{"answers":{"affected":"3 open source packages ship an affected version, including scikit-learn. It affects 1 product.","exploited":"It is not confirmed as exploited in the wild, but public exploit code for CVE-2020-28975 exists.","fix":"Upgrade scikit-learn to a fixed version for your release line: 0.24.dev0 or 1.0.1.","what":"CVE-2020-28975 is a high-severity denial of service vulnerability in n/a, published on 21 Nov 2020. An attacker can exploit it over the internet without logging in, with no action from the victim."},"fix_prompt":"Check this codebase for CVE-2020-28975 and fix it if it is affected.\n\nWhat it is: CVE-2020-28975 is a high-severity denial of service vulnerability in n/a, published on 21 Nov 2020. 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-2020-28975 exists.\n\nAffected packages and fixed versions:\n- scikit-learn (PyPI): affected all versions; fixed in 0.24.dev0\n- scikit-learn (PyPI): affected from 0.23.2; fixed in 1.0.1\n- scikit-learn (PyPI): affected from 0.23.2; fixed in 1.0.1\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-2020-28975/ (Markdown: https://insights.sbomify.com/CVE-2020-28975/index.md)","id":"CVE-2020-28975","markdown":"https://insights.sbomify.com/CVE-2020-28975/index.md","name":"CVE-2020-28975","record":{"aliases":["GHSA-jxfp-4rvq-9h9m","PYSEC-2020-108","openSUSE-SU-2024:11805-1","openSUSE-SU-2025:14729-1"],"analysis":{"component_type":"library","fix_type":"patch","impacts":["denial_of_service"],"network_reachable":"yes","non_default_config":false,"product_category":"Machine learning library","requires_auth":"none","summary":"Attackers can cause a segmentation fault and denial of service in Libsvm by providing a crafted model with large support values.","user_interaction":"not_required","vuln_class":"denial_of_service"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"mitre","cpe":[{"product":"scikit-learn","vendor":"scikit-learn"}],"cvss":{"score":7.5,"severity":"high","source":"nvd","vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","version":"3.1"},"cwes":[],"description":"svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 0.23.2 and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.","ecosystems":["PyPI","openSUSE:Tumbleweed"],"exploits":{"exploitdb":0,"first_seen":null,"github_poc":0,"max_poc_stars":null,"metasploit":0,"nuclei":0,"refs":[],"tier":"weaponised"},"has_fix":true,"headline":"scikit-learn Denial of Service","id":"CVE-2020-28975","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"PyPI","product":null,"products":[],"type":"denial_of_service","year":"2020"},"n_packages":4,"n_references":6,"next":{"headline":"Server-side request forgery in n/a","id":"CVE-2020-28976"},"packages":[{"ecosystem":"PyPI","fixed":["0.24.dev0"],"introduced":["0"],"last_affected":[],"package":"scikit-learn","purl":"pkg:pypi/scikit-learn","source":"PYSEC-2020-108"},{"ecosystem":"PyPI","fixed":["1.0.1"],"introduced":["0.23.2"],"last_affected":[],"package":"scikit-learn","purl":null,"source":"GHSA-jxfp-4rvq-9h9m"},{"ecosystem":"PyPI","fixed":["1.0.1"],"introduced":["0.23.2"],"last_affected":[],"package":"scikit-learn","purl":"pkg:pypi/scikit-learn","source":"GHSA-jxfp-4rvq-9h9m"},{"ecosystem":"openSUSE:Tumbleweed","fixed":["1.6.1-1.1"],"introduced":["0"],"last_affected":[],"package":"python-scikit-learn","purl":"pkg:rpm/opensuse/python-scikit-learn\u0026distro=openSUSE%20Tumbleweed","source":"openSUSE-SU-2025:14729-1"}],"prev":{"headline":"Information disclosure in n/a","id":"CVE-2020-28974"},"products":["n/a"],"published":"2020-11-21","related":[{"cvss_score":9.8,"headline":"scikit-learn Deserialization of Untrusted Data","id":"CVE-2020-13092","kev_date_added":null,"published":"2020-05-15"},{"cvss_score":4.7,"headline":"Sensitive Data Leakage in sklearn.feature_extraction.text.TfidfVectorizer in scikit-learn/scikit-learn","id":"CVE-2024-5206","kev_date_added":null,"published":"2024-06-06"}],"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":"CC BY 4.0","name":"SUSE","prefix":"openSUSE"},{"class":"attribution","licence":"US public information, NVD API terms","name":"NVD"},{"class":"attribution","licence":"FIRST CVSS licence","name":"CVSS (FIRST)"}],"ssvc":{"automatable":"no","exploitation":"poc","technical_impact":"partial"},"state":"PUBLISHED","updated":"2024-08-04","vendors":["n/a"]},"summary":"Attackers can cause a segmentation fault and denial of service in Libsvm by providing a crafted model with large support values.","url":"https://insights.sbomify.com/CVE-2020-28975/"}