Product:
Azure Machine Learning
Summary
Improper neutralization of special elements in output used by a downstream component in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network. This vulnerability can lead to significant security risks if exploited. Attackers can manipulate the output to deceive users or systems.
Details
| Severity | Base Score | CVE |
|---|---|---|
| HIGH | 8.2 | CVE-2026-33833 |
Exploitation
To exploit this vulnerability, an attacker must have network access and can perform spoofing by injecting malicious content into the output of Azure Machine Learning. This requires user interaction, as the attacker needs to trick the user into executing the malicious output. Once successful, the attacker can impersonate legitimate users or systems.
Affected Products
- Azure Machine Learning: Vulnerable to injection attacks that can lead to spoofing.
Mitigation
To mitigate this vulnerability, it is recommended to apply the latest security updates provided by Microsoft. Additionally, users should implement strict input validation and output encoding practices to prevent injection attacks. Regular security assessments and monitoring can also help identify and address potential vulnerabilities.