A Comparative Evaluation of AI Agent Security Guardrails
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913066753458176 |
|---|---|
| author | Li, Qi Li, Jiu Wei, Pingtao Xu, Jianjun Wei, Xueyi Shi, Jiwei Zhang, Xuan Yang, Yanhui Hui, Xiaodong Xu, Peng Zhou, Lingquan |
| author_facet | Li, Qi Li, Jiu Wei, Pingtao Xu, Jianjun Wei, Xueyi Shi, Jiwei Zhang, Xuan Yang, Yanhui Hui, Xiaodong Xu, Peng Zhou, Lingquan |
| contents | This report presents a comparative evaluation of DKnownAI Guard in AI agent security scenarios, benchmarked against three competing products: AWS Bedrock Guardrails, Azure Content Safety, and Lakera Guard. Using human annotation as the ground truth, we assess each guardrail's ability to detect two categories of risks: threats to the agent itself (e.g., instruction override, indirect injection, tool abuse) and requests intended to elicit harmful content (e.g., hate speech, pornography, violence). Evaluation results demonstrate that DKnownAI Guard achieves the highest recall rate at 96.5\% and ranks first in true negative rate (TNR) at 90.4\%, delivering the best overall performance among all evaluated guardrails. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_24826 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Comparative Evaluation of AI Agent Security Guardrails Li, Qi Li, Jiu Wei, Pingtao Xu, Jianjun Wei, Xueyi Shi, Jiwei Zhang, Xuan Yang, Yanhui Hui, Xiaodong Xu, Peng Zhou, Lingquan Cryptography and Security Artificial Intelligence This report presents a comparative evaluation of DKnownAI Guard in AI agent security scenarios, benchmarked against three competing products: AWS Bedrock Guardrails, Azure Content Safety, and Lakera Guard. Using human annotation as the ground truth, we assess each guardrail's ability to detect two categories of risks: threats to the agent itself (e.g., instruction override, indirect injection, tool abuse) and requests intended to elicit harmful content (e.g., hate speech, pornography, violence). Evaluation results demonstrate that DKnownAI Guard achieves the highest recall rate at 96.5\% and ranks first in true negative rate (TNR) at 90.4\%, delivering the best overall performance among all evaluated guardrails. |
| title | A Comparative Evaluation of AI Agent Security Guardrails |
| topic | Cryptography and Security Artificial Intelligence |
| url | https://arxiv.org/abs/2604.24826 |