Threats Tagged 'cve-2026-58659'

Red Hat® Enterprise Linux® AI is a foundation model platform to seamlessly develop, test, and run Granite family large language models (LLMs) for enterprise applications. This update provides the latest Red Hat Enterprise Linux AI 3.4.1 container disk images for use with OpenShift Virtualization. For a full list of changes in this release, see the Red Hat Enterprise Linux AI Release Notes linked in the References section.

Red Hat® AI Inference Server

Red Hat AI Inference Server 3.4.5 (spyre) has a security advisory issued by Red Hat Product Security covering multiple CVEs including CVE-2026-5241. The advisory lists a high severity level but does not provide specific patch or fix information. The product is Red Hat AI Inference Server, and the advisory references multiple CVEs affecting this product. No known exploits in the wild are reported at this time.

Red Hat AI Inference Server 3.4.5 (cuda) has been identified with multiple security vulnerabilities, including CVE-2026-5241. The Red Hat advisory confirms the release of version 3.4.5 but does not list any fixes for these vulnerabilities. The advisory provides references and contact information but does not specify remediation steps or patches. The vulnerabilities are considered high severity based on the advisory classification.

Red Hat AI Inference Server 3.4.5 (cpu) has a security advisory issued by Red Hat Product Security addressing multiple vulnerabilities including CVE-2026-5241. The advisory lists numerous CVEs affecting the product but does not provide specific technical details or patches. No fixes are currently available as per the vendor advisory.

PyTorch Lightning through 2.6.5, fixed in commit d710d68, contains a remote code execution vulnerability in the _load_state function that imports and executes attacker-controlled module names from checkpoint _instantiator hyperparameters. Attackers can craft malicious checkpoint files that bypass weights_only=True protections to execute arbitrary code when LightningModule.load_from_checkpoint is called.