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torch@1.8.1 vulnerabilities

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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Direct Vulnerabilities

Known vulnerabilities in the torch package. This does not include vulnerabilities belonging to this package’s dependencies.

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Vulnerability Vulnerable Version
  • H
Heap-based Buffer Overflow

torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration

Affected versions of this package are vulnerable to Heap-based Buffer Overflow in the /runtime/vararg_functions.cpp component. An attacker can cause a crash or potentially execute arbitrary code by supplying crafted input.

How to fix Heap-based Buffer Overflow?

Upgrade torch to version 2.2.0 or higher.

[,2.2.0)
  • H
Use After Free

torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration

Affected versions of this package are vulnerable to Use After Free due to improper handling of memory in the interpreter.cpp component. An attacker can execute arbitrary code or cause a denial of service.

How to fix Use After Free?

Upgrade torch to version 2.2.0 or higher.

[,2.2.0)
  • M
Race Condition

torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration

Affected versions of this package are vulnerable to Race Condition in the database management. This occurred due to concurrent access to shared resources without adequate synchronization, causing unpredictable system behavior.

How to fix Race Condition?

Upgrade torch to version 1.13.0 or higher.

[,1.13.0)
  • M
Race Condition

torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration

Affected versions of this package are vulnerable to Race Condition in the torch.jit.annotations.parse_type_line function. This allowes simultaneous reading and writing the set of devices without synchronizing.

How to fix Race Condition?

Upgrade torch to version 1.10.0 or higher.

[,1.10.0)
  • C
Command Injection

torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration

Affected versions of this package are vulnerable to Command Injection in torch.jit.annotations.parse_type_line which can cause arbitrary code execution because eval is used unsafely.

How to fix Command Injection?

Upgrade torch to version 1.13.1 or higher.

[0,1.13.1)
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