Suspicious Local LLM Frameworks

• LLM Model File Creation :
  endpoint Endpoint None version:3
  Detects the creation of Large Language Model (LLM) files on Windows endpoints by monitoring file creation events for specific model file formats and extensions commonly used by local AI frameworks. This detection identifies potential shadow AI deployments, unauthorized model downloads, and rogue LLM infrastructure by detecting file creation patterns associated with quantized models (.gguf, .ggml), safetensors model format files, and Ollama Modelfiles. These file types are characteristic of local inference frameworks such as Ollama, llama.cpp, GPT4All, LM Studio, and similar tools that enable running LLMs locally without cloud dependencies. Organizations can use this detection to identify potential data exfiltration risks, policy violations related to unapproved AI usage, and security blind spots created by decentralized AI deployments that bypass enterprise governance and monitoring.


• Windows Local LLM Framework Execution :
  endpoint Endpoint None version:3
  The following analytic detects execution of unauthorized local LLM frameworks (Ollama, LM Studio, GPT4All, Jan, llama.cpp, KoboldCPP, Oobabooga, NutStudio) and Python-based AI/ML libraries (HuggingFace Transformers, LangChain) on Windows endpoints by leveraging process creation events. It identifies cases where known LLM framework executables are launched or command-line arguments reference AI/ML libraries. This activity is significant as it may indicate shadow AI deployments, unauthorized model inference operations, or potential data exfiltration through local AI systems. If confirmed malicious, this could lead to unauthorized access to sensitive data, intellectual property theft, or circumvention of organizational AI governance policies.


• Local LLM Framework DNS Query :
  endpoint Endpoint None version:3
  Detects DNS queries related to local LLM models on endpoints by monitoring Sysmon DNS query events (Event ID 22) for known LLM model domains and services. Local LLM frameworks like Ollama, LM Studio, and GPT4All make DNS calls to repositories such as huggingface.co and ollama.ai for model downloads, updates, and telemetry. These queries can reveal unauthorized AI tool usage or data exfiltration risks on corporate networks.