torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl: 5 vulnerabilities (highest severity is: 9.8)

[mend-bolt-for-github]

Vulnerable Library - torch-1.13.0-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/7a/fb/b1b11ae95ffa7099ca2e60ed5945e56130cc8740208f42aa77f17e03ab3c/torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl

Path to dependency file: /requirements.txt

Path to vulnerable library: /requirements.txt

Found in HEAD commit: 8007902a6bde49bdad6e8694dfa82feb12e3f45c

Vulnerabilities

CVE	Severity	CVSS	Dependency	Type	Fixed in (torch version)	Remediation Possible**
CVE-2024-48063	Critical	9.8	torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl	Direct	torch - 2.5.0	❌
CVE-2022-45907	Critical	9.8	torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl	Direct	torch - 1.13.1	❌
CVE-2024-31584	High	7.5	torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl	Direct	torch - 2.2.0	❌
CVE-2024-31583	High	7.5	torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl	Direct	torch - 2.2.0	❌
CVE-2024-31580	High	7.5	torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl	Direct	torch - 2.2.0	❌

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

Details

CVE-2024-48063

Vulnerable Library - torch-1.13.0-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/7a/fb/b1b11ae95ffa7099ca2e60ed5945e56130cc8740208f42aa77f17e03ab3c/torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl

Path to dependency file: /requirements.txt

Path to vulnerable library: /requirements.txt

Dependency Hierarchy:

• ❌ torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl (Vulnerable Library)

Found in HEAD commit: 8007902a6bde49bdad6e8694dfa82feb12e3f45c

Found in base branch: main

Vulnerability Details

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.

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 Fix

Type: Upgrade version

Origin: https://nvd.nist.gov/vuln/detail/CVE-2024-48063

Release Date: 2024-10-29

Fix Resolution: torch - 2.5.0

Step up your Open Source Security Game with Mend here

CVE-2022-45907

Vulnerable Library - torch-1.13.0-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/7a/fb/b1b11ae95ffa7099ca2e60ed5945e56130cc8740208f42aa77f17e03ab3c/torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl

Path to dependency file: /requirements.txt

Path to vulnerable library: /requirements.txt

Dependency Hierarchy:

• ❌ torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl (Vulnerable Library)

Found in HEAD commit: 8007902a6bde49bdad6e8694dfa82feb12e3f45c

Found in base branch: main

Vulnerability Details

In PyTorch before trunk/89695, torch.jit.annotations.parse_type_line can cause arbitrary code execution because eval is used unsafely.

Publish Date: 2022-11-26

URL: CVE-2022-45907

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 Fix

Type: Upgrade version

Origin: https://www.cve.org/CVERecord?id=CVE-2022-45907

Release Date: 2022-11-26

Fix Resolution: torch - 1.13.1

Step up your Open Source Security Game with Mend here

CVE-2024-31584

Vulnerable Library - torch-1.13.0-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/7a/fb/b1b11ae95ffa7099ca2e60ed5945e56130cc8740208f42aa77f17e03ab3c/torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl

Path to dependency file: /requirements.txt

Path to vulnerable library: /requirements.txt

Dependency Hierarchy:

• ❌ torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl (Vulnerable Library)

Found in HEAD commit: 8007902a6bde49bdad6e8694dfa82feb12e3f45c

Found in base branch: main

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: torch - 2.2.0

Step up your Open Source Security Game with Mend here

CVE-2024-31583

Vulnerable Library - torch-1.13.0-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/7a/fb/b1b11ae95ffa7099ca2e60ed5945e56130cc8740208f42aa77f17e03ab3c/torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl

Path to dependency file: /requirements.txt

Path to vulnerable library: /requirements.txt

Dependency Hierarchy:

• ❌ torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl (Vulnerable Library)

Found in HEAD commit: 8007902a6bde49bdad6e8694dfa82feb12e3f45c

Found in base branch: main

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: torch - 2.2.0

Step up your Open Source Security Game with Mend here

CVE-2024-31580

Vulnerable Library - torch-1.13.0-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/7a/fb/b1b11ae95ffa7099ca2e60ed5945e56130cc8740208f42aa77f17e03ab3c/torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl

Path to dependency file: /requirements.txt

Path to vulnerable library: /requirements.txt

Dependency Hierarchy:

• ❌ torch-1.13.0-cp37-cp37m-manylinux1_x86_64.whl (Vulnerable Library)

Found in HEAD commit: 8007902a6bde49bdad6e8694dfa82feb12e3f45c

Found in base branch: main

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: torch - 2.2.0

Step up your Open Source Security Game with Mend here

[secure-code-warrior-for-github]

Micro-Learning Topic: Vulnerable library (Detected by phrase)

Matched on "Vulnerable Library"

What is this? (2min video)

Use of vulnerable components will introduce weaknesses into the application. Components with published vulnerabilities will allow easy exploitation as resources will often be available to automate the process.

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[secure-code-warrior-for-github]

Micro-Learning Topic: Buffer overflow (Detected by phrase)

Matched on "buffer overflow"

What is this? (2min video)

A buffer overflow condition exists when a program attempts to put more data in a buffer than it can hold or when a program attempts to put data in a memory area past a buffer.

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Micro-Learning Topic: Denial of service (Detected by phrase)

Matched on "Denial of Service"

The Denial of Service (DoS) attack is focused on making a resource (site, application, server) unavailable for the purpose it was designed. There are many ways to make a service unavailable for legitimate users by manipulating network packets, programming, logical, or resources handling vulnerabilities, among others. Source: https://www.owasp.org/index.php/Denial_of_Service

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Micro-Learning Topic: Use-after-free (Detected by phrase)

Matched on "use-after-free"

What is this? (2min video)

Dereferencing pointers to objects that have already been freed opens the door to execution of arbitrary code. Attackers may be able to insert instructions at the freed memory location in order to trigger the exploit when the pointer is used after the memory has been freed.

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