AI Infra Guard is an AI infrastructure security protection and monitoring tool that covers triple security protection at the request layer (input filtering), model layer (output compliance/jailbreak detection), and data layer (privacy leakage prevention).

AIInfraGuard

Core parameters and statistics

Project	Specifications
Product Name	AI Infra Guard
Category	AI Infrastructure Security
Delivery form	Web/SaaS
Support Platform	Web
Supported languages	Chinese, English
Target users	AI operation and maintenance team, security team, AI platform managers
User scale	Undisclosed
Pricing Model	Freemium (Free + Subscription)

AI Infra Guard is a tool focused on AI infrastructure security protection and operational monitoring. As more and more enterprises deploy AI models into production environments, the security threats faced by model interfaces are becoming increasingly diverse - new attack methods such as prompt injection, adversarial attacks, data leakage and abuse have brought challenges to traditional WAFs and API gateways. AI Infra Guard is designed to address these AI-specific security risks, building a security protection system from three dimensions: request layer, model layer and data layer.

User and market recognition

Gradually build user awareness in the field, and product capabilities are used by content creators and teams to improve work efficiency. Some industry users have incorporated it into their daily workflow. It is recommended to refer to the latest official disclosures for specific user scale and industry adoption rate data.

Cost advantage

Cost Dimension	Description
Free version	Basic security monitoring, including prompt injection detection and basic current limiting, free
Professional Edition	Advanced anomaly detection + custom rules + multi-model management
Enterprise Edition	Private deployment + customized security rules + exclusive threat intelligence

For enterprises that are in the security exploration stage of AI models, the basic security monitoring of the free version is enough to cover daily protection needs. The decision-making point for paid upgrades is whether privatized deployment (data-sensitive industries), custom security rules, and proprietary threat intelligence are required. Compared with deploying self-developed security solutions, the SaaS approach has more advantages in terms of initial investment and operation and maintenance costs.

Main functions

• AI-specific security detection: Design a detection rule library for AI-specific attack patterns such as prompt injection, jailbreak, adversarial attacks, etc., and regularly update the attack pattern library.
• Multi-level security protection: request layer (input filtering, current limiting) → model layer (output compliance, jailbreak detection) → data layer (privacy leakage protection), three layers are advanced step by step.
• Machine learning-based anomaly detection: Establish a baseline by learning normal request patterns and identify abnormal behaviors that deviate from the baseline.
• Access Control: Multi-dimensional policy management, supporting IP whitelist, API Key authentication, and user-level permission control.
• Health Monitoring: Monitor the running status, request latency and error rate of the model service in real time.
• Fine-grained audit log: records detailed information of all requests, supports multi-dimensional retrieval and audit report export.

Model and version evolution

Version	Date	Key Changes
v1.0 public beta version	2026-07	Three-layer protection architecture + anomaly detection + access control + health monitoring
v0.9 early version	—	Basic security detection, identifying known attack patterns

Early versions focused on basic security detection, while the current version extends to access control, anomaly detection and health monitoring. Subsequent iteration directions include automated security response, threat intelligence sharing, and native integration with mainstream model deployment platforms.

Technical advantages

• AI-specific security detection: designed for AI-specific attack modes such as prompt injection, jailbreak, adversarial attacks, etc., rather than general SQL injection or XSS detection.
• Three-layer protection architecture: request layer → model layer → data layer progressively, and other layers can still provide protection when a single layer fails.
• Machine Learning Anomaly Detection Engine: Establishes a baseline by learning normal request patterns, and identifies new attack patterns and unseen abnormal traffic patterns.
• Fine-grained audit log: records request source, time, content summary and disposal actions, and supports audit report export.

How to use

Entrance	How to use
Web side	Browser access → Registration → Access AI service interface → Configure security policy → Monitoring dashboard

Typical process: Register and create a workspace → Connect to the AI service interface (providing model API endpoints) → Load basic security policies by default → Customize rule configuration → Alarm notification settings (email/Webhook/SMS) → View the security posture dashboard.

Product Pricing

Package	Price	Contents
Free version	$0	Basic security monitoring, prompt injection detection, basic current limiting
Professional Edition	Unpublished	Advanced anomaly detection + custom rules + multi-model management
Enterprise Edition	Unpublished	Private deployment + exclusive threat intelligence + SLA guarantee

Pricing.

Application scenarios

• AI service online security assessment: A comprehensive security check will be conducted before the model interface is launched, including prompt injection testing, access control verification and baseline health checks.
• Production environment runtime protection: Continuously monitor the security situation of model interfaces, and detect and block attacks in real time. Contains three levels of protection: automatic alarm, current limiting and blocking.
• Compliance Auditing and Reporting: Regularly export security incident reports for internal audits and external compliance inspections.
• Multi-model unified security management: Manage the security policies of multiple model services on the same console to achieve unified security baselines and compliance standards.

Applicable people

• Security Operations Team: Manage protection strategies and event responses for multiple model services through a unified security console.
• AI Platform Manager: A platform team that provides unified AI services to internal business units. AI Infra Guard provides security layer encapsulation.
• Compliance Department: Internal or external audit team that requires AI service security audit evidence and compliance reports.
• Not suitable for boundaries: AI Infra Guard focuses on the security protection of AI model interfaces and does not replace traditional network firewalls or WAFs. Enterprise AI infrastructure still needs to be used in conjunction with regular cybersecurity measures.

Comparison of competing products

Comparison Dimensions	AI Infra Guard	Traditional WAF	API Gateway
Core differences	AI-specific security detection	General web security	Traffic management
Price	Freemium	By traffic/instance	By call volume
Coverage scenarios	prompt injection + counterattack + data leakage	SQL injection + XSS	routing + current limiting
User reviews	Unpublished	Mature	Mature
Technical threshold	Low (SaaS)	Medium	Medium

Summary and Outlook

AI Infra Guard focuses on the dedicated security needs of AI infrastructure and provides a three-layer security solution from detection to protection. The core value lies in filling the gaps of traditional security tools in AI scenarios - general WAF cannot detect prompt injection, and API gateway cannot identify adversarial attacks.

Current limitations: There is room for improvement in automatic response capabilities (automatic adjustment of protection strategies after an attack is detected) and real-time threat intelligence updates.

Procurement/Adoption Risk Assessment: It is recommended that enterprises with AI production environments first complete a basic security assessment through the free version to understand the real risk level faced by the model interface, and then decide whether to require functional expansion of the paid plan based on the assessment results.

Related tools: crewai, langchain

Version Info

• Public beta version ：The public beta version adds a three-layer protection architecture, anomaly detection, access control and health monitoring. （2026-07-14）
• earlier version ：Basic security detection to identify known attack patterns. （2026-07-14）