{"answers":{"affected":"3 open source packages ship an affected version, including executorch.","exploited":"There is no known exploitation of CVE-2025-54952 in the wild and no public exploit code.","fix":"No fix has been published for CVE-2025-54952 yet. Limit exposure of the affected software until one is available.","what":"CVE-2025-54952 is a critical vulnerability in Meta Platforms, Inc ExecuTorch, published on 7 Aug 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-2025-54952 and fix it if it is affected.\n\nWhat it is: CVE-2025-54952 is a critical vulnerability in Meta Platforms, Inc ExecuTorch, published on 7 Aug 2025. An attacker can exploit it over the internet without logging in, with no action from the victim.\nExploitation: There is no known exploitation of CVE-2025-54952 in the wild and no public exploit code.\n\nAffected packages and fixed versions:\n- executorch (PyPI): affected all versions up to 0.6.0; no fix listed\n- executorch (PyPI): affected all versions up to 0.6.0; no fix listed\n- executorch (PyPI): affected all versions up to 0.6.0; 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-2025-54952/ (Markdown: https://insights.sbomify.com/CVE-2025-54952/index.md)","id":"CVE-2025-54952","markdown":"https://insights.sbomify.com/CVE-2025-54952/index.md","name":"CVE-2025-54952","record":{"aliases":["GHSA-33r8-vrx9-rmcv","PYSEC-2026-1351"],"analysis":{"component_type":"library","fix_type":"patch","impacts":["code_execution"],"network_reachable":"yes","non_default_config":false,"product_category":"ExecuTorch ML library","requires_auth":"none","summary":"Integer overflow in ExecuTorch model loading allows attackers to trigger code execution via crafted models.","user_interaction":"not_required","vuln_class":"integer_overflow"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"facebook","cpe":[],"cvss":{"score":9.8,"severity":"critical","source":"cisa-adp","vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H","version":"3.1"},"cwes":[{"id":"CWE-680","name":"Integer Overflow to Buffer Overflow"}],"description":"An integer overflow vulnerability in the loading of ExecuTorch models can cause smaller-than-expected memory regions to be allocated, potentially resulting in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit 8f062d3f661e20bb19b24b767b9a9a46e8359f2b.","ecosystems":["PyPI"],"exploits":{"exploitdb":0,"first_seen":null,"github_poc":0,"max_poc_stars":null,"metasploit":0,"nuclei":0,"refs":[],"tier":"none_known"},"has_fix":false,"headline":"ExecuTorch integer overflow vulnerability leads to code execution","id":"CVE-2025-54952","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"PyPI","product":null,"products":[],"type":"integer_overflow","year":"2025"},"n_packages":3,"n_references":2,"next":{"headline":"Race condition in OpenNebula","id":"CVE-2025-54955"},"packages":[{"ecosystem":"PyPI","fixed":[],"introduced":["0"],"last_affected":["0.6.0"],"package":"executorch","purl":null,"source":"GHSA-33r8-vrx9-rmcv"},{"ecosystem":"PyPI","fixed":[],"introduced":["0"],"last_affected":["0.6.0"],"package":"executorch","purl":"pkg:pypi/executorch","source":"GHSA-33r8-vrx9-rmcv"},{"ecosystem":"PyPI","fixed":[],"introduced":["0"],"last_affected":["0.6.0"],"package":"executorch","purl":"pkg:pypi/executorch","source":"PYSEC-2026-1351"}],"prev":{"headline":"ExecuTorch vulnerable to Heap-based Buffer Overflow","id":"CVE-2025-54951"},"products":["ExecuTorch"],"published":"2025-08-07","related":[],"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":"CWE Terms of Use","name":"CWE (MITRE)"},{"class":"attribution","licence":"FIRST CVSS licence","name":"CVSS (FIRST)"}],"ssvc":{"automatable":"yes","exploitation":"none","technical_impact":"total"},"state":"PUBLISHED","updated":"2025-08-08","vendors":["Meta Platforms, Inc"]},"summary":"Integer overflow in ExecuTorch model loading allows attackers to trigger code execution via crafted models.","url":"https://insights.sbomify.com/CVE-2025-54952/"}