Generative AI Endpoints
Generative AI Endpoints, in the context of cybersecurity, are the publicly exposed network interfaces (typically REST APIs or similar web service access points) that allow users, applications, or external systems to submit data (prompts) to a deployed Generative AI model and receive its output (generated text, code, images, etc.).
These endpoints are the critical gateways to the organization’s most powerful and potentially most vulnerable AI assets. Their security is paramount because they directly mediate all external interaction with the model.
Key characteristics and cybersecurity considerations of these endpoints include:
Direct Attack Vector: Endpoints are the primary targets for logical attacks, particularly Prompt Injection. An attacker sends a carefully crafted input via the endpoint to manipulate the model's instructions, forcing it to ignore its original directives, leak sensitive data it was trained on, or perform unauthorized actions.
Authentication and Authorization: The endpoint must enforce robust authentication to ensure only authorized users or services can access the model. Failure to do so exposes the model to an unauthenticated denial-of-service attack or unauthorized access, resulting in the theft of intellectual property (model usage).
Rate Limiting and Abuse: Endpoints must be protected against misuse, such as high-volume scraping or rapid-fire queries that could extract proprietary training data or lead to exorbitant usage costs.
Data Flow and Logging: The endpoint serves as the point of ingress for all user input and the point of egress for all generated content. Comprehensive endpoint logging is essential for auditing, detecting malicious input patterns, and ensuring that no sensitive information is leaked in the model’s responses.
In summary, a Generative AI Endpoint is the external network boundary of the model and represents the high-stakes intersection of network security and model security.
ThreatNG, an all-in-one external attack surface management, digital risk protection, and security ratings solution, provides essential external vigilance to secure Generative AI Endpoints by focusing on the public-facing exposures that an unauthenticated attacker would target. Since endpoints are the primary gateway for attacks like Prompt Injection, ThreatNG ensures that external security controls around endpoints remain intact.
External Discovery and Inventory
ThreatNG’s capability to perform purely external unauthenticated discovery using no connectors is the foundation for locating all exposed GenAI endpoints.
Subdomain Intelligence: ThreatNG discovers all associated subdomains and identifies the cloud and web platforms hosting them. This directly locates the public-facing API endpoints or applications that interact with the GenAI models. The module performs HTTP Responses analysis and Header Analysis, which reveals how the endpoint is communicating.
Technology Stack Identification: ThreatNG provides exhaustive, unauthenticated discovery of technologies, including the 265 technologies categorized as Artificial Intelligence, as well as vendors in AI Model & Platform Providers and AI Development & MLOps. This confirms the existence of a GenAI endpoint.
Example of ThreatNG Helping: ThreatNG discovers an unmanaged subdomain, copilot-staging.company.com, which the Technology Stack module identifies as running an AI Model & Platform Provider service. This pinpoints an exposed GenAI endpoint that was previously untracked, likely a Shadow AI asset.
External Assessment for Endpoint Risk
ThreatNG's external assessment modules highlight the critical configuration flaws that make a GenAI endpoint vulnerable to unauthenticated exploitation or misuse.
Non-Human Identity (NHI) Exposure: This critical governance metric quantifies vulnerability to threats from high-privilege machine identities, such as leaked API keys and service accounts. Since endpoints are often protected by these non-human credentials, their exposure is a direct endpoint compromise risk.
Web Application Hijack Susceptibility: This rating assesses the presence or absence of key security headers on subdomains, such as Content-Security-Policy and X-Frame-Options. A weak rating here indicates the GenAI endpoint's web interface is susceptible to classic web attacks (like Cross-Site Scripting via improper output handling) that could be triggered by a malicious prompt.
Cyber Risk Exposure (Sensitive Code): This rating is based on findings that include Sensitive Code Discovery and Exposure (code secret exposure). Finding a configuration file that exposes the endpoint’s access key via this module immediately compromises the endpoint's security.
Example of ThreatNG Helping: ThreatNG flags a poor Web Application Hijack Susceptibility rating for a public-facing chatbot endpoint. This signals that if an attacker were to succeed with a prompt injection attack, the lack of security headers could enable the malicious output to execute a classic XSS attack on the user's browser.
Reporting and Continuous Monitoring
ThreatNG provides Continuous Monitoring of the external attack surface, ensuring that any changes to the GenAI endpoint's security posture are flagged immediately.
External Adversary View and MITRE ATT&CK Mapping: ThreatNG aligns the security posture with external threats by performing unauthenticated, outside-in assessment. It automatically translates raw findings—like leaked credentials associated with the endpoint—to specific MITRE ATT&CK techniques (e.g., initial access), showing how the endpoint could be exploited.
Reporting (Prioritized): ThreatNG provides prioritized reports that help organizations allocate resources effectively by focusing on the most critical risks. A finding of an exposed API combined with a lack of security headers on the hosting subdomain would be highly prioritized.
Investigation Modules
ThreatNG's Investigation Modules allow security teams to gather granular, unauthenticated evidence regarding the endpoint's exposure.
Sensitive Code Exposure: This module discovers public code repositories and explicitly looks for Access Credentials (various API Keys and Access Tokens) and Configuration Files. Finding a leaked LLM access key here is a primary method of endpoint compromise.
Subdomain Intelligence (Content Identification and Ports): This module identifies content such as Admin Pages and APIs on subdomains and checks for exposed ports. Finding a public API or an exposed database port near the GenAI endpoint provides crucial context about the attack vector.
Online Sharing Exposure: This module identifies the presence of organizational entities on code-sharing platforms such as Pastebin and GitHub Gist. An attacker often finds LLM API keys or configuration snippets in these forums, which grant direct access to the endpoint.
Example of ThreatNG Helping: An analyst uses the Sensitive Code Exposure module and finds an exposed configuration snippet on a development forum that references the specific path of a production GenAI API endpoint. This provides an attacker with the exact target for a Prompt Injection attack, which the security team can preemptively address.
Complementary Solutions
ThreatNG's external discovery provides essential, unauthenticated intelligence to complementary solutions like API Security Gateways and AI Security Platforms (focused on prompt analysis).
Complementary Solutions (API Security Gateways): ThreatNG's discovery of a newly exposed GenAI API endpoint via Subdomain Intelligence is immediately routed to the API Security Gateway. The asset's external visibility forces the gateway to implement security policies, such as rate limiting and enhanced input validation, on that specific external endpoint to prevent token abuse orscale attacks.
Complementary Solutions (AI Security Platforms): ThreatNG’s detection of a leaked service account credential via NHI Exposure that grants access to the endpoint is passed to the AI Security Platform. The external proof of credential compromise enables the platform to prioritize its internal work, such as running specific red-teaming scenarios against the model using that compromised key to test for potential data leakage or unauthorized actions.
