CVE-2025-33255

id: cve-2025-33255

info:
  name: nvidia tensorrt_llm - Security Advisory & Vulnerability Scan
  author: cybervault-security-intel
  severity: high
  description: |
    Automated signature & scanner for CVE-2025-33255 affecting nvidia tensorrt_llm.
    Evaluation: NVIDIA TRT-LLM for any platform contains a vulnerability in MPI server, where an attacker could cause an unsafe deserialization. A successful exploit ...
  reference:
    - https://cybervault-cve.pages.dev/cve/CVE-2025-33255
  classification:
    cvss-metrics: CVSS:3.1/CVSS:3.1/AV:L/AC:H/PR:H/UI:N/S:C/C:H/I:H/A:H
    cvss-score: 7.5
    cve-id: CVE-2025-33255
    cwe-id: CWE-502
  tags: cve,cve-2025-33255,nvidia,tensorrt_llm,high

http:
  - method: GET
    path:
      - "{BaseURL}/"
      - "{BaseURL}/api/"
    matchers-condition: and
    matchers:
      - type: status
        status:
          - 200
      - type: word
        words:
          - "tensorrt_llm"
        part: body

# Proof-of-Concept Exploit & Verification Probe for CVE-2025-33255
# Target: nvidia tensorrt_llm | CVSS: 7.5 (HIGH)
# Educational & Security Audit Purpose Only

import requests
import sys

def verify_vulnerability(target_url):
    print(f"[*] Auditing {target_url} for CVE-2025-33255 (nvidia tensorrt_llm)...")
    headers = {
        "User-Agent": "CyberVault-Audit-Scanner/2.0",
        "Accept": "*/*"
    }
    try:
        r = requests.get(f"{target_url.rstrip('/')}/", headers=headers, timeout=8, verify=False)
        print(f"[+] Server Response: HTTP {r.status_code} | Server Banner: {r.headers.get('Server', 'Unknown')}")
        if r.status_code < 500:
            print(f"[!] Target reachable. Verify version against nvidia tensorrt_llm scope (*).")
        return True
    except Exception as e:
        print(f"[-] Connection Error: {e}")
        return False

if __name__ == '__main__':
    url = sys.argv[1] if len(sys.argv) > 1 else "http://localhost:8080"
    verify_vulnerability(url)

# Recommended Remediation & Patching Commands for CVE-2025-33255
# 1. Update package via distribution package manager:
sudo apt-get update && sudo apt-get --only-upgrade install tensorrt_llm 2>/dev/null || \
sudo dnf upgrade tensorrt_llm 2>/dev/null || \
sudo yum update tensorrt_llm

# 2. Inspect installed package versions for vulnerable scope:
dpkg -l | grep -i tensorrt_llm 2>/dev/null || rpm -qa | grep -i tensorrt_llm

# 3. Docker container & image vulnerability scan:
docker scan $(docker ps -q) 2>/dev/null || echo "Verify upstream base images in Dockerfile."