{"answers":{"affected":"3 open source packages ship an affected version, including transformers. It affects 1 product.","exploited":"It is not confirmed as exploited in the wild, but public exploit code for CVE-2025-6638 exists.","fix":"Upgrade transformers to 4.53.0 or later.","what":"CVE-2025-6638 is a medium-severity denial of service vulnerability in huggingface/transformers, published on 12 Sep 2025. An attacker can exploit it over the internet without logging in, with no action from the victim."},"fix_prompt":"Check this codebase for CVE-2025-6638 and fix it if it is affected.\n\nWhat it is: CVE-2025-6638 is a medium-severity denial of service vulnerability in huggingface/transformers, published on 12 Sep 2025. An attacker can exploit it over the internet without logging in, with no action from the victim.\nExploitation: It is not confirmed as exploited in the wild, but public exploit code for CVE-2025-6638 exists.\n\nAffected packages and fixed versions:\n- transformers (PyPI): affected all versions; fixed in 4.53.0\n- transformers (PyPI): affected all versions; fixed in 4.53.0\n- transformers (PyPI): affected all versions; fixed in 4.53.0\n\nTask:\n1. Search the dependency manifests and lockfiles (for example package.json, package-lock.json, requirements.txt, poetry.lock, uv.lock, pom.xml, build.gradle, go.mod, Cargo.lock, Gemfile.lock) and any Dockerfiles for the affected packages, including transitive dependencies.\n2. If an affected version is in use, upgrade it to the fixed version for its release line with the project's package manager, so the lockfile is regenerated. Prefer the smallest upgrade that fixes it.\n3. If there is no fix, or the upgrade would break the build, do not guess: explain the risk and the safest workaround instead.\n4. Run the tests and summarise what changed and why.\n5. If nothing in the project is affected, say so and change nothing.\n\nReference: https://insights.sbomify.com/CVE-2025-6638/ (Markdown: https://insights.sbomify.com/CVE-2025-6638/index.md)","id":"CVE-2025-6638","markdown":"https://insights.sbomify.com/CVE-2025-6638/index.md","name":"CVE-2025-6638","record":{"aliases":["GHSA-59p9-h35m-wg4g","PYSEC-2026-1981"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["denial_of_service"],"network_reachable":"yes","non_default_config":false,"product_category":"Python ML library","requires_auth":"none","summary":"Attackers can cause denial of service in Hugging Face Transformers by submitting crafted inputs to the MarianTokenizer, leading to excessive CPU consumption.","user_interaction":"not_required","vuln_class":"denial_of_service"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"@huntr_ai","cpe":[{"product":"transformers","vendor":"huggingface"}],"cvss":{"score":5.3,"severity":"medium","source":"cna","vector":"CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L","version":"3.0"},"cwes":[{"id":"CWE-1333","name":"Inefficient Regular Expression Complexity"}],"description":"A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically affecting the MarianTokenizer's `remove_language_code()` method. This vulnerability is present in version 4.52.4 and has been fixed in version 4.53.0. The issue arises from inefficient regex processing, which can be exploited by crafted input strings containing malformed language code patterns, leading to excessive CPU consumption and potential denial of service.","ecosystems":["PyPI"],"exploits":{"exploitdb":0,"first_seen":null,"github_poc":0,"max_poc_stars":null,"metasploit":0,"nuclei":0,"refs":[],"tier":"weaponised"},"has_fix":true,"headline":"Regular Expression Denial of Service (ReDoS) in huggingface/transformers","id":"CVE-2025-6638","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"PyPI","product":null,"products":[],"type":"denial_of_service","year":"2025"},"n_packages":3,"n_references":2,"next":{"headline":"Missing authorization in Tutor LMS Pro","id":"CVE-2025-6639"},"packages":[{"ecosystem":"PyPI","fixed":["4.53.0"],"introduced":["0"],"last_affected":[],"package":"transformers","purl":null,"source":"GHSA-59p9-h35m-wg4g"},{"ecosystem":"PyPI","fixed":["4.53.0"],"introduced":["0"],"last_affected":[],"package":"transformers","purl":"pkg:pypi/transformers","source":"GHSA-59p9-h35m-wg4g"},{"ecosystem":"PyPI","fixed":["4.53.0"],"introduced":["0"],"last_affected":[],"package":"transformers","purl":"pkg:pypi/transformers","source":"PYSEC-2026-1981"}],"prev":{"headline":"PRT File Parsing Out-of-Bounds Write Vulnerability","id":"CVE-2025-6637"},"products":["huggingface/transformers"],"published":"2025-09-12","related":[{"cvss_score":9.6,"headline":"Deserialization of Untrusted Data in huggingface/transformers","id":"CVE-2023-7018","kev_date_added":null,"published":"2023-12-20"},{"cvss_score":9,"headline":"Deserialization of Untrusted Data in huggingface/transformers","id":"CVE-2023-6730","kev_date_added":null,"published":"2023-12-19"},{"cvss_score":8.8,"headline":"Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability","id":"CVE-2024-11393","kev_date_added":null,"published":"2024-11-22"},{"cvss_score":8.8,"headline":"Hugging Face Transformers Trax Model Deserialization of Untrusted Data Remote Code Execution Vulnerability","id":"CVE-2024-11394","kev_date_added":null,"published":"2024-11-22"},{"cvss_score":8,"headline":"Policy Bypass in LightGlue Nested Config Resolution in huggingface/transformers","id":"CVE-2026-5241","kev_date_added":null,"published":"2026-06-03"},{"cvss_score":7.8,"headline":"Arbitrary Remote Code Execution via `_attn_implementation_internal` Config Injection in huggingface/transformers","id":"CVE-2026-4372","kev_date_added":null,"published":"2026-05-24"},{"cvss_score":7.8,"headline":"Hugging Face Transformers Perceiver Model Deserialization of Untrusted Data Remote Code Execution Vulnerability","id":"CVE-2025-14920","kev_date_added":null,"published":"2025-12-23"}],"sources":[{"class":"attribution","licence":"CVE Terms of Use (MITRE)","name":"CVE List","prefix":"CVE"},{"class":"attribution","licence":"CC BY 4.0","name":"GitHub Advisory Database","prefix":"GHSA"},{"class":"attribution","licence":"CC BY 4.0","name":"PyPA Advisory Database","prefix":"PYSEC"},{"class":"attribution","licence":"US public information, NVD API terms","name":"NVD"},{"class":"attribution","licence":"CWE Terms of Use","name":"CWE (MITRE)"},{"class":"attribution","licence":"FIRST CVSS licence","name":"CVSS (FIRST)"}],"ssvc":{"automatable":"yes","exploitation":"poc","technical_impact":"partial"},"state":"PUBLISHED","updated":"2025-09-12","vendors":["huggingface"]},"summary":"Attackers can cause denial of service in Hugging Face Transformers by submitting crafted inputs to the MarianTokenizer, leading to excessive CPU consumption.","url":"https://insights.sbomify.com/CVE-2025-6638/"}