How severe is CVE-2025-1194?

CVE-2025-1194 has a CVSS 3.x base score of 6.5, rated medium severity. It is exploitable over network with low attack complexity, requires no privileges and user interaction. Impact on confidentiality is none, integrity none, and availability high.

Is CVE-2025-1194 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (30th percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2025-1194?

CVE-2025-1194 affects Huggingface Transformers. See the affected-products list for the exact vulnerable versions.

How do I fix CVE-2025-1194?

Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.

Does CVE-2025-1194 have an EU (EUVD) identifier?

Yes. CVE-2025-1194 is tracked in the ENISA EU Vulnerability Database (EUVD) as EUVD-2025-15128.

When was CVE-2025-1194 published?

CVE-2025-1194 was published on 2025-04-29 and last updated on 2026-06-17.

CVE-2025-1194

CVE-2025-1194 is a medium-severity vulnerability in Huggingface Transformers with a CVSS 3.x base score of 6.5. It is not currently listed as actively exploited by CISA, and its EPSS exploit-prediction score is low. The underlying weakness is classified as CWE-1333.

Key facts

Severity: Medium (CVSS 3.x base score 6.5)
EPSS exploit prediction: 0% (30th percentile)
Actively exploited: Not listed in CISA KEV
EU (EUVD) id: EUVD-2025-15128
Weakness: CWE-1333
Affected product: Huggingface Transformers
Published: 2025-04-29
Last modified: 2026-06-17

Description

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).

Frequently asked questions

What is 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).
How severe is CVE-2025-1194?: CVE-2025-1194 has a CVSS 3.x base score of 6.5, rated medium severity. It is exploitable over network with low attack complexity, requires no privileges and user interaction. Impact on confidentiality is none, integrity none, and availability high.
Is CVE-2025-1194 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (30th percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2025-1194?: CVE-2025-1194 affects Huggingface Transformers. See the affected-products list for the exact vulnerable versions.
How do I fix CVE-2025-1194?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
Does CVE-2025-1194 have an EU (EUVD) identifier?: Yes. CVE-2025-1194 is tracked in the ENISA EU Vulnerability Database (EUVD) as EUVD-2025-15128.
When was CVE-2025-1194 published?: CVE-2025-1194 was published on 2025-04-29 and last updated on 2026-06-17.

References

Affected products (1)

cpe:2.3:a:huggingface:transformers:*:*:*:*:*:*:*:*

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