CVE-2024-29090 in AI Engine Plugin
Summary
by MITRE • 03/28/2024
Server-Side Request Forgery (SSRF) vulnerability in Jordy Meow AI Engine: ChatGPT Chatbot.This issue affects AI Engine: ChatGPT Chatbot: from n/a through 2.1.4.
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Analysis
by VulDB Data Team • 03/28/2024
The CVE-2024-29090 vulnerability represents a critical server-side request forgery flaw within the Jordy Meow AI Engine: ChatGPT Chatbot platform, specifically impacting versions ranging from n/a through 2.1.4. This vulnerability falls under the broader category of CWE-918, which defines server-side request forgery as a security weakness where an attacker can manipulate a server into making unintended requests to internal or external systems. The flaw enables malicious actors to exploit the chatbot's request handling mechanisms, potentially allowing unauthorized access to internal network resources that should remain protected from external exposure.
The technical implementation of this SSRF vulnerability stems from inadequate input validation and sanitization within the AI engine's request processing pipeline. When the chatbot system receives user input or API requests, it fails to properly validate or filter the URLs or endpoints specified in these requests, allowing attackers to inject malicious URLs that can cause the server to make unintended requests to internal systems. This weakness particularly affects the platform's ability to distinguish between legitimate external requests and potentially harmful internal network probes or attacks, creating a pathway for attackers to bypass normal network security controls.
The operational impact of this vulnerability extends beyond simple data exposure, as it can enable attackers to perform reconnaissance activities against internal network infrastructure, access sensitive internal services, or even escalate privileges within the affected environment. The vulnerability's scope allows for potential exploitation of internal systems that are typically protected by firewalls or network segmentation, effectively creating a backdoor that bypasses traditional perimeter security measures. This risk is particularly severe in environments where the chatbot system has access to internal resources or where internal services are not properly isolated from external-facing components.
Security practitioners should implement comprehensive mitigations including strict input validation, URL filtering, and network segmentation to prevent unauthorized access to internal systems. The vulnerability aligns with ATT&CK technique T1071.004, which covers application layer protocol: DNS, and can be addressed through proper network access controls, web application firewalls, and input sanitization measures. Organizations should also consider implementing outbound traffic filtering to prevent the chatbot from making unauthorized requests to internal resources, while ensuring that all system components are updated to versions that have addressed this specific SSRF vulnerability through proper code review and security testing processes.