CVE-2026-103243 in LightLLM
Summary
by MITRE • 09/30/2026
LightLLM through 1.2.0 fails to validate image_url and audio_url parameters in multimodal endpoints, allowing unauthenticated attackers to perform server-side request forgery. Attackers can supply arbitrary URLs to fetch internal resources, with vision model processing disclosing content or error responses revealing internal network topology.
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Analysis
by VulDB Data Team • 09/30/2026
LightLLM versions through 1.2.0 contain a critical input validation deficiency within its multimodal API endpoints that facilitates server-side request forgery attacks against unauthenticated adversaries. The vulnerability stems from the application's failure to rigorously validate or sanitize the image_url and audio_url parameters provided by clients during requests to these specific interfaces. Instead of restricting inputs to expected, safe domains or enforcing strict allow-listing protocols, the framework accepts arbitrary Uniform Resource Locators supplied directly by the user. This lack of validation allows an attacker to inject URLs pointing to internal network resources that are otherwise inaccessible from the public internet, effectively turning LightLLM into a proxy for malicious requests directed at backend infrastructure services such as database servers, administrative panels, or cloud metadata endpoints.
The operational impact of this vulnerability is severe due to its potential to compromise both data confidentiality and network integrity. By leveraging server-side request forgery, an attacker can force the vulnerable service to fetch sensitive internal resources on behalf of the malicious actor. In scenarios involving vision models, the processing of these injected URLs may result in the disclosure of image content hosted within the private network, exposing proprietary or personal information. Furthermore, even if the primary resource does not return visible data, error responses generated during the fetching process can reveal critical details about the internal network topology. These errors often include stack traces, server headers, or specific failure messages that disclose the existence and nature of backend services, thereby aiding attackers in mapping the environment for subsequent exploitation phases such as targeted attacks against identified weak points.
From a classification perspective, this vulnerability aligns with CWE-918 Server-Side Request Forgery (SSRF), which describes flaws where a web application fetches a remote resource without validating the user-supplied URL. Additionally, the attack vector relates to ATT&CK technique T1571 Non-Standard Port or Protocol if internal services operate on non-standard ports, and potentially T1046 Network Service Discovery if error responses are used to enumerate active hosts and services within the private network segment. The absence of authentication requirements for this endpoint exacerbates the risk, as any external entity with access to the LightLLM interface can exploit this flaw without needing valid credentials or prior compromise of user accounts.
Mitigation strategies must prioritize immediate input validation and strict URL allow-listing mechanisms. Developers should implement a robust whitelist that restricts accepted URLs in image_url and audio_url parameters to only those domains explicitly required for legitimate multimodal processing functions, rejecting all other inputs with appropriate error codes rather than attempting complex sanitization which can often be bypassed through encoding tricks or redirect chains. If possible, deploying the service within an isolated network segment using egress filtering rules that block outbound connections to private IP ranges and cloud metadata endpoints provides a critical layer of defense in depth. Upgrading to LightLLM version 1.2.1 or later is essential as it addresses these validation gaps by enforcing stricter parameter checks. Until patching occurs, organizations should consider placing the service behind a reverse proxy that inspects outgoing requests for suspicious patterns or restricts network access to only necessary external endpoints.