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high advisory

Security Bypass Vulnerability in LiteLLM

A vulnerability in LiteLLM, tracked as CVE-2024-4786, allows remote authenticated attackers to circumvent established security controls.

LiteLLM +7
3t 1c updated
medium advisory

Detection of Local LLM Model File Creation on Endpoints

This 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.

Ollama +9 shadow-it llm data-exfiltration policy-violation endpoint shadow-ai local-llm intellectual-property-theft +2
2r 5t
high advisory

LangSmith SDK Untrusted Manifest Deserialization Vulnerability

The LangSmith SDK is vulnerable to untrusted manifest deserialization when pulling public prompts via `pull_prompt`, potentially leading to SSRF, prompt injection, or sensitive data exposure; CVE-2026-45134.

langsmith +2 deserialization ssrf prompt-injection
2r 3t