CVE-2025-3777: Transformers vulnerable to improper input validation in image_utils
Transformers
An improper input validation flaw in Hugging Face Transformers allows URL username injection to bypass validation checks. A patch has been released in version 4.52.1.
disclosed CVENo confirmed exploitation, so this record is tracked as a disclosed vulnerability and not counted as an incident. It moves into the counts if CISA or the vendor confirms exploitation. Why
- CVSS
- 3.5
- EPSS
- <0.01 · top 64% · 2026-11-13
- fix status
- Fix status unknown
- first report
- 7 Jul 2025
- last update
- 7 Jul 2025
- CVE ids
Timeline · 2
Sources · 2
Advisories and databases
- 2025-07-07CVE-2025-3777: Transformers's Improper Input Validation vulnerability can be exploited through username injectionGitHub Advisory Database · github.com/advisories/GHSA-phhr-52qp-3mj4
- 2025-07-07CVE-2025-3777: Hugging Face Transformers versions up to 4.49.0 are affected by an improper input validation vulnerability in the…NVD · nvd.nist.gov/vuln/detail/CVE-2025-3777
Titles and links belong to their publishers. The summary above is written by gcdRadar in its own words; data is CC BY-SA 4.0.
Classification
- lane
- Patch now
- AI role
- Attack on AI
- categories
- Infrastructure vulnerability
- severity
- 2 · Disclosed vulnerability
- fix status
- Fix status unknown
- targets
- Framework / tooling
- owasp llm top 10
- LLM03:2025 Supply Chain
- mitre atlas
- no technique for these categories
- tags
- input-validation
- dates
- happened 7 Jul 2025 · first reported 7 Jul 2025
- origin
- GitHub Advisory DatabaseVulnerability record from NVD / the GitHub Advisory Database. This product uses the NVD API but is not endorsed or certified by the NVD.
- record
- confidence 0.95 · created 2026-10-18 07:00Z · updated 2026-10-18 10:04Z
Lane, AI role, categories and severity come from the classifier; the OWASP and ATLAS rows are derived from the categories. How these are assigned
Copy a brief
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the brief as text
# CVE-2025-3777: Transformers vulnerable to improper input validation in image_utils https://gcdradar.vercel.app/incidents/cve-2025-3777-transformers-vulnerable-to-improper-input-vali · AIR-2025-0313 · closed 2025-07-07 - Lane: Patch now - Severity: 2 (Disclosed vulnerability) - Fix status: Fix status unknown - First reported: 2025-07-07 - AI role: Attack on AI - Products: Transformers - CVE ids: CVE-2025-3777 - CVSS: 3.5 ## Summary An improper input validation flaw in Hugging Face Transformers allows URL username injection to bypass validation checks. A patch has been released in version 4.52.1. ## What to do No action recorded; read the sources below and the vendor's advisory. ## Latest updates - 2025-07-07: CVE-2025-3777: Hugging Face Transformers versions up to 4.49.0 are affected by an improper input validation vulnerability in the… (https://nvd.nist.gov/vuln/detail/CVE-2025-3777) - 2025-07-07: CVE-2025-3777: Transformers's Improper Input Validation vulnerability can be exploited through username injection (https://github.com/advisories/GHSA-phhr-52qp-3mj4) ## Sources - 2025-07-07 GitHub Advisory Database: CVE-2025-3777: Transformers's Improper Input Validation vulnerability can be exploited through username injection https://github.com/advisories/GHSA-phhr-52qp-3mj4 - 2025-07-07 NVD: CVE-2025-3777: Hugging Face Transformers versions up to 4.49.0 are affected by an improper input validation vulnerability in the… https://nvd.nist.gov/vuln/detail/CVE-2025-3777 Verify against the vendor's advisory before changing production. Data CC BY-SA 4.0, https://gcdradar.vercel.app.
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