Summary
langchain-nvidia-ai-endpoints has local file disclosure through VLM image inputs
langchain-nvidia-ai-endpoints versions before 1.4.2 accepted local filesystem paths as image inputs for Vision Language Model (VLM) requests. If an application passed attacker-controlled image input to ChatNVIDIA or VLM reranking APIs, an attacker could cause files readable by the application process to be read and included in the outbound request to the configured NVIDIA/NIM model endpoint.
Patched Version
Upgrade to langchain-nvidia-ai-endpoints >= 1.4.2.
The patched version rejects raw local filesystem paths for VLM image inputs. Supported inputs are remote URLs, data:image/...;base64,... URIs, and supported asset/file IDs.
Workarounds
If upgrading is not immediately possible, applications should reject local filesystem paths in user-controlled VLM image inputs and only allow trusted remote URLs, data URIs, or known safe asset/file IDs.
Applications should also run with least-privilege filesystem access so that the application process cannot read files it does not need.
Impact
Applications are affected if they use VLM image inputs with ChatNVIDIA or NVIDIARerank and allow untrusted users to control image URLs or document image metadata.
An attacker who can control those inputs may be able to read local files accessible to the application process. Applications that do not use VLM image inputs, or that only pass trusted image references, are not affected.
Input manipulates file paths to reach files outside the intended directory, such as configuration or credential files. Typical impact: unauthorized file read or write outside the intended directory.
GHSA-G28H-2CMM-RJ9X has a CVSS score of 7.5 (High). The vector is network-reachable, no 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 (1.4.2); upgrading removes the vulnerable code path.
Affected versions
Security releases
Kodem intelligence
Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.
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. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.
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Frequently Asked Questions
- What is GHSA-G28H-2CMM-RJ9X? GHSA-G28H-2CMM-RJ9X is a high-severity path traversal vulnerability in langchain-nvidia-ai-endpoints (pip), affecting versions <= 1.4.1. It is fixed in 1.4.2. Input manipulates file paths to reach files outside the intended directory, such as configuration or credential files.
- How severe is GHSA-G28H-2CMM-RJ9X? GHSA-G28H-2CMM-RJ9X has a CVSS score of 7.5 (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.
- Which versions of langchain-nvidia-ai-endpoints are affected by GHSA-G28H-2CMM-RJ9X? langchain-nvidia-ai-endpoints (pip) versions <= 1.4.1 is affected.
- Is there a fix for GHSA-G28H-2CMM-RJ9X? Yes. GHSA-G28H-2CMM-RJ9X is fixed in 1.4.2. Upgrade to this version or later.
- Is GHSA-G28H-2CMM-RJ9X exploitable, and should I be worried? Whether GHSA-G28H-2CMM-RJ9X 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
- What actually determines whether GHSA-G28H-2CMM-RJ9X 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.
- How do I fix GHSA-G28H-2CMM-RJ9X? Upgrade
langchain-nvidia-ai-endpointsto 1.4.2 or later.