An update for python-Keras is now available for openEuler-24.03-LTS-SP1 Security Advisory openeuler-security@openeuler.org openEuler security committee openEuler-SA-2025-2689 Final 1.0 1.0 2025-11-14 Initial 2025-11-14 2025-11-14 openEuler SA Tool V1.0 2025-11-14 python-Keras security update An update for python-Keras is now available for openEuler-24.03-LTS-SP1 Keras is a high-level neural networks API for Python. Security Fix(es): The Keras.Model.load_model method, including when executed with the intended security mitigation safe_mode=True, is vulnerable to arbitrary local file loading and Server-Side Request Forgery (SSRF). This vulnerability stems from the way the StringLookup layer is handled during model loading from a specially crafted .keras archive. The constructor for the StringLookup layer accepts a vocabulary argument that can specify a local file path or a remote file path. * Arbitrary Local File Read: An attacker can create a malicious .keras file that embeds a local path in the StringLookup layer's configuration. When the model is loaded, Keras will attempt to read the content of the specified local file and incorporate it into the model state (e.g., retrievable via get_vocabulary()), allowing an attacker to read arbitrary local files on the hosting system. * Server-Side Request Forgery (SSRF): Keras utilizes tf.io.gfile for file operations. Since tf.io.gfile supports remote filesystem handlers (such as GCS and HDFS) and HTTP/HTTPS protocols, the same mechanism can be leveraged to fetch content from arbitrary network endpoints on the server's behalf, resulting in an SSRF condition. The security issue is that the feature allowing external path loading was not properly restricted by the safe_mode=True flag, which was intended to prevent such unintended data access.(CVE-2025-12058) An update for python-Keras is now available for openEuler-24.03-LTS-SP1. openEuler Security has rated this update as having a security impact of medium. A Common Vunlnerability Scoring System(CVSS)base score,which gives a detailed severity rating, is available for each vulnerability from the CVElink(s) in the References section. Medium python-Keras https://www.openeuler.org/zh/security/security-bulletins/detail/?id=openEuler-SA-2025-2689 https://www.openeuler.org/en/security/cve/detail/?cveId=CVE-2025-12058 https://nvd.nist.gov/vuln/detail/CVE-2025-12058 openEuler-24.03-LTS-SP1 python-Keras-2.12.0-2.oe2403sp1.src.rpm python-Keras-help-2.12.0-2.oe2403sp1.noarch.rpm python3-Keras-2.12.0-2.oe2403sp1.noarch.rpm The Keras.Model.load_model method, including when executed with the intended security mitigation safe_mode=True, is vulnerable to arbitrary local file loading and Server-Side Request Forgery (SSRF). This vulnerability stems from the way the StringLookup layer is handled during model loading from a specially crafted .keras archive. The constructor for the StringLookup layer accepts a vocabulary argument that can specify a local file path or a remote file path. * Arbitrary Local File Read: An attacker can create a malicious .keras file that embeds a local path in the StringLookup layer's configuration. When the model is loaded, Keras will attempt to read the content of the specified local file and incorporate it into the model state (e.g., retrievable via get_vocabulary()), allowing an attacker to read arbitrary local files on the hosting system. * Server-Side Request Forgery (SSRF): Keras utilizes tf.io.gfile for file operations. Since tf.io.gfile supports remote filesystem handlers (such as GCS and HDFS) and HTTP/HTTPS protocols, the same mechanism can be leveraged to fetch content from arbitrary network endpoints on the server's behalf, resulting in an SSRF condition. The security issue is that the feature allowing external path loading was not properly restricted by the safe_mode=True flag, which was intended to prevent such unintended data access. 2025-11-14 CVE-2025-12058 openEuler-24.03-LTS-SP1 Medium 5.5 AV:N/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L python-Keras security update 2025-11-14 https://www.openeuler.org/zh/security/security-bulletins/detail/?id=openEuler-SA-2025-2689