CVE-2025-3777: huggingface/transformers · Improper Input Validation
Affects huggingface/transformersSource CVE Database V5
Not known to be exploited · CVSS 3.5 Low · fixed in 4.52.1 : update huggingface/transformers when convenient.
Data as of 26 Oct 2026, 06:26 UTC
- EPSS
- 0.4% chance of exploitation in 30 days – higher than 34% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 4.52.1
CVSS:3.0/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:N/A:NExploitation evidence
Disclosed: evidence found.
CVE published 7 Jul 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.
What to do
Affected software
| Product | Affected | Fixed in |
|---|---|---|
PyPItransformerspkg:pypi/transformersOther threats | Affected
| Fixed in– |
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
1. Immediate upgrade of the Hugging Face Transformers library to version 4.52.1 or later, where the vulnerability is fixed. 2. Implement strict URL validation using robust parsing libraries (e.g., urllib.parse in Python) instead of naive string methods like startswith(). 3. Employ additional security controls such as URL allowlisting, domain verification, and threat intelligence integration to detect and block suspicious URLs before processing. 4. Educate developers and security teams about the risks of improper input validation and encourage secure coding practices, especially when handling external inputs like URLs. 5. Conduct regular code audits and dependency scans to identify and remediate vulnerabilities in third-party libraries. 6. For user-facing applications, implement multi-factor authentication and phishing detection mechanisms to mitigate the impact of social engineering attacks. 7. Monitor network traffic and logs for unusual URL access patterns that could indicate exploitation attempts.
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.