Vendor
TensorFlow
403 known vulnerabilities.
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Critical 9.8CVE-2024-3660 Public exploit
Arbitrary code injection vulnerability in Keras framework < 2.13
A arbitrary code injection vulnerability in TensorFlow's Keras framework (<2.13) allows attackers to execute arbitrary code with the same permissions as the application using a model that allow arbitrary code irrespective of the application.
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Critical 9.8
TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation
TensorFlow is an open source platform for machine learning. Attackers using Tensorflow prior to 2.12.0 or 2.11.1 can access heap memory which is not in the control of user, leading to a crash or remote code execution. The fix will be included in TensorFlow ve…
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Critical 9.3CVE-2021-37678 Public exploit
Arbitrary code execution due to YAML deserialization
TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tens…
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Critical 9.1
Heap out of bounds read in filesystem glob matching in TensorFlow
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that…
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Critical 9.0
Integer truncation in Shard API usage
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taki…
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Critical 9.0
Data leak in Tensorflow
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked…
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Critical 9.0
Denial of Service in Tensorflow
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of ser…