Vulnerability in Huggingface Huggingface/transformers
CVE-2025-1194
A Regular Expression Denial of Service (ReDoS) vulnerability was identified in the huggingface/transformers library, specifically in the file `tokenization_gpt_neox_japanese.py` of the GPT-NeoX-Japanese model. The vulnerability occurs in the SubWordJapaneseTokenizer class, where regular expressions process specially crafted inputs. The issue stems from a regex exhibiting exponential complexity under certain conditions, leading to excessive backtracking. This can result in high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) scenario. The affected version is v4.48.1 (latest).
Vulnerability class: ReDoS (Regular Expression Denial of Service)
EPSS: 0.004 (33.4th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 6.5 (Medium). Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H.
Affected products
- Huggingface Huggingface/transformers — versions unspecified
- Huggingface Transformers
Weakness classification (CWE)
Public proof-of-concept exploits
References
- security@huntr.dev (Exploit, Third Party Advisory)
- security@huntr.dev (Patch)
Frequently asked questions
- What is CVE-2025-1194?
- CVE-2025-1194 is a medium-severity vulnerability in Huggingface Huggingface/transformers, classified under Inefficient Regular Expression Complexity. CVSS score: 6.5/10. Published 2025-04-29.
- How severe is CVE-2025-1194?
- Medium severity. CVSS v3 base score is 6.5 out of 10.
- Is CVE-2025-1194 known to be exploited?
- 3 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.