CVE-2025-3777
3.5 · LOWOverview
CVE-2025-3777 is a low-severity vulnerability affecting huggingface transformers. 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 and patches from huggingface. Update transformers to the latest patched version. 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.
Affected Products
| Vendor | Product | Versions | Status |
|---|---|---|---|
| huggingface | transformers | >= 0, < 4.52.1 | Affected |
Frequently Asked Questions
What is CVE-2025-3777?
CVE-2025-3777 is a low-severity vulnerability affecting huggingface transformers. 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 and patches from huggingface. Update transformers to the latest patched version. 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's AI-powered security agents can automatically detect CVE-2025-3777 across your infrastructure using autonomous pentesting, DAST scanning, and HackBrowser. The platform continuously monitors for known vulnerabilities and provides actionable remediation guidance prioritized by real-world exploitability.
How CyberStrike Helps
AI agents map your attack surface to find vulnerabilities like this one.
Automated penetration testing that runs continuously, not just quarterly.
AI-driven PR review catches vulnerable dependencies before they ship.
Browser-based exploitation validates findings with real proof-of-concept.
Related LOW CVEs from 2025
View all →Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') vulnerabi
A vulnerability has been found in Union Bank of India Vyom 8.0.34 on Android and classified as probl
Symlink following in the installer for Zoom Workplace App for macOS before 6.2.10 may allow an authe
In DA, there is a possible out of bounds read due to a missing bounds check. This could lead to loca
HCL Connections Docs is vulnerable to a sensitive information disclosure which could allow a user to
The MongoDB Shell may be susceptible to control character injection where an attacker with control o
Android apps can load web pages using the Custom Tabs feature. This feature supports a transition an
Information Exposure vulnerability in Hitachi JP1/IT Desktop Management 2 - Smart Device Manager on
A vulnerability has been identified in the libarchive library. This flaw involves an integer overflo
A vulnerability has been identified in the libarchive library. This flaw can be triggered when file
handcraftedinthealps goodby-csv is a highly memory efficient, flexible and extendable open-source CS
A vulnerability, which was classified as problematic, has been found in TOTOLINK T10 4.1.8cu.5207. A