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NVIDIA disclosed two high-severity deserialization vulnerabilities affecting BioNeMo and the FLARE SDK, both tracked under CWE-502 and capable of compromising confidentiality, integrity, and availability. CVE-2026-24164 impacts BioNeMo and could allow code execution, denial of service, information disclosure, and data tampering through deserialization of untrusted data. The flaw carries a CVSS:3.1 vector of AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H, indicating remote attack potential with low complexity and high impact.
A second flaw, CVE-2026-24186, affects the NVIDIA FLARE SDK in FOBS handling, where a malicious FOBS-encoded message can trigger unsafe deserialization and lead to code execution. That issue was scored CVSS:3.1 AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H, reflecting similarly severe impact with no user interaction required. NVIDIA advisory material, NVD entries, and official CVE records were published for both vulnerabilities, signaling that organizations using either platform should review vendor guidance and prioritize remediation.
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2 events from the most recent confirmed update back to the earliest known activity.
A deserialization vulnerability in the NVIDIA FLARE SDK's FOBS component was disclosed as CVE-2026-24186. NVIDIA indicated that a malicious FOBS-encoded message could trigger the flaw and lead to code execution, with references added to NVD, NVIDIA's advisory, and the CVE record.
A deserialization of untrusted data vulnerability in NVIDIA BioNeMo was reported and assigned CVE-2026-24164. The flaw could enable code execution, denial of service, information disclosure, and data tampering, and references were added to NVD, NVIDIA's advisory, and the CVE record.
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Multiple high-severity deserialization vulnerabilities have been identified in widely used AI and analytics frameworks, including NVIDIA Isaac Lab, MooreThreads torch_musa, and NVIDIA Merlin components. These flaws allow attackers to exploit unsafe deserialization processes, potentially leading to remote code execution or denial-of-service conditions on affected systems. In the case of MooreThreads torch_musa, the vulnerability arises from the use of `pickle.load()` on user-controlled files without validation, enabling arbitrary code execution with the privileges of the victim process. Similarly, NVIDIA Isaac Lab and Merlin frameworks are affected by deserialization issues that could be exploited remotely, with Merlin's NVTabular and Transformers4Rec components specifically highlighted for their susceptibility to code execution and data tampering attacks. Security advisories urge immediate patching, as these vulnerabilities are remotely exploitable and pose significant risks to enterprise environments. The affected products span various versions, and organizations using these frameworks are advised to review vendor guidance and apply available security updates to mitigate the threat. The vulnerabilities have been assigned high or critical CVSS scores, underscoring the urgency for remediation to prevent potential exploitation in production environments.
Jun 29, 2026
A critical deserialization vulnerability (CVE-2025-32210) was discovered in NVIDIA Isaac Lab, a component of the NVIDIA Isaac Sim framework, allowing attackers with low privileges and minimal user interaction to execute arbitrary code on affected systems. The flaw, categorized as CWE-502, affects all versions of Isaac Lab prior to v2.3.0 and carries a CVSS score of 9.0, indicating a high risk to confidentiality, integrity, and availability. NVIDIA responded by releasing a security update that implements proper input validation and secure data handling, urging all users to upgrade to Isaac Lab v2.3.0 immediately to mitigate the risk of exploitation. The vulnerability also prompted broader advisories regarding critical security patches for NVIDIA's AI platforms, including both Isaac Lab and the NeMo Framework, due to the risk of full code execution if left unpatched. Organizations using these AI tools are strongly advised to verify their deployments and apply the latest security updates across all environments. The urgency of the patch is underscored by the potential for attackers to achieve complete system compromise through network-based attacks requiring only low-level access and user interaction.
Jun 29, 2026
NVIDIA disclosed **CVE-2026-24233**, a high-severity vulnerability in **TensorRT-LLM for Linux** caused by insecure deserialization in the product’s restricted unpickler for model weight loading. The flaw affects versions **up to and including `v1.3.0 rc14`** and allows a **local, unauthenticated attacker** to trigger deserialization of untrusted data, potentially leading to **remote code execution, privilege escalation, data tampering, and information disclosure**. The issue carries a **CVSS v3.1 score of 8.4** with vector `AV:L/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H`. The vulnerability is classified as **`CWE-502: Deserialization of Untrusted Data`**, a weakness that arises when software processes attacker-controlled serialized input without sufficient validation. MITRE notes that such flaws can let attackers abuse gadget chains or unsafe object handling to alter program state, cause denial of service, or execute arbitrary code, and recommends mitigations including integrity protection for serialized data, strict allowlisting of acceptable classes, reducing available gadget types, and defensive coding patterns that block unsafe deserialization paths.
Jul 15, 2026