intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same

artifacts belonging to other users. This can lead to unauthorized cross-user writes, model supply chain poisoning, and arbitrary code execution when compromised models are loaded. The issue

Python code when loaded, bypassing Picklescan's safety checks and enabling supply-chain poisoning of shared model files

Picklescan is vulnerable to RCE through missing detection when calling

Picklescan is vulnerable to RCE via missing detection when calling

llama-index-core insecurely handles temporary files

Open WebUI's process_files_batch() endpoint missing ownership check

Open WebUI Vulnerable to Unauthenticated RAG Configuration Disclosure

Open WebUI Vulnerable to IDOR: Retrieval API Bypasses Knowledge Base

Open WebUI: Redis Cache Keys tool_servers and terminal_servers

mcp-memory-service: Missing Authentication on Document API Endpoints Allows

vLLM is an inference and serving engine for large language

ViewComponent: Reused Component Instances Retain Stale Render Context

PraisonAI MCP `tools/call` path-traversal => RCE via Python `.pth` injection