GCD AI RADAR
incidents/AIR-2025-0313

CVE-2025-3777: Transformers vulnerable to improper input validation in image_utils

Attack on AI2 Disclosed vulnerabilityInfrastructure vulnerability

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

Details

type
Attack on AI
An AI model, agent or AI-powered product was the thing exploited, abused or leaked.
categories
  • Infrastructure vulnerability
    CVEs and advisories in AI frameworks, inference servers, MCP servers, AI developer tools and hosting stacks.
owasp llm top 10
mitre atlas
no technique for these categories
Both rows are derived from the type and categories (OWASP 2025 edition, ATLAS release 2026.09), not classified per record. How
severity
2 · Disclosed vulnerability
CVE or vendor advisory, patched or patchable, no confirmed exploitation.
targets
Framework / tooling
products
Transformers
incident date
7 Jul 2025
first reported
7 Jul 2025
origin
GitHub Advisory Database
Vulnerability record from NVD / the GitHub Advisory Database. This product uses the NVD API but is not endorsed or certified by the NVD.
classifier confidence
0.95 · published at or above 0.80; see the methodology
tags
CVE-2025-3777 · input-validation
record
created 2026-10-18 07:00Z · updated 2026-10-18 10:04Z · json

Sources · 2

  1. 2025-07-07
    CVE-2025-3777: Transformers's Improper Input Validation vulnerability can be exploited through username injection
    GitHub Advisory Database · github.com/advisories/GHSA-phhr-52qp-3mj4
  2. 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…
    NVD · nvd.nist.gov/vuln/detail/CVE-2025-3777

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