PYSEC-2020-117

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-2020-293

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor,...

PYSEC-2020-321

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 service in products using tensorflow-servin...

PYSEC-2020-115

In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to dlpack.todlpack there is a memory leak following an expected validation failure. The issue occurs because the status argument during validation failures is not properly checked. Since each of the above methods ca...

CVE-2020-15212 Out of bounds access in tensorflow-lite

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to segmentidsdata can alter outputindex and then write to outside of outputdata...

CVE-2020-15212

CVE-2020-15212 affects TensorFlow Lite: models using segment_sum can trigger writes outside heap buffers when negative segment_ids are present, allowing out-of-bounds writes and potential memory corruption. The issue is fixed in TensorFlow 2.2.1 and 2.3.1 (commit 204945b19e44b57906c9344c0d00120ee...

CVE-2020-15212

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to segmentidsdata can alter outputindex and then write to outside of outputdata...

CVE-2020-15213

CVE-2020-15213 affects TensorFlow Lite prior to 2.2.1 and 2.3.1. The vulnerability arises in the segment_sum implementation: models that use segment sums can trigger a denial of service by causing an out-of-memory allocation. The root cause is that code uses the last element of the segment_ids te...

CVE-2020-15213 Denial of service in tensorflow-lite

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor,...

CVE-2020-15213

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor,...

CVE-2020-15214

CVE-2020-15214 affects TensorFlow Lite prior to 2.2.1 and 2.3.1. A write-out-of-bounds can occur when segment IDs are not sorted in segment_sum, due to memory allocation based on the last segment-id element, causing segmentation faults and potential memory corruption. The issue is patched in comm...

CVE-2020-15214 Out of bounds write in tensorflow-lite

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the...

CVE-2020-15201

CVE-2020-15201 : TensorFlow before 2.3.1 contains a bounds-checking flaw in RaggedCountSparseOutput, where input ragged-tensor validation is missing. Specifically, values in the splits tensor may not form a valid partitioning of values, risking a heap-based buffer overflow if split_values does no...

CVE-2020-15201 Heap buffer overflow in Tensorflow

In Tensorflow before version 2.3.1, the RaggedCountSparseOutput implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the splits tensor generate a valid partitioning of the values tensor. Hence, the code is...

CVE-2020-15201

In Tensorflow before version 2.3.1, the RaggedCountSparseOutput implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the splits tensor generate a valid partitioning of the values tensor. Hence, the code is...

CVE-2020-15202 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 taking int or int32 arguments is being used. In...

CVE-2020-15202

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 taking int or int32 arguments is being used. In...

CVE-2020-15202

CVE-2020-15202 : TensorFlow Shard API truncation bug affects multiple releases (1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1). A lambda taking int/int32 instead of int64 in work-parallelization can cause integer truncation, leading to segfaults, out-of-bounds reads/writes, stack overflows, or data corrupti...

CVE-2020-15203

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the fill argument of tf.strings.asstring, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a printf call is constructed. This may result in segmentati...

CVE-2020-15203 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, by controlling the fill argument of tf.strings.asstring, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a printf call is constructed. This may result in segmentati...