CVE-2025-1194
Regular Expression Denial of Service (ReDoS) in huggingface/transformers
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).
Attack profile
How easy it is to exploit
- Attack vector
- Network
- Complexity
- Low
- Privileges needed
- None
- User interaction
- Required
What an attacker can affect
- Confidentiality
- None
- Integrity
- None
- Availability
- Low
Exploit likelihood
What each source reports
CVE List Score used
Regular Expression Denial of Service (ReDoS) in huggingface/transformers
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).
- Record
CVE-2025-1194- CVSS 3.0
- 4.3 Medium
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L - Weakness
- CWE-1333
- Updated
- 2026-11-02
EUVDEUVD-2025-15128
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).
- Record
EUVD-2025-15128- CVSS 3.0
- 4.3 Medium
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L - Updated
- 2026-11-02
GitHub AdvisoriesGHSA-fpwr-67px-3qhx
Transformers Regular Expression Denial of Service (ReDoS) vulnerability
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).
- Record
GHSA-fpwr-67px-3qhx- CVSS 3.1
- 4.3 Medium
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L - Weakness
- CWE-1333
- Updated
- 2026-11-02
NVD
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).
- Record
CVE-2025-1194- CVSS 3.1
- 6.5 Medium
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H - CVSS 3.0
- 4.3 Medium
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L - Weakness
- CWE-1333
- Updated
- 2026-11-02
OSV
Regular Expression Denial of Service (ReDoS) in huggingface/transformers
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).
- Record
CVE-2025-1194- CVSS 3.0
- 4.3 Medium
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L - Weakness
- CWE-1333
- Updated
- 2026-11-02
OSVGHSA-fpwr-67px-3qhx
Transformers Regular Expression Denial of Service (ReDoS) vulnerability
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).
- Record
GHSA-fpwr-67px-3qhx- CVSS 3.1
- 4.3 Medium
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L - Weakness
- CWE-1333
- Updated
- 2026-11-02
OSVPYSEC-2026-1984
Transformers Regular Expression Denial of Service (ReDoS) vulnerability
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).
- Record
PYSEC-2026-1984- CVSS 3.1
- 4.3 Medium
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L - Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
transformersPyPI |
before 4.50.0 | 4.50.0 |
transformersPyPI |
before 4.50.0, plus listed versions 0.12.0.02.1.02.1.12.10.0 Show 45 moreShow less2.11.02.2.02.2.12.2.22.3.02.4.02.4.12.5.02.5.12.6.02.7.02.8.02.9.02.9.13.0.03.0.13.0.23.1.03.2.03.3.03.3.13.4.03.5.03.5.14.0.04.0.0rc14.0.14.1.04.1.14.10.04.10.14.10.24.10.34.11.04.11.14.11.24.11.34.12.04.12.14.12.24.12.34.12.44.12.54.13.04.14.0 |
4.50.0 |
History
| Recorded | Changed | Sources |
|---|---|---|
| first indexed | CVE List, EUVD, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2025-1194 is a medium vulnerability (CVSS 4.3) in Huggingface Huggingface/transformers, published April 29, 2025. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.49%, the 42nd percentile. Fixed in transformers 4.50.0.
References
huntr.com/bounties/86f58dcd-683f-4adc-a735-849f51e9abb2
github.com/huggingface/transformers/commit/92c5ca9dd70de3ade2af2eb835c96215cc50e815
nvd.nist.gov/vuln/detail/CVE-2025-1194
pypi.org/project/transformers
Left out here: 121 versions. The JSON record has them.