{"answers":{"affected":"3 open source packages ship an affected version, including mlx. It affects 1 product.","exploited":"It is not confirmed as exploited in the wild, but public exploit code for CVE-2025-62608 exists.","fix":"Upgrade mlx to 0.29.4 or later.","what":"CVE-2025-62608 is a medium-severity memory corruption vulnerability in ml-explore mlx, published on 21 Nov 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-2025-62608 and fix it if it is affected.\n\nWhat it is: CVE-2025-62608 is a medium-severity memory corruption vulnerability in ml-explore mlx, published on 21 Nov 2025. 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-2025-62608 exists.\n\nAffected packages and fixed versions:\n- mlx (PyPI): affected all versions; fixed in 0.29.4\n- mlx (PyPI): affected all versions; fixed in 0.29.4\n- mlx (PyPI): affected all versions; fixed in 0.29.4\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-2025-62608/ (Markdown: https://insights.sbomify.com/CVE-2025-62608/index.md)","id":"CVE-2025-62608","markdown":"https://insights.sbomify.com/CVE-2025-62608/index.md","name":"CVE-2025-62608","record":{"aliases":["GHSA-w6vg-jg77-2qg6","PYSEC-2025-138"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["denial_of_service","data_read"],"network_reachable":"yes","non_default_config":false,"product_category":"MLX machine learning library","requires_auth":"none","summary":"A heap buffer overflow in MLX allows attackers to cause crashes or disclose information via malicious NumPy files.","user_interaction":"not_required","vuln_class":"memory_corruption"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"GitHub_M","cpe":[{"product":"mlx","vendor":"ml-explore"}],"cvss":{"score":5.5,"severity":"medium","source":"cna","vector":"CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:L/SC:N/SI:N/SA:N/E:P","version":"4.0"},"cwes":[{"id":"CWE-122","name":"Heap-based Buffer Overflow"}],"description":"MLX is an array framework for machine learning on Apple silicon. Prior to version 0.29.4, there is a heap buffer overflow in mlx::core::load() when parsing malicious NumPy .npy files. Attacker-controlled file causes 13-byte out-of-bounds read, leading to crash or information disclosure. This issue has been patched in version 0.29.4.","ecosystems":["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":"MLX has heap-buffer-overflow in load()","id":"CVE-2025-62608","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"PyPI","product":null,"products":[],"type":"memory_corruption","year":"2025"},"n_packages":3,"n_references":3,"next":{"headline":"MLX has Wild Pointer Dereference in load_gguf()","id":"CVE-2025-62609"},"packages":[{"ecosystem":"PyPI","fixed":["0.29.4"],"introduced":["0"],"last_affected":[],"package":"mlx","purl":null,"source":"GHSA-w6vg-jg77-2qg6"},{"ecosystem":"PyPI","fixed":["0.29.4"],"introduced":["0"],"last_affected":[],"package":"mlx","purl":"pkg:pypi/mlx","source":"GHSA-w6vg-jg77-2qg6"},{"ecosystem":"PyPI","fixed":["0.29.4"],"introduced":["0"],"last_affected":[],"package":"mlx","purl":"pkg:pypi/mlx","source":"PYSEC-2025-138"}],"prev":{"headline":"Nautobot Single Source of Truth (SSoT) has an unauthenticated ServiceNow configuration URL","id":"CVE-2025-62607"},"products":["mlx"],"published":"2025-11-21","related":[{"cvss_score":5.5,"headline":"MLX has Wild Pointer Dereference in load_gguf()","id":"CVE-2025-62609","kev_date_added":null,"published":"2025-11-21"}],"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":"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":"yes","exploitation":"poc","technical_impact":"partial"},"state":"PUBLISHED","updated":"2025-11-21","vendors":["ml-explore"]},"summary":"A heap buffer overflow in MLX allows attackers to cause crashes or disclose information via malicious NumPy files.","url":"https://insights.sbomify.com/CVE-2025-62608/"}