CVE-2025-6242

A Server-Side Request Forgery (SSRF) vulnerability exists in the MediaConnector class within the vLLM project's multimodal feature set. The load_from_url and load_from_url_async methods fetch and process media from user-provided URLs without adequate restrictions on the target hosts. This allows an attacker to coerce the vLLM server into making arbitrary requests to internal network resources.

This vulnerability is particularly critical in containerized environments like llm-d, where a compromised vLLM pod could be used to scan the internal network, interact with other pods, and potentially cause denial of service or access sensitive data. For example, an attacker could make the vLLM pod send malicious requests to an internal llm-d management endpoint, leading to system instability by falsely reporting metrics like the KV cache state.

Vulnerability Details

The core of the vulnerability lies in the MediaConnector.load_from_url method and its asynchronous counterpart. These methods accept a URL string to fetch media content (images, audio, video).

https://github.com/vllm-project/vllm/blob/119f683949dfed10df769fe63b2676d7f1eb644e/vllm/multimodal/utils.py#L97-L113

The function directly processes URLs with http, https, and file schemes. An attacker can supply a URL pointing to an internal IP address or a localhost endpoint. The vLLM server will then initiate a connection to this internal resource.

• HTTP/HTTPS Scheme: An attacker can craft a request like {"image_url": "http://127.0.0.1:8080/internal_api"}. The vLLM server will send a GET request to this internal endpoint.
• File Scheme: The _load_file_url method attempts to restrict file access to a subdirectory defined by --allowed-local-media-path. While this is a good security measure for local file access, it does not prevent network-based SSRF attacks.

Impact in llm-d Environments

The risk is significantly amplified in orchestrated environments such as llm-d, where multiple pods communicate over an internal network.

1. Denial of Service (DoS): An attacker could target internal management endpoints of other services within the llm-d cluster. For instance, if a monitoring or metrics service is exposed internally, an attacker could send malformed requests to it. A specific example is an attacker causing the vLLM pod to call an internal API that reports a false KV cache utilization, potentially triggering incorrect scaling decisions or even a system shutdown.

2. Internal Network Reconnaissance: Attackers can use the vulnerability to scan the internal network for open ports and services by providing URLs like http://10.0.0.X:PORT and observing the server's response time or error messages.

3. Interaction with Internal Services: Any unsecured internal service becomes a potential target. This could include databases, internal APIs, or other model pods that might not have robust authentication, as they are not expected to be directly exposed.

Delegating this security responsibility to an upper-level orchestrator like llm-d is problematic. The orchestrator cannot easily distinguish between legitimate requests initiated by the vLLM engine for its own purposes and malicious requests originating from user input, thus complicating traffic filtering rules and increasing management overhead.

Untrusted input controls a URL used for redirection, which can forward users to attacker-controlled sites. Typical impact: phishing and credential harvesting via a trusted domain.

CVE-2025-6242 has a CVSS score of 7.1 (High). The vector is network-reachable, low privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (0.11.0); upgrading removes the vulnerable code path.

Kodem intelligence

See the --allowed-media-domains option discussed here: https://docs.vllm.ai/en/latest/usage/security.html#4-restrict-domains-access-for-media-urls

1. What is CVE-2025-6242? CVE-2025-6242 is a high-severity open redirect vulnerability in vllm (pip), affecting versions >= 0.5.0, < 0.11.0. It is fixed in 0.11.0. Untrusted input controls a URL used for redirection, which can forward users to attacker-controlled sites.
2. How severe is CVE-2025-6242? CVE-2025-6242 has a CVSS score of 7.1 (High). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
3. Which versions of vllm are affected by CVE-2025-6242? vllm (pip) versions >= 0.5.0, < 0.11.0 is affected.
4. Is there a fix for CVE-2025-6242? Yes. CVE-2025-6242 is fixed in 0.11.0. Upgrade to this version or later.
5. Is CVE-2025-6242 exploitable, and should I be worried? Whether CVE-2025-6242 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
6. What actually determines whether CVE-2025-6242 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
7. How do I fix CVE-2025-6242? Upgrade vllm to 0.11.0 or later.