Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow is vulnerable to an integer overflow during cost estimation for crop and resize. Since the cropping parameters are user controlled, a malicious person can trigger undefined behavior. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21726
Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21727
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness. The axis argument can be -1 (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes axis + 1, an attacker can trigger an integer overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21740
Tensorflow is an Open Source Machine Learning Framework. The implementation of SparseCountSparseOutput is vulnerable to a heap overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23558
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in TfLiteIntArrayCreate. The TfLiteIntArrayGetSizeInBytes returns an int instead of a size_t. An attacker can control model inputs such thatcomputed_sizeoverflows the size ofint` datatype. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23559
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in embedding lookup operations. Both embedding_size and lookup_size are products of values provided by the user. Hence, a malicious user could trigger overflows in the multiplication. In certain scenarios, this can then result in heap OOB read/write. Users are advised to upgrade to a patched version.
CVE-2022-23560
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would allow limited reads and writes outside of arrays in TFLite. This exploits missing validation in the conversion from sparse tensors to dense tensors. The fix is included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. Users are advised to upgrade as soon as possible.
CVE-2022-23561
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23562
Tensorflow is an Open Source Machine Learning Framework. The implementation of Range suffers from integer overflows. These can trigger undefined behavior or, in some scenarios, extremely large allocations. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23566
Tensorflow is an Open Source Machine Learning Framework. TensorFlow is vulnerable to a heap OOB write in Grappler. The set_output function writes to an array at the specified index. Hence, this gives a malicious user a write primitive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23573
Tensorflow is an Open Source Machine Learning Framework. The implementation of AssignOp can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23574
Tensorflow is an Open Source Machine Learning Framework. There is a typo in TensorFlow's SpecializeType which results in heap OOB read/write. Due to a typo, arg is initialized to the ith mutable argument in a loop where the loop index is j. Hence it is possible to assign to arg from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
CVE-2022-21728
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for ReverseSequence does not fully validate the value of batch_dim and can result in a heap OOB read. There is a check to make sure the value of batch_dim does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of Dim would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21730
Tensorflow is an Open Source Machine Learning Framework. The implementation of FractionalAvgPoolGrad does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23590
Tensorflow is an Open Source Machine Learning Framework. A GraphDef from a TensorFlow SavedModel can be maliciously altered to cause a TensorFlow process to crash due to encountering a StatusOr value that is an error and forcibly extracting the value from it. We have patched the issue in multiple GitHub commits and these will be included in TensorFlow 2.8.0 and TensorFlow 2.7.1, as both are affected.
CVE-2022-23591
Tensorflow is an Open Source Machine Learning Framework. The GraphDef format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a GraphDef containing a fragment such as the following can be consumed when loading a SavedModel. This would result in a stack overflow during execution as resolving each NodeDef means resolving the function itself and its nodes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21725
Tensorflow is an Open Source Machine Learning Framework. The estimator for the cost of some convolution operations can be made to execute a division by 0. The function fails to check that the stride argument is strictly positive. Hence, the fix is to add a check for the stride argument to ensure it is valid. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21729
Tensorflow is an Open Source Machine Learning Framework. The implementation of UnravelIndex is vulnerable to a division by zero caused by an integer overflow bug. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21731
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for ConcatV2 can be used to trigger a denial of service attack via a segfault caused by a type confusion. The axis argument is translated into concat_dim in the ConcatShapeHelper helper function. Then, a value for min_rank is computed based on concat_dim. This is then used to validate that the values tensor has at least the required rank. However, WithRankAtLeast receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that min_rank is a 32-bits value and the value of axis, the rank argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21732
Tensorflow is an Open Source Machine Learning Framework. The implementation of ThreadPoolHandle can be used to trigger a denial of service attack by allocating too much memory. This is because the num_threads argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21733
Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21734
Tensorflow is an Open Source Machine Learning Framework. The implementation of MapStage is vulnerable a CHECK-fail if the key tensor is not a scalar. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21735
Tensorflow is an Open Source Machine Learning Framework. The implementation of FractionalMaxPool can be made to crash a TensorFlow process via a division by 0. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21736
Tensorflow is an Open Source Machine Learning Framework. The implementation of SparseTensorSliceDataset has an undefined behavior: under certain condition it can be made to dereference a nullptr value. The 3 input arguments to SparseTensorSliceDataset represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21737
Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21738
Tensorflow is an Open Source Machine Learning Framework. The implementation of SparseCountSparseOutput can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21739
Tensorflow is an Open Source Machine Learning Framework. The implementation of QuantizedMaxPool has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21741
Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23557
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would trigger a division by zero in BiasAndClamp implementation. There is no check that the bias_size is non zero. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23564
Tensorflow is an Open Source Machine Learning Framework. When decoding a resource handle tensor from protobuf, a TensorFlow process can encounter cases where a CHECK assertion is invalidated based on user controlled arguments. This allows attackers to cause denial of services in TensorFlow processes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23565
Tensorflow is an Open Source Machine Learning Framework. An attacker can trigger denial of service via assertion failure by altering a SavedModel on disk such that AttrDefs of some operation are duplicated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23567
Tensorflow is an Open Source Machine Learning Framework. The implementations of Sparse*Cwise* ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or CHECK-fails when building new TensorShape objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large TensorShape with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23568
Tensorflow is an Open Source Machine Learning Framework. The implementation of AddManySparseToTensorsMap is vulnerable to an integer overflow which results in a CHