{"answers":{"affected":"2 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-2025-3136 exists.","fix":"Upgrade pytorch to 2.7.0 or later.","what":"CVE-2025-3136 is a medium-severity memory corruption vulnerability in PyTorch, published on 3 Apr 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-2025-3136 and fix it if it is affected.\n\nWhat it is: CVE-2025-3136 is a medium-severity memory corruption vulnerability in PyTorch, published on 3 Apr 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-2025-3136 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-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-2025-3136/ (Markdown: https://insights.sbomify.com/CVE-2025-3136/index.md)","id":"CVE-2025-3136","markdown":"https://insights.sbomify.com/CVE-2025-3136/index.md","name":"CVE-2025-3136","record":{"aliases":["BIT-pytorch-2025-3136","DEBIAN-CVE-2025-3136","ECHO-ff69-5060-f4ce","GHSA-r37f-v2p6-x6cx","PYSEC-2025-197","UBUNTU-CVE-2025-3136"],"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":"Local attackers can exploit memory corruption in PyTorch's CUDA caching allocator to potentially execute arbitrary code or cause 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:N/VI:N/VA:L/SC:N/SI:N/SA:N","version":"4.0"},"cwes":[{"id":"CWE-787","name":"Out-of-bounds Write"},{"id":"CWE-119","name":"Improper Restriction of Operations within the Bounds of a Memory Buffer"}],"description":"A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0. This issue affects the function torch.cuda.memory.caching_allocator_delete of the file c10/cuda/CUDACachingAllocator.cpp. The manipulation leads to memory corruption. An attack has to be approached locally. 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 CUDACachingAllocator.cpp torch.cuda.memory.caching_allocator_delete memory corruption","id":"CVE-2025-3136","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":null,"products":[],"type":"memory_corruption","year":"2025"},"n_packages":2,"n_references":6,"next":{"headline":"PHPGurukul Online Security Guards Hiring System changeimage.php sql injection","id":"CVE-2025-3137"},"packages":[{"ecosystem":"Bitnami","fixed":["2.7.0"],"introduced":["2.6.0"],"last_affected":[],"package":"pytorch","purl":"pkg:bitnami/pytorch","source":"BIT-pytorch-2025-3136"},{"ecosystem":"PyPI","fixed":[],"introduced":["0"],"last_affected":["2.6.0-NA"],"package":"torch","purl":"pkg:pypi/torch","source":"PYSEC-2025-197"}],"prev":{"headline":"fcba_zzm ics-park Smart Park Management System update sql injection","id":"CVE-2025-3135"},"products":["PyTorch"],"published":"2025-04-03","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":"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":"2025-04-03","vendors":["n/a"]},"summary":"Local attackers can exploit memory corruption in PyTorch's CUDA caching allocator to potentially execute arbitrary code or cause denial of service.","url":"https://insights.sbomify.com/CVE-2025-3136/"}