torch@1.3.1 vulnerabilities

Tensors and Dynamic neural networks in Python with strong GPU acceleration

latest version

2.6.0

first published

6 years ago

latest version published

2 months ago

licenses detected

BSD-3-Clause
[0,)

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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
M Improper Check for Unusual or Exceptional Conditions torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration Affected versions of this package are vulnerable to Improper Check for Unusual or Exceptional Conditions in the `ctc_loss()` function in `LossCTC.cpp`, when running on a CUDA system. An attacker can cause the application to crash by passing in input with empty tensors. How to fix Improper Check for Unusual or Exceptional Conditions? A fix was pushed into the `master` branch but not yet published.	[0,)
M Improper Resource Shutdown or Release torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration Affected versions of this package are vulnerable to Improper Resource Shutdown or Release via the `torch.mkldnn_max_pool2d` function. An attacker can disrupt service by exploiting this vulnerability locally and causing a `Floating point exception` crash. How to fix Improper Resource Shutdown or Release? There is no fixed version for `torch`.	[0,)
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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