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Recent Vulnerabilities

• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34445 • published on April 1, 2026 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
• CVE-2026-34397 • published on April 1, 2026 Himmelblau is an interoperability suite for Microsoft Azure Entra ID and Intune. From versions 2.0.0-alpha to before 2.3.9 and 3.0.0-alpha to before 3.1.1, there is a conditional local privilege escalation vulnerability in an edge-case naming collision. Only authenticated himmelblau users whose mapped CN/short name exactly matches a privileged local group name (e.g., "sudo", "wheel", "docker", "adm") can cause the NSS module to resolve that group name to their fake primary group. If the system uses NSS results for group-based authorization decisions (sudo, polkit, etc.), this can grant the attacker the privileges of that group. This issue has been patched in versions 2.3.9 and 3.1.1.
• CVE-2026-34397 • published on April 1, 2026 Himmelblau is an interoperability suite for Microsoft Azure Entra ID and Intune. From versions 2.0.0-alpha to before 2.3.9 and 3.0.0-alpha to before 3.1.1, there is a conditional local privilege escalation vulnerability in an edge-case naming collision. Only authenticated himmelblau users whose mapped CN/short name exactly matches a privileged local group name (e.g., "sudo", "wheel", "docker", "adm") can cause the NSS module to resolve that group name to their fake primary group. If the system uses NSS results for group-based authorization decisions (sudo, polkit, etc.), this can grant the attacker the privileges of that group. This issue has been patched in versions 2.3.9 and 3.1.1.
• CVE-2026-34397 • published on April 1, 2026 Himmelblau is an interoperability suite for Microsoft Azure Entra ID and Intune. From versions 2.0.0-alpha to before 2.3.9 and 3.0.0-alpha to before 3.1.1, there is a conditional local privilege escalation vulnerability in an edge-case naming collision. Only authenticated himmelblau users whose mapped CN/short name exactly matches a privileged local group name (e.g., "sudo", "wheel", "docker", "adm") can cause the NSS module to resolve that group name to their fake primary group. If the system uses NSS results for group-based authorization decisions (sudo, polkit, etc.), this can grant the attacker the privileges of that group. This issue has been patched in versions 2.3.9 and 3.1.1.
• CVE-2026-34397 • published on April 1, 2026 Himmelblau is an interoperability suite for Microsoft Azure Entra ID and Intune. From versions 2.0.0-alpha to before 2.3.9 and 3.0.0-alpha to before 3.1.1, there is a conditional local privilege escalation vulnerability in an edge-case naming collision. Only authenticated himmelblau users whose mapped CN/short name exactly matches a privileged local group name (e.g., "sudo", "wheel", "docker", "adm") can cause the NSS module to resolve that group name to their fake primary group. If the system uses NSS results for group-based authorization decisions (sudo, polkit, etc.), this can grant the attacker the privileges of that group. This issue has been patched in versions 2.3.9 and 3.1.1.
• CVE-2026-34397 • published on April 1, 2026 Himmelblau is an interoperability suite for Microsoft Azure Entra ID and Intune. From versions 2.0.0-alpha to before 2.3.9 and 3.0.0-alpha to before 3.1.1, there is a conditional local privilege escalation vulnerability in an edge-case naming collision. Only authenticated himmelblau users whose mapped CN/short name exactly matches a privileged local group name (e.g., "sudo", "wheel", "docker", "adm") can cause the NSS module to resolve that group name to their fake primary group. If the system uses NSS results for group-based authorization decisions (sudo, polkit, etc.), this can grant the attacker the privileges of that group. This issue has been patched in versions 2.3.9 and 3.1.1.
• CVE-2026-34397 • published on April 1, 2026 Himmelblau is an interoperability suite for Microsoft Azure Entra ID and Intune. From versions 2.0.0-alpha to before 2.3.9 and 3.0.0-alpha to before 3.1.1, there is a conditional local privilege escalation vulnerability in an edge-case naming collision. Only authenticated himmelblau users whose mapped CN/short name exactly matches a privileged local group name (e.g., "sudo", "wheel", "docker", "adm") can cause the NSS module to resolve that group name to their fake primary group. If the system uses NSS results for group-based authorization decisions (sudo, polkit, etc.), this can grant the attacker the privileges of that group. This issue has been patched in versions 2.3.9 and 3.1.1.
• CVE-2026-34397 • published on April 1, 2026 Himmelblau is an interoperability suite for Microsoft Azure Entra ID and Intune. From versions 2.0.0-alpha to before 2.3.9 and 3.0.0-alpha to before 3.1.1, there is a conditional local privilege escalation vulnerability in an edge-case naming collision. Only authenticated himmelblau users whose mapped CN/short name exactly matches a privileged local group name (e.g., "sudo", "wheel", "docker", "adm") can cause the NSS module to resolve that group name to their fake primary group. If the system uses NSS results for group-based authorization decisions (sudo, polkit, etc.), this can grant the attacker the privileges of that group. This issue has been patched in versions 2.3.9 and 3.1.1.
• CVE-2026-34397 • published on April 1, 2026 Himmelblau is an interoperability suite for Microsoft Azure Entra ID and Intune. From versions 2.0.0-alpha to before 2.3.9 and 3.0.0-alpha to before 3.1.1, there is a conditional local privilege escalation vulnerability in an edge-case naming collision. Only authenticated himmelblau users whose mapped CN/short name exactly matches a privileged local group name (e.g., "sudo", "wheel", "docker", "adm") can cause the NSS module to resolve that group name to their fake primary group. If the system uses NSS results for group-based authorization decisions (sudo, polkit, etc.), this can grant the attacker the privileges of that group. This issue has been patched in versions 2.3.9 and 3.1.1.