CVE-2026-122015 · AI agents & MCP
NO FIX YET · SEE WHAT TO DO
npcpy, an NPC-Worldwide Python library for LLM agents, has an input validation flaw in its MLX provider's get_mlx_response function, triggered through the model argument. The exploit is public, and the sources say an attacker can trigger it remotely, but they do not state what an attacker gets beyond that.
first public Nov 4, 2026 · 1 source
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Teams that use the npcpy library with the MLX provider and pass model names that come from user input or outside the application are exposed. Projects that use npcpy with other providers, or that hard-code the model name, are less likely to be reached. The sources do not say what exactly happens after the validation failure.
Not affected if default-config, hardcoded-model-name
Who cares llm-agents, mlx, npcpy, python
pip show npcpy; versions up to 2.1.27 are affected.get_mlx_response or the MLX provider in npcpy/gen/response.py that pass user-controlled values as model.A vulnerability was found in NPC-Worldwide npcpy up to 2.1.27. This vulnerability affects the function get_mlx_response of the file npcpy/gen/response.py of the component MLX Provider. The manipulation of the argument model results in improper input validation. The attack can be launched remotely. The exploit has been made public and could be used.
This page as .md · .json · CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
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