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Morpheus SDK
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torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl: 3 vulnerabilities (highest severity is: 7.5) #25

Open mend-bolt-for-github[bot] opened 5 months ago

mend-bolt-for-github[bot] commented 5 months ago
Vulnerable Library - torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl

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: /models/validation-inference-scripts/dfp-models/requirements.txt

Path to vulnerable library: /models/validation-inference-scripts/dfp-models/requirements.txt,/models/validation-inference-scripts/dfp-models/requirements.txt

Found in HEAD commit: 42a2d393427e16f1b80a5df9fe14a37d045088ad

Vulnerabilities

CVE Severity CVSS Dependency Type Fixed in (torch version) Remediation Possible**
CVE-2024-31584 High 7.5 torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl Direct 2.2.0 ❌
CVE-2024-31583 High 7.5 torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl Direct 2.2.0 ❌
CVE-2024-31580 High 7.5 torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl Direct 2.2.0 ❌

**In some cases, Remediation PR cannot be created automatically for a vulnerability despite the availability of remediation

Details

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

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: /models/validation-inference-scripts/dfp-models/requirements.txt

Path to vulnerable library: /models/validation-inference-scripts/dfp-models/requirements.txt,/models/validation-inference-scripts/dfp-models/requirements.txt

Dependency Hierarchy: - :x: **torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl** (Vulnerable Library)

Found in HEAD commit: 42a2d393427e16f1b80a5df9fe14a37d045088ad

Found in base branch: branch-23.03

### Vulnerability Details

Pytorch 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 Fix

Type: 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.whl

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: /models/validation-inference-scripts/dfp-models/requirements.txt

Path to vulnerable library: /models/validation-inference-scripts/dfp-models/requirements.txt,/models/validation-inference-scripts/dfp-models/requirements.txt

Dependency Hierarchy: - :x: **torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl** (Vulnerable Library)

Found in HEAD commit: 42a2d393427e16f1b80a5df9fe14a37d045088ad

Found in base branch: branch-23.03

### Vulnerability Details

Pytorch 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 Fix

Type: 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.whl

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: /models/validation-inference-scripts/dfp-models/requirements.txt

Path to vulnerable library: /models/validation-inference-scripts/dfp-models/requirements.txt,/models/validation-inference-scripts/dfp-models/requirements.txt

Dependency Hierarchy: - :x: **torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl** (Vulnerable Library)

Found in HEAD commit: 42a2d393427e16f1b80a5df9fe14a37d045088ad

Found in base branch: branch-23.03

### Vulnerability Details

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.

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 Fix

Type: 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)