Us Va Vt

To: itso@vt.edu Subject: Unauthenticated AI inference endpoint, Virginia Polytechnic Institute and State University (128.173.243.8)

Nicholas Michael Kloster / NuClide Research nicholas@nuclide-research.com

2026-05-01

Re: Unauthenticated Ollama AI inference endpoint, Virginia Polytechnic Institute and State University IP / Host: 128.173.243.8 Severity: CRITICAL

I’m an independent security researcher. I hold CISA disclosures CVE-2025-4364 and ICSA-25-140-11 and conduct good-faith AI infrastructure research under the NuClide Research umbrella. This is an unsolicited disclosure, no engagement exists with your organization, and I have not accessed, modified, or exfiltrated any data beyond what was necessary to confirm the exposure.

Summary

Virginia Tech has at least 4 Ollama-running IPs in Shodan; only h80adf308.dhcp.vt.edu (128.173.243.8) responds publicly. The DHCP hostname indicates a desktop or workstation on the campus DHCP pool rather than a dedicated server. 5 models, no cloud proxies.

Infrastructure

Additional VT IPs in Shodan (198.82.9.219, 198.82.11.101, 198.82.13.6) did not respond, likely firewalled or offline.

Model Inventory

Findings

F1: Researcher Workstation Publicly Exposed (LOW)

DHCP hostname pattern (h80adf308.dhcp.vt.edu) indicates a laptop or desktop on campus DHCP. No cloud proxies, no credential leak. Standard unauthenticated Ollama exposure on a workstation.

F2: CVE-2025-63389 Injectable (HIGH)

All models injectable via unauthenticated /api/create.

Why it matters

The credential leak (username + SSH public key) exposes your service account to enumeration and credential-stuffing against other services.

One-line fix

OLLAMA_HOST=127.0.0.1:11434
systemctl restart ollama

This rebinds Ollama to loopback only. If running in Docker: docker run -p 127.0.0.1:11434:11434 ollama/ollama.

CVE-2025-63389

All models on this instance are injectable via the unauthenticated /api/create endpoint, an attacker can overwrite any model’s system prompt or delete models entirely. No patch exists as of this disclosure.

Reference

Full technical details, parameter counts, and remediation notes are in this public research repository: AI-LLM-Infrastructure-OSINT/blob/main/case-studies/universities/US/VA-vt.md

This research is part of a broader sweep of university AI infrastructure exposures documented at: AI-LLM-Infrastructure-OSINT/blob/main/case-studies/universities/OVERVIEW.md

I’m happy to answer questions or assist with verification. No response is required.

Regards, Nicholas Michael Kloster / NuClide Research nicholas@nuclide-research.com AI-LLM-Infrastructure-OSINT