{"id":"CVE-2026-12480","aliases":["AZL-92027","DEBIAN-CVE-2026-12480","EUVD-2026-41090","GHSA-26c4-7vv6-867j","PYSEC-2026-3629","UBUNTU-CVE-2026-12480"],"status":"published","title":"Arbitrary HDF5 File Read via Virtual Dataset Bypass in keras-team/keras","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.","severity":{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-09","score":0.0019,"percentile":0.08724,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-73"],"published":"2026-07-01T16:53:32Z","modified":"2026-11-05T05:40:51Z","fixes":[{"ecosystem":"PyPI","package":"keras","fixed_in":["3.12.3","3.15.0"],"sources":["ghsa","osv"]},{"ecosystem":"Azure Linux:3","package":"keras","fixed_in":["3.3.3-8"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.12.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"3.13.0"},{"fixed":"3.15.0"}]}]},{"source":"osv","ecosystem":"Azure Linux:3","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.3.3-8"}]}]},{"source":"osv","ecosystem":"Debian:11","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"}]}],"versions":["2.3.1+dfsg-3","2.3.1+dfsg2-1"]},{"source":"osv","ecosystem":"PyPI","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.12.3"}]}],"versions":["0.2.0","0.3.0","0.3.1","0.3.2","0.3.3","1.0.0","1.0.1","1.0.2","1.0.3","1.0.4","1.0.5","1.0.6","1.0.7","1.0.8","1.1.0","1.1.1","1.1.2","1.2.0","1.2.1","1.2.2","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.0.5","2.0.6","2.0.7","2.0.8","2.0.9","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.1.5","2.1.6","2.10.0","2.10.0rc0","2.10.0rc1","2.11.0","2.11.0rc0","2.11.0rc1","2.11.0rc2","2.11.0rc3","2.12.0","2.12.0rc0","2.12.0rc1","2.13.1","2.13.1rc0","2.13.1rc1","2.14.0","2.14.0rc0","2.15.0","2.15.0rc0","2.15.0rc1","2.2.0","2.2.1","2.2.2","2.2.3","2.2.4","2.2.5","2.3.0","2.3.1","2.4.0","2.4.1","2.4.2","2.4.3","2.5.0rc0","2.6.0","2.6.0rc0","2.6.0rc1","2.6.0rc2","2.6.0rc3","2.7.0","2.7.0rc0","2.7.0rc2","2.8.0","2.8.0rc0","2.8.0rc1","2.9.0","2.9.0rc0","2.9.0rc1","2.9.0rc2","3.0.0","3.0.1","3.0.2","3.0.3","3.0.4","3.0.5","3.1.0","3.1.1","3.10.0","3.11.0","3.11.1","3.11.2","3.11.3","3.12.0","3.12.1","3.12.2","3.2.0","3.2.1","3.3.0","3.3.1","3.3.2","3.3.3","3.4.0","3.4.1","3.5.0","3.6.0","3.7.0","3.8.0","3.9.0","3.9.1","3.9.2"]},{"source":"osv","ecosystem":"PyPI","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"3.13.0"},{"fixed":"3.15.0"}]}],"versions":["3.13.0","3.13.1","3.13.2","3.14.0","3.14.1"]},{"source":"osv","ecosystem":"PyPI","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.12.3"},{"introduced":"3.13.0"},{"fixed":"3.15.0"}]}],"versions":["0.2.0","0.3.0","0.3.1","0.3.2","0.3.3","1.0.0","1.0.1","1.0.2","1.0.3","1.0.4","1.0.5","1.0.6","1.0.7","1.0.8","1.1.0","1.1.1","1.1.2","1.2.0","1.2.1","1.2.2","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.0.5","2.0.6","2.0.7","2.0.8","2.0.9","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.1.5","2.1.6","2.10.0","2.10.0rc0","2.10.0rc1","2.11.0","2.11.0rc0","2.11.0rc1","2.11.0rc2","2.11.0rc3","2.12.0","2.12.0rc0","2.12.0rc1","2.13.1","2.13.1rc0","2.13.1rc1","2.14.0","2.14.0rc0","2.15.0","2.15.0rc0","2.15.0rc1","2.2.0","2.2.1","2.2.2","2.2.3","2.2.4","2.2.5","2.3.0","2.3.1","2.4.0","2.4.1","2.4.2","2.4.3","2.5.0rc0","2.6.0","2.6.0rc0","2.6.0rc1","2.6.0rc2","2.6.0rc3","2.7.0","2.7.0rc0","2.7.0rc2","2.8.0","2.8.0rc0","2.8.0rc1","2.9.0","2.9.0rc0","2.9.0rc1","2.9.0rc2","3.0.0","3.0.1","3.0.2","3.0.3","3.0.4","3.0.5","3.1.0","3.1.1","3.10.0","3.11.0","3.11.1","3.11.2","3.11.3","3.12.0","3.12.1","3.12.2","3.13.0","3.13.1","3.13.2","3.14.0","3.14.1","3.2.0","3.2.1","3.3.0","3.3.1","3.3.2","3.3.3","3.4.0","3.4.1","3.5.0","3.6.0","3.7.0","3.8.0","3.9.0","3.9.1","3.9.2"]},{"source":"osv","ecosystem":"Ubuntu:18.04:LTS","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"}]}],"versions":["1.0.7-2","2.1.1-1"]},{"source":"osv","ecosystem":"Ubuntu:20.04:LTS","package":"keras","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"}]}],"versions":["2.2.4-1"]}],"products":[{"vendor":"keras-team","product":"keras-team/keras"}],"references":[{"url":"https://huntr.com/bounties/1875d257-5b03-4a69-ac70-e98653fa12c7","tags":["exploit","web","report"]},{"url":"https://github.com/keras-team/keras/commit/d5a88bdb137c0d3039b8f4bbbe8c7099925cc10c","tags":["fix","web","report"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