning, tools, or memory

AprielGuard addresses these issues with a unified model and a unified safety + adversarial taxonomy, built specifically for modern LLM agent ecosystems.

AprielGuard Overview

It outputs:

AprielGuard overview