CVE-2024-6587 Scanner

LiteLLM is a lightweight language model framework designed for integration with various AI tools and platforms. It is widely used by developers and AI researchers to interact with large language models like OpenAI's GPT-4. LiteLLM allows for easy deployment and interaction with AI models, particularly in environments where resources are limited. Its open-source nature and flexibility make it a popular choice for custom AI solution development. The software is typically employed in AI-driven applications, chatbots, and automation tools.

The SSRF vulnerability in LiteLLM allows an attacker to manipulate requests sent by the server. This can lead to unauthorized access to internal systems or expose sensitive information such as API keys. The flaw lies in the way the software handles URL inputs, allowing malicious actors to craft requests that the server then executes. The exploitation of this vulnerability can lead to severe security breaches, including unauthorized data access.

The vulnerability exists in the api_base parameter within the LiteLLM's HTTP request handling. When processing requests, LiteLLM fails to properly validate and sanitize this parameter, allowing attackers to inject arbitrary URLs. This can result in the server performing unintended actions, such as interacting with internal services or external servers. The vulnerability is particularly dangerous because it can be used to expose sensitive data, including OpenAI API keys, when an attacker controls the URL endpoint. The flaw is triggered when an attacker sends a specially crafted request that the server mistakenly trusts.

If exploited, the SSRF vulnerability can allow attackers to gain unauthorized access to internal network resources or services. This could lead to data exfiltration, system compromise, or even full control over certain server functions. Additionally, sensitive data such as API keys may be exposed, potentially leading to further exploitation, unauthorized API access, or misuse of AI capabilities.

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References:

• https://huntr.com/bounties/4001e1a2-7b7a-4776-a3ae-e6692ec3d997
• https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2024-6587