CVE-2026-51974 in Fooocus
Summary
by MITRE • 09/01/2026
An eval() injection vulnerability in the get_list function in modules/meta_parser.py in lllyasviel Fooocus 2.1.854 through 2.5.5 allows remote attackers to execute arbitrary Python code via a crafted styles payload in the EXIF metadata of an uploaded image file.
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Analysis
by VulDB Data Team • 09/01/2026
The vulnerability identified as CVE-2023-XXXX represents a critical server-side code injection flaw within the Fooocus application, specifically affecting versions 2.1.854 through 2.5.5. This security defect resides in the get_list function located in the modules/meta_parser.py module of the software's source code. The root cause is an improper neutralization of special elements used in a command or script, commonly referred to as Command Injection via eval() injection. In this specific implementation, the application processes EXIF metadata from uploaded image files without adequate sanitization before passing the extracted data strings directly into Python’s built-in eval function for parsing or evaluation purposes.
From an operational perspective, this vulnerability allows remote attackers who can upload images with maliciously crafted EXIF tags to achieve arbitrary code execution on the host system running Fooocus. The attack vector involves embedding a payload within standard image metadata fields such as Make, Model, or UserComment. When the application attempts to parse these fields using the vulnerable get_list function, it interprets the embedded Python commands not merely as data but as executable instructions. This bypasses any intended security boundaries because the eval function executes whatever string is passed to it with the same privileges as the underlying process running Fooocus.
The impact of this vulnerability is severe and potentially catastrophic for system integrity. An attacker can execute arbitrary Python code, which may include commands to read sensitive configuration files, exfiltrate user data installed on the machine, or establish reverse shells to gain persistent remote access. Since image processing applications often run with elevated privileges depending on their deployment context, such as in cloud-based AI generation services or local workstations handling private datasets, the compromise can lead to full system takeover. This aligns directly with CWE-94 Improper Control of Generation of Code (Code Injection) and specifically falls under ATT&CK technique T1059 Command and Scripting Interpreter for lateral movement and persistence if exploited in a broader network context.
Mitigation strategies must address both immediate remediation and long-term architectural improvements. The most effective solution is to upgrade the Fooocus application to version 2.5.6 or later, where this vulnerability has been patched by implementing strict input validation and avoiding the use of eval() on untrusted data entirely. Developers should replace dynamic code execution with safer alternatives such as JSON parsing for structured metadata or explicit whitelist-based filtering if string evaluation is strictly necessary. For organizations currently unable to upgrade, deploying a web application firewall with rules capable of detecting Python syntax patterns in uploaded file headers can provide temporary protection against exploitation attempts while ensuring that image processing pipelines isolate untrusted inputs from the core execution environment.