CVE-2021-29582

TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in tf.rawops.Dequantize, an attacker can trigger a read from outside of bounds of heap allocated data. The...

CVE-2021-29584

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a CHECK-fail in caused by an integer overflow in constructing a new tensor shape. This is because the...

PT-2021-18328 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow versions 2.4.2 and earlier TensorFlow versions 2.3.3 and earlier TensorFlow versions 2.2.3 and earlier TensorFlow versions 2.1.4 and earlier Description: The implementation of tf.raw...

PT-2021-18272 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow versions 2.4.1 and earlier TensorFlow versions 2.3.2 and earlier Description: Specifying a negative dense shape in tf.raw ops.SparseCountSparseOutput results in a segmentation fault being thrown o...

PT-2021-18316 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow versions 2.4.2 and earlier TensorFlow versions 2.3.3 and earlier TensorFlow versions 2.2.3 and earlier TensorFlow versions 2.1.4 and earlier Description: An attacker can trigger a null pointer...

PT-2021-18335 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow version 2.4.2 TensorFlow version 2.3.3 TensorFlow version 2.2.3 TensorFlow version 2.1.4 Description: An attacker can trigger a denial of service via a CHECK-fail caused by an integer overflow in...

PT-2021-18274 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow version 2.4.2 TensorFlow version 2.3.3 TensorFlow version 2.2.3 TensorFlow version 2.1.4 Description: An attacker can trigger a denial of service via a CHECK-fail in tf.raw...

PT-2021-18319 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow versions 2.4.2 and earlier TensorFlow versions 2.3.3 and earlier TensorFlow versions 2.2.3 and earlier TensorFlow versions 2.1.4 and earlier Description: An attacker can trigger undefined behavior...

PT-2021-18285 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow versions 2.4.2 and earlier TensorFlow versions 2.3.3 and earlier TensorFlow versions 2.2.3 and earlier TensorFlow versions 2.1.4 and earlier Description: An attacker can trigger a denial of servic...

Determining Key Shape from Sound

Its not yet very accurate or practical, but under ideal conditions it is possible to figure out the shape of a house key by listening to it being used. Listen to Your Key: Towards Acoustics-based Physical Key Inference Abstract: Physical locks are one of the most prevalent mechanisms for securing...

Arbitrary Code Execution

tensorlfow is vulnerable to arbitrary code execution. The SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor, allowing an attacker to execute arbitrary code on the host OS by causing a shape mismatch that can result in accesses outside of...

Tensorflow Data Validation Vulnerability

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. A security vulnerability exists in Tensorflow version 2.3.0 that stems from the inability of the SparseCountSparseOutput and RaggedCountSparseOutput implementations to verify that the weights...

PYSEC-2020-274

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the SparseFillEmptyRowsGrad implementation has incomplete validation of the shapes of its arguments. Although reverseindexmapt and gradvaluest are accessed in a similar pattern, only reverseindexmapt is validated to be of proper...

PYSEC-2020-309

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the SparseFillEmptyRowsGrad implementation has incomplete validation of the shapes of its arguments. Although reverseindexmapt and gradvaluest are accessed in a similar pattern, only reverseindexmapt is validated to be of proper...

PYSEC-2020-311

In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights a...

PYSEC-2020-274

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the SparseFillEmptyRowsGrad implementation has incomplete validation of the shapes of its arguments. Although reverseindexmapt and gradvaluest are accessed in a similar pattern, only reverseindexmapt is validated to be of proper...

PYSEC-2020-119

In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights a...

PYSEC-2020-311

In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights a...

PYSEC-2020-313

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed...

PYSEC-2020-119

In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights a...