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CVE-2025-3777

3.5 · LOW

Hugging Face Transformers versions up to 4.49.0 are affected by an improper input validation vulnerability in the `image_utils.py` file.

Published Jul 7, 2025CWE-20EPSS 0.41%

Overview

CVE-2025-3777 is a low-severity vulnerability. It was published on July 7, 2025 and has a CVSS 3.0 base score of 3.5 (LOW).

This vulnerability has a CVSS 3.0 base score of 3.5, rated LOW. It can be exploited remotely over the network. Some level of privileges is required for exploitation.

Technical description

Hugging Face Transformers versions up to 4.49.0 are affected by an improper input validation vulnerability in the `image_utils.py` file. The vulnerability arises from insecure URL validation using the `startswith()` method, which can be bypassed through URL username injection. This allows attackers to craft URLs that appear to be from YouTube but resolve to malicious domains, potentially leading to phishing attacks, malware distribution, or data exfiltration. The issue is fixed in version 4.52.1.

Remediation

Check the references section for vendor advisories, patches, and mitigation guidance. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

Frequently asked questions

What is CVE-2025-3777?

CVE-2025-3777 is a low-severity vulnerability. It was published on July 7, 2025 and has a CVSS 3.0 base score of 3.5 (LOW).

How severe is CVE-2025-3777?

This vulnerability has a CVSS 3.0 base score of 3.5, rated LOW. It can be exploited remotely over the network. Some level of privileges is required for exploitation.

How do I fix or remediate CVE-2025-3777?

Check the references section for vendor advisories, patches, and mitigation guidance. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

How can CyberStrike help with CVE-2025-3777?

CyberStrike is an open-source, AI-augmented pentesting engine. Rather than flag a version number, it tests whether an issue like CVE-2025-3777 is actually reachable in your own applications and APIs, then verifies each finding before reporting it. That tells you if the weakness is a real, exploitable risk in your environment or a false positive you can safely deprioritize.

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