| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| NVIDIA Megatron Bridge contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure. |
| Unauthenticated PHP Object Injection in Ninja Forms - Layout & Styles <= 3.0.31 versions. |
| DocSys V2.02.80 is vulnerable to Any File Download. An attacker does not need to go through authentication to utilize the downloadDocEx.do interface and download any file via the parameter targetPath. |
| ModelScope uses PyYAML's unsafe yaml.Loader to parse model configuration files, allowing arbitrary code execution through Python object construction tags. Attackers can craft malicious model repositories with poisoned configuration files that execute code when loaded by users. |
| Deserialization of Untrusted Data (CWE-502) in the Elasticsearch machine learning component can lead to remote code execution via Object Injection (CAPEC-586). A specially crafted trained model artifact could cause attacker-controlled logic to execute with a materially broader system-call surface than intended. Exploitation requires an authenticated user with sufficient privileges to create and deploy trained models. |
| Potential for logging sensitive data in Spring Cloud Function AWS.
Spring Cloud Function 5.0.0 - 5.0.3
Spring Cloud Function 4.3.0 - 4.3.4
Spring Cloud Function 4.2.0 - 4.2.7
Spring Cloud Function 3.2.16 and earlier |
| A vulnerability in the Backblaze Client allows a local user to make the system not bootable by creating a link from Backblaze's folder to Windows OS system files during a backup. Successful exploitation requires an administrator-level system change that results in the absence of specific Windows OS security controls. This vulnerability is due to improper link resolution. |
