In PyTorch <=2.4.1, the RemoteModule has Deserialization RCE. NOTE: this is disputed by multiple parties because this is intended behavior in PyTorch distributed computing.
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)
CVE-2024-31584
### Vulnerable Library - torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)
CVE-2024-31583
### Vulnerable Library - torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)
CVE-2024-31580
### Vulnerable Library - torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
PyTorch before v2.2.0 was discovered to contain a heap buffer overflow vulnerability in the component /runtime/vararg_functions.cpp. This vulnerability allows attackers to cause a Denial of Service (DoS) via a crafted input.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/00/86/77a9eddbf46f1bca2468d16a401911f58917f95b63402d6a7a4522521e5d/torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl
Path to dependency file: /requirements.txt
Path to vulnerable library: /requirements.txt
Found in HEAD commit: 46b2b180777accd8b00c59f7f7b3dae4eeecfed2
Vulnerabilities
**In some cases, Remediation PR cannot be created automatically for a vulnerability despite the availability of remediation
Details
CVE-2024-48063
### Vulnerable Library - torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whlTensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/00/86/77a9eddbf46f1bca2468d16a401911f58917f95b63402d6a7a4522521e5d/torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl
Path to dependency file: /requirements.txt
Path to vulnerable library: /requirements.txt
Dependency Hierarchy: - :x: **torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl** (Vulnerable Library)
Found in HEAD commit: 46b2b180777accd8b00c59f7f7b3dae4eeecfed2
Found in base branch: main
### Vulnerability DetailsIn PyTorch <=2.4.1, the RemoteModule has Deserialization RCE. NOTE: this is disputed by multiple parties because this is intended behavior in PyTorch distributed computing.
Publish Date: 2024-10-29
URL: CVE-2024-48063
### CVSS 3 Score Details (9.8)Base Score Metrics: - Exploitability Metrics: - Attack Vector: Network - Attack Complexity: Low - Privileges Required: None - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: High - Integrity Impact: High - Availability Impact: High
For more information on CVSS3 Scores, click here. ### Suggested FixType: Upgrade version
Origin: https://nvd.nist.gov/vuln/detail/CVE-2024-48063
Release Date: 2024-10-29
Fix Resolution: 2.5.0
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)
CVE-2024-31584
### Vulnerable Library - torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whlTensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/00/86/77a9eddbf46f1bca2468d16a401911f58917f95b63402d6a7a4522521e5d/torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl
Path to dependency file: /requirements.txt
Path to vulnerable library: /requirements.txt
Dependency Hierarchy: - :x: **torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl** (Vulnerable Library)
Found in HEAD commit: 46b2b180777accd8b00c59f7f7b3dae4eeecfed2
Found in base branch: main
### Vulnerability DetailsPytorch before v2.2.0 has an Out-of-bounds Read vulnerability via the component torch/csrc/jit/mobile/flatbuffer_loader.cpp.
Publish Date: 2024-04-19
URL: CVE-2024-31584
### CVSS 3 Score Details (7.5)Base Score Metrics: - Exploitability Metrics: - Attack Vector: Network - Attack Complexity: Low - Privileges Required: None - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: None - Integrity Impact: None - Availability Impact: High
For more information on CVSS3 Scores, click here. ### Suggested FixType: Upgrade version
Origin: https://www.cve.org/CVERecord?id=CVE-2024-31584
Release Date: 2024-04-19
Fix Resolution: 2.2.0
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)
CVE-2024-31583
### Vulnerable Library - torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whlTensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/00/86/77a9eddbf46f1bca2468d16a401911f58917f95b63402d6a7a4522521e5d/torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl
Path to dependency file: /requirements.txt
Path to vulnerable library: /requirements.txt
Dependency Hierarchy: - :x: **torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl** (Vulnerable Library)
Found in HEAD commit: 46b2b180777accd8b00c59f7f7b3dae4eeecfed2
Found in base branch: main
### Vulnerability DetailsPytorch before version v2.2.0 was discovered to contain a use-after-free vulnerability in torch/csrc/jit/mobile/interpreter.cpp.
Publish Date: 2024-04-17
URL: CVE-2024-31583
### CVSS 3 Score Details (7.5)Base Score Metrics: - Exploitability Metrics: - Attack Vector: Network - Attack Complexity: Low - Privileges Required: None - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: None - Integrity Impact: None - Availability Impact: High
For more information on CVSS3 Scores, click here. ### Suggested FixType: Upgrade version
Origin: https://www.cve.org/CVERecord?id=CVE-2024-31583
Release Date: 2024-04-17
Fix Resolution: 2.2.0
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)
CVE-2024-31580
### Vulnerable Library - torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whlTensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/00/86/77a9eddbf46f1bca2468d16a401911f58917f95b63402d6a7a4522521e5d/torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl
Path to dependency file: /requirements.txt
Path to vulnerable library: /requirements.txt
Dependency Hierarchy: - :x: **torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl** (Vulnerable Library)
Found in HEAD commit: 46b2b180777accd8b00c59f7f7b3dae4eeecfed2
Found in base branch: main
### Vulnerability DetailsPyTorch before v2.2.0 was discovered to contain a heap buffer overflow vulnerability in the component /runtime/vararg_functions.cpp. This vulnerability allows attackers to cause a Denial of Service (DoS) via a crafted input.
Publish Date: 2024-04-17
URL: CVE-2024-31580
### CVSS 3 Score Details (7.5)Base Score Metrics: - Exploitability Metrics: - Attack Vector: Network - Attack Complexity: Low - Privileges Required: None - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: None - Integrity Impact: None - Availability Impact: High
For more information on CVSS3 Scores, click here. ### Suggested FixType: Upgrade version
Origin: https://www.cve.org/CVERecord?id=CVE-2024-31580
Release Date: 2024-04-17
Fix Resolution: 2.2.0
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)