{"answers":{"affected":"4 open source packages ship an affected version, including pytorch and torch. It affects 1 product.","exploited":"It is not confirmed as exploited in the wild, but public exploit code for CVE-2025-2953 exists.","fix":"Upgrade pytorch to 2.7.0 or later.","what":"CVE-2025-2953 is a medium-severity denial of service vulnerability in PyTorch, published on 30 Mar 2025. It can only be exploited from the same machine or local network, with no action from the victim."},"fix_prompt":"Check this codebase for CVE-2025-2953 and fix it if it is affected.\n\nWhat it is: CVE-2025-2953 is a medium-severity denial of service vulnerability in PyTorch, published on 30 Mar 2025. It can only be exploited from the same machine or local network, with no action from the victim.\nExploitation: It is not confirmed as exploited in the wild, but public exploit code for CVE-2025-2953 exists.\n\nAffected packages and fixed versions:\n- pytorch (Bitnami): affected from 2.6.0; fixed in 2.7.0\n- torch (PyPI): affected all versions up to 2.6.0+cu124; no fix listed\n- torch (PyPI): affected all versions; fixed in 2.7.1-rc1\n- torch (PyPI): affected all versions; fixed in 2.7.1-rc1\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-2025-2953/ (Markdown: https://insights.sbomify.com/CVE-2025-2953/index.md)","id":"CVE-2025-2953","markdown":"https://insights.sbomify.com/CVE-2025-2953/index.md","name":"CVE-2025-2953","record":{"aliases":["AZL-60913","AZL-60931","BIT-pytorch-2025-2953","DEBIAN-CVE-2025-2953","ECHO-8cc1-2152-8f65","GHSA-3749-ghw9-m3mg","PYSEC-2025-191","UBUNTU-CVE-2025-2953"],"analysis":{"component_type":"library","fix_type":"no_fix_stated","impacts":["denial_of_service"],"network_reachable":"adjacent_or_local","non_default_config":false,"product_category":"PyTorch machine learning library","requires_auth":"low_privilege","summary":"A local attacker can cause a denial of service in PyTorch via the mkldnn_max_pool2d function, impacting system availability.","user_interaction":"not_required","vuln_class":"denial_of_service"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"VulDB","cpe":[{"product":"pytorch","vendor":"linuxfoundation"}],"cvss":{"score":4.8,"severity":"medium","source":"cna","vector":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N","version":"4.0"},"cwes":[{"id":"CWE-404","name":"Improper Resource Shutdown or Release"}],"description":"A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The real existence of this vulnerability is still doubted at the moment. The security policy of the project warns to use unknown models which might establish malicious effects.","ecosystems":["Bitnami","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":"PyTorch torch.mkldnn_max_pool2d denial of service","id":"CVE-2025-2953","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":null,"products":[],"type":"denial_of_service","year":"2025"},"n_packages":4,"n_references":6,"next":{"headline":"mannaandpoem OpenManus File file_saver.py execute access control","id":"CVE-2025-2954"},"packages":[{"ecosystem":"Bitnami","fixed":["2.7.0"],"introduced":["2.6.0"],"last_affected":[],"package":"pytorch","purl":"pkg:bitnami/pytorch","source":"BIT-pytorch-2025-2953"},{"ecosystem":"PyPI","fixed":[],"introduced":["0"],"last_affected":["2.6.0+cu124"],"package":"torch","purl":"pkg:pypi/torch","source":"PYSEC-2025-191"},{"ecosystem":"PyPI","fixed":["2.7.1-rc1"],"introduced":["0"],"last_affected":[],"package":"torch","purl":null,"source":"GHSA-3749-ghw9-m3mg"},{"ecosystem":"PyPI","fixed":["2.7.1-rc1"],"introduced":["0"],"last_affected":[],"package":"torch","purl":"pkg:pypi/torch","source":"GHSA-3749-ghw9-m3mg"}],"prev":{"headline":"Bluestar Micro Mall api.php unrestricted upload","id":"CVE-2025-2952"},"products":["PyTorch"],"published":"2025-03-30","related":[{"cvss_score":9.8,"headline":"Deserialization in n/a","id":"CVE-2024-48063","kev_date_added":null,"published":"2024-10-29"},{"cvss_score":9.8,"headline":"PyTorch vulnerable to arbitrary code execution","id":"CVE-2022-45907","kev_date_added":null,"published":"2022-11-26"},{"cvss_score":9.3,"headline":"PyTorch: `torch.load` with `weights_only=True` leads to remote code execution","id":"CVE-2025-32434","kev_date_added":null,"published":"2025-04-18"},{"cvss_score":8.8,"headline":"PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files","id":"CVE-2026-24747","kev_date_added":null,"published":"2026-01-27"},{"cvss_score":7.8,"headline":"Pytorch use-after-free vulnerability","id":"CVE-2024-31583","kev_date_added":null,"published":"2024-04-17"},{"cvss_score":7.5,"headline":"Denial of service in n/a","id":"CVE-2025-55551","kev_date_added":null,"published":"2025-09-25"},{"cvss_score":7.5,"headline":"Denial of service in n/a","id":"CVE-2025-55553","kev_date_added":null,"published":"2025-09-25"}],"sources":[{"class":"attribution","licence":"Apache-2.0","name":"Bitnami","prefix":"BIT"},{"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":"no","exploitation":"poc","technical_impact":"partial"},"state":"PUBLISHED","updated":"2025-04-22","vendors":["n/a"]},"summary":"A local attacker can cause a denial of service in PyTorch via the mkldnn_max_pool2d function, impacting system availability.","url":"https://insights.sbomify.com/CVE-2025-2953/"}