CVE-2026-12570

{"id": "CVE-2026-12570", "cveTags": [], "metrics": {"ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2026-12570", "role": "CISA Coordinator", "options": [{"exploitation": "poc"}, {"automatable": "no"}, {"technicalImpact": "partial"}], "version": "2.0.3", "timestamp": "2026-08-10T17:37:17.637683Z"}}], "cvssMetricV30": [{"type": "Secondary", "source": "security@huntr.dev", "cvssData": {"scope": "UNCHANGED", "version": "3.0", "baseScore": 5.5, "attackVector": "LOCAL", "baseSeverity": "MEDIUM", "vectorString": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H", "integrityImpact": "NONE", "userInteraction": "REQUIRED", "attackComplexity": "LOW", "availabilityImpact": "HIGH", "privilegesRequired": "NONE", "confidentialityImpact": "NONE"}, "impactScore": 3.6, "exploitabilityScore": 1.8}]}, "affected": [{"source": "security@huntr.dev", "affectedData": [{"vendor": "keras-team", "product": "keras-team/keras", "versions": [{"status": "affected", "version": "unspecified", "lessThan": "3.12.3, 3.15.0", "versionType": "custom"}]}]}], "published": "2026-08-10T07:16:44.370", "references": [{"url": "https://github.com/keras-team/keras/commit/4933ea4a5b3fcc24ceacdc276f5bb5dfbd06756c", "source": "security@huntr.dev"}, {"url": "https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8", "source": "security@huntr.dev"}, {"url": "https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8", "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"}], "vulnStatus": "Awaiting Analysis", "weaknesses": [{"type": "Secondary", "source": "security@huntr.dev", "description": [{"lang": "en", "value": "CWE-770"}]}], "descriptions": [{"lang": "en", "value": "A vulnerability in keras-team/keras versions <= 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models."}, {"lang": "es", "value": "Una vulnerabilidad en las versiones menor o igual que 3.15.0 de keras-team/keras permite un ataque de denegaci\u00f3n de servicio (DoS) al cargar archivos de modelo .keras maliciosos a trav\u00e9s de la funci\u00f3n keras.models.load_model(). El m\u00e9todo H5IOStore.__getitem__ en keras/src/saving/saving_lib.py no valida la forma o el tama\u00f1o de los conjuntos de datos, lo que lleva a una asignaci\u00f3n de memoria ilimitada. Un archivo .keras especialmente dise\u00f1ado puede explotar esta falla para desencadenar una condici\u00f3n de falta de memoria (OOM), lo que provoca la terminaci\u00f3n del proceso (c\u00f3digo de salida 137). Este problema elude la correcci\u00f3n para CVE-2026-0897, que solo abord\u00f3 una vulnerabilidad similar en KerasFileEditor. El vector de ataque incluye modelos envenenados de repositorios p\u00fablicos o registros de modelos maliciosos, lo que representa un riesgo para las tuber\u00edas de aprendizaje autom\u00e1tico que procesan modelos no confiables."}], "lastModified": "2026-10-23T20:10:00.160", "sourceIdentifier": "security@huntr.dev"}