The year 2023 has witnessed a rapid surge in the popularity of Artificial Intelligence (AI) and Large Language Models (LLM). With the advent of AI-native applications, it becomes crucial to ensure their protection and security. This article aims to shed light on six best practices for safeguarding AI applications using API gateway.
1. Identity Authentication: Fortifying the Protection Layers
Identity authentication is the first line of defense when it comes to securing AI applications. Implementing robust authentication mechanisms such as OAuth, API keys, JWT (JSON Web Tokens), or other modern authentication methods adds an extra layer of protection. By verifying the identity of the users, API gateways can prevent unauthorized access and potential data breaches.
2. Canary Release: Controlled Release of Updates
When introducing a new API, it may be desirable for specific users in particular regions to experience it initially. Therefore, leveraging the canary release mechanism within the API gateway ensures that selected users can explore new features.
3. Rate Limiting: Controlling the API Traffic
Balancing swift responses for legitimate users while discerning and restricting malicious users is crucial. Commonly, IP or token-based limitations on access frequency and speed are enforced, mitigating the risk of robot attacks and enhancing the experience for real and reliable users.
4. IP Blacklist and Whitelist: Restricting Access
In AI application development, we prefer users from legal and compliant regions. Establishing an IP blacklist and whitelist allows only users on the whitelist to access the API. IPs within the blacklist are denied access, aiding in IP-based judgments.
5. Data Sovereignty: Protecting User Data
In the era of stringent data privacy regulations, data sovereignty plays a crucial role in maintaining AI application security. API gateways ensure compliance by securing user data and preventing any unauthorized exposure. With the ability to control data routing and storage, API gateways help businesses maintain sovereignty over their users' data, minimizing the risk of data breaches.
6. Request Body and Response Body Verification: Ensuring Data Integrity
Ensuring the validation of user requests and server responses is paramount. This validation can be achieved through OpenAPI or JSON Schema, guaranteeing that user requests adhere to the defined specifications, and that the server's response data complies with regulations, preventing data leakage and associated risks.
These six aspects might be one of many considerations when deploying applications online. Advanced measures like observability and complex log analysis may be necessary to uncover additional security risks.
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