2026-12480","tags":["web","advisory"]},{"url":"https://github.com/keras-team/keras/commit/8f987f11bf7512f0df4774a8f1557bba07dc2b49","tags":["web"]},{"url":"https://github.com/keras-team/keras/releases/tag/v3.12.3","tags":["web"]},{"url":"https://github.com/keras-team/keras/releases/tag/v3.15.0","tags":["web"]},{"url":"https://github.com/advisories/GHSA-26c4-7vv6-867j","tags":["advisory"]},{"url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/12xxx/CVE-2026-12480.json","tags":["advisory"]},{"url":"https://security-tracker.debian.org/tracker/CVE-2026-12480","tags":["advisory"]},{"url":"https://github.com/keras-team/keras","tags":["package"]},{"url":"https://pypi.org/project/keras","tags":["package"]},{"url":"https://ubuntu.com/security/CVE-2026-12480","tags":["report"]},{"url":"https://www.cve.org/CVERecord?id=CVE-2026-12480","tags":["report"]}],"sources":{"cve":[{"id":"CVE-2026-12480","title":"Arbitrary HDF5 File Read via Virtual Dataset Bypass in keras-team/keras","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.","status":"published","published":"2026-07-01T16:53:32.326Z","modified":"2026-07-01T17:46:31.093Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium","assessor":"cna"}],"cwes":["CWE-73"],"updated_at":"2026-11-02T14:19:47.998488Z"}],"euvd":[{"id":"EUVD-2026-41090","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.","status":"published","published":"2026-07-01T16:53:32Z","modified":"2026-07-01T17:46:31Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium"}],"updated_at":"2026-11-02T18:20:19.066641Z"}],"ghsa":[{"id":"GHSA-26c4-7vv6-867j","title":"Keras: HDF5 virtual datasets can disclose local files","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.3 and 3.15.0.","status":"published","published":"2026-07-01T18:31:51Z","modified":"2026-08-07T20:28:59Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium"}],"cwes":["CWE-73"],"updated_at":"2026-11-02T14:40:58.888637Z"}],"nvd":[{"id":"CVE-2026-12480","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.","status":"published","published":"2026-07-01T17:16:19.33Z","modified":"2026-10-25T17:10:00.197Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium","assessor":"secondary"}],"cwes":["CWE-73"],"updated_at":"2026-11-02T14:12:27.199837Z"}],"osv":[{"id":"CVE-2026-12480","title":"Arbitrary HDF5 File Read via Virtual Dataset Bypass in keras-team/keras","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.","status":"published","published":"2026-07-01T16:53:32.326Z","modified":"2026-10-28T02:31:08.757837249Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium"}],"cwes":["CWE-73"],"updated_at":"2026-11-02T15:44:57.354194Z"},{"id":"DEBIAN-CVE-2026-12480","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.","status":"published","published":"2026-07-01T17:16:19.33Z","modified":"2026-08-27T23:05:49.786119112Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium"}],"updated_at":"2026-11-02T15:45:51.374409Z"},{"id":"GHSA-26c4-7vv6-867j","title":"Keras: HDF5 virtual datasets can disclose local files","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.3 and 3.15.0.","status":"published","published":"2026-07-01T18:31:51Z","modified":"2026-08-10T11:40:53.891931306Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium"}],"cwes":["CWE-73"],"updated_at":"2026-11-02T15:46:33.956911Z"},{"id":"PYSEC-2026-3629","title":"Keras: HDF5 virtual datasets can disclose local files","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.3 and 3.15.0.","status":"published","published":"2026-08-10T10:43:49.083911Z","modified":"2026-08-10T11:30:13.122559743Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium"}],"updated_at":"2026-11-02T15:52:56.847083Z"},{"id":"UBUNTU-CVE-2026-12480","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.","status":"published","published":"2026-07-01T17:16:00Z","modified":"2026-07-09T15:15:45Z","cvss":[{"version":"3.0","score":5.5,"vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N","level":"medium"}],"updated_at":"2026-11-02T16:56:00.592716Z"},{"id":"AZL-92027","title":"CVE-2026-12480 affecting package keras for versions less than 3.3.3-8","description":"Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.","status":"published","published":"2026-07-01T17:16:19Z","modified":"2026-11-05T05:40:51Z","updated_at":"2026-11-05T16:41:25.633663Z"}]}}