CVE-2026-47117: Improper Control of Generation of Code ('Code Injection') in maziyarpanahi openmed
OpenMed before 1.5.2 contains a remote code execution vulnerability in the PII privacy-filter model loading path. The privacy-filter dispatcher used broad substring matching on the user-supplied model_name parameter, allowing a value such as attacker/foo-privacy-filter-bar to route through a path that loads Hugging Face models with trust_remote_code=True. An unauthenticated attacker can supply a malicious model repository containing custom Transformers code via auto_map in config.json or tokenizer_config.json, which is imported and executed with the privileges of the OpenMed service process.
AI Analysis
Technical Summary
CVE-2026-47117 is a critical remote code execution vulnerability in OpenMed before version 1.5.2. The issue is due to improper control of code generation in the privacy-filter dispatcher, which uses broad substring matching on the model_name parameter. This allows an attacker to route requests to load Hugging Face models with trust_remote_code=True, enabling execution of attacker-supplied code embedded in model configuration files (auto_map in config.json or tokenizer_config.json). The vulnerability can be exploited remotely without authentication, resulting in execution of arbitrary code with the OpenMed service's privileges.
Potential Impact
An unauthenticated remote attacker can execute arbitrary code on the OpenMed server by supplying a specially crafted model_name parameter that causes loading of malicious Hugging Face models. This leads to full compromise of the OpenMed service process, potentially allowing data theft, service disruption, or further network penetration. The CVSS 4.0 base score is 9.3, indicating a critical severity with network attack vector, no required privileges or user interaction, and high impact on confidentiality, integrity, and availability.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Since the vulnerability affects OpenMed versions prior to 1.5.2, upgrading to version 1.5.2 or later is recommended once an official fix is released. Until then, restrict access to the model loading functionality and avoid using untrusted model_name inputs to mitigate risk.
CVE-2026-47117: Improper Control of Generation of Code ('Code Injection') in maziyarpanahi openmed
Description
OpenMed before 1.5.2 contains a remote code execution vulnerability in the PII privacy-filter model loading path. The privacy-filter dispatcher used broad substring matching on the user-supplied model_name parameter, allowing a value such as attacker/foo-privacy-filter-bar to route through a path that loads Hugging Face models with trust_remote_code=True. An unauthenticated attacker can supply a malicious model repository containing custom Transformers code via auto_map in config.json or tokenizer_config.json, which is imported and executed with the privileges of the OpenMed service process.
CVSS v4.0
Score 9.3critical
Affected software
pkg:github/maziyarpanahi/openmedRun on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-47117 is a critical remote code execution vulnerability in OpenMed before version 1.5.2. The issue is due to improper control of code generation in the privacy-filter dispatcher, which uses broad substring matching on the model_name parameter. This allows an attacker to route requests to load Hugging Face models with trust_remote_code=True, enabling execution of attacker-supplied code embedded in model configuration files (auto_map in config.json or tokenizer_config.json). The vulnerability can be exploited remotely without authentication, resulting in execution of arbitrary code with the OpenMed service's privileges.
Potential Impact
An unauthenticated remote attacker can execute arbitrary code on the OpenMed server by supplying a specially crafted model_name parameter that causes loading of malicious Hugging Face models. This leads to full compromise of the OpenMed service process, potentially allowing data theft, service disruption, or further network penetration. The CVSS 4.0 base score is 9.3, indicating a critical severity with network attack vector, no required privileges or user interaction, and high impact on confidentiality, integrity, and availability.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Since the vulnerability affects OpenMed versions prior to 1.5.2, upgrading to version 1.5.2 or later is recommended once an official fix is released. Until then, restrict access to the model loading functionality and avoid using untrusted model_name inputs to mitigate risk.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- VulnCheck
- Date Reserved
- 2026-05-18T19:22:26.749Z
- Cvss Version
- 4.0
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a1efb6ae29bf47b50db3b50
Added to database: 06/02/2026, 15:48:58 UTC
Last enriched: 07/15/2026, 10:04:19 UTC
Last updated: 07/31/2026, 19:22:59 UTC
Views: 95
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