Product
Detection of Local LLM Framework DNS Queries
1 rule 3 TTPs 18 IOCsThis brief details the detection of DNS queries originating from local Large Language Model (LLM) frameworks like Ollama, LM Studio, and GPT4All on Windows endpoints, leveraging Sysmon Event ID 22 to identify potential unauthorized AI tool usage or data exfiltration risks associated with model downloads, updates, and telemetry from repositories such as huggingface.co and ollama.ai.
Detection of Local LLM Model File Creation on Endpoints
2 rules 5 TTPsThis brief describes how the creation of Large Language Model (LLM) files, including formats like .gguf, .safetensors, .ggml, and Modelfiles, by local AI inference frameworks such as Ollama, llama.cpp, GPT4All, and LM Studio can be detected on Windows endpoints, indicating potential shadow AI deployments, unauthorized model downloads, or rogue LLM infrastructure which poses data exfiltration risks and policy violations.
Detection of Generative AI Processes Connecting to Unusual Domains
1 rule 1 TTPAdversaries may compromise macOS-based Generative AI (GenAI) tools through prompt injection, malicious Model Context Protocol (MCP) servers, or poisoned plugins to establish Command and Control (C2) channels or exfiltrate sensitive data by causing them to connect to unusual domains.
GenAI Process Connection to Unusual Domain on macOS
2 rules 1 TTPThis rule detects GenAI tools on macOS connecting to unusual domains, potentially indicating command and control activity, data exfiltration, or malicious payload retrieval following compromise via prompt injection, malicious MCP servers, or poisoned plugins.
GenAI Process Performing Encoding/Chunking Prior to Network Activity
2 rules 4 TTPsThis rule detects GenAI processes performing encoding or chunking (base64, gzip, tar, zip) followed by outbound network activity, indicating data preparation for exfiltration.