{"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-2025-2998 exists.","fix":"Upgrade pytorch to 2.7.0 or later.","what":"CVE-2025-2998 is a medium-severity memory corruption vulnerability in PyTorch, published on 31 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-2025-2998 and fix it if it is affected.\n\nWhat it is: CVE-2025-2998 is a medium-severity memory corruption vulnerability in PyTorch, published on 31 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-2025-2998 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; no fix listed\n- torch (PyPI): affected all versions up to 2.6.0; no fix listed\n- torch (PyPI): affected all versions up to 2.6.0-NA; no fix listed\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-2025-2998/ (Markdown: https://insights.sbomify.com/CVE-2025-2998/index.md)","id":"CVE-2025-2998","markdown":"https://insights.sbomify.com/CVE-2025-2998/index.md","name":"CVE-2025-2998","record":{"aliases":["BIT-pytorch-2025-2998","DEBIAN-CVE-2025-2998","ECHO-a3a3-45a6-10ed","GHSA-f4hp-rmr7-r7v8","PYSEC-2025-192","UBUNTU-CVE-2025-2998"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["code_execution","denial_of_service"],"network_reachable":"adjacent_or_local","non_default_config":false,"product_category":"PyTorch deep learning library","requires_auth":"low_privilege","summary":"A local attacker can exploit memory corruption in PyTorch's pad_packed_sequence function to potentially execute arbitrary code or cause a denial of service.","user_interaction":"not_required","vuln_class":"memory_corruption"},"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:L/VI:L/VA:L/SC:N/SI:N/SA:N","version":"4.0"},"cwes":[{"id":"CWE-119","name":"Improper Restriction of Operations within the Bounds of a Memory Buffer"}],"description":"A vulnerability was found in PyTorch 2.6.0. It has been declared as critical. Affected by this vulnerability is the function torch.nn.utils.rnn.pad_packed_sequence. The manipulation leads to memory corruption. Local access is required to approach this attack. The exploit has been disclosed to the public and may be used.","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.nn.utils.rnn.pad_packed_sequence memory corruption","id":"CVE-2025-2998","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":null,"products":[],"type":"memory_corruption","year":"2025"},"n_packages":4,"n_references":5,"next":{"headline":"PyTorch torch.nn.utils.rnn.unpack_sequence memory corruption","id":"CVE-2025-2999"},"packages":[{"ecosystem":"Bitnami","fixed":["2.7.0"],"introduced":["2.6.0"],"last_affected":[],"package":"pytorch","purl":"pkg:bitnami/pytorch","source":"BIT-pytorch-2025-2998"},{"ecosystem":"PyPI","fixed":[],"introduced":["0"],"last_affected":["2.6.0"],"package":"torch","purl":null,"source":"GHSA-f4hp-rmr7-r7v8"},{"ecosystem":"PyPI","fixed":[],"introduced":["0"],"last_affected":["2.6.0"],"package":"torch","purl":"pkg:pypi/torch","source":"GHSA-f4hp-rmr7-r7v8"},{"ecosystem":"PyPI","fixed":[],"introduced":["0"],"last_affected":["2.6.0-NA"],"package":"torch","purl":"pkg:pypi/torch","source":"PYSEC-2025-192"}],"prev":{"headline":"zhangyanbo2007 youkefu url server-side request forgery","id":"CVE-2025-2997"},"products":["PyTorch"],"published":"2025-03-31","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":"2025-03-31","vendors":["n/a"]},"summary":"A local attacker can exploit memory corruption in PyTorch's pad_packed_sequence function to potentially execute arbitrary code or cause a denial of service.","url":"https://insights.sbomify.com/CVE-2025-2998/"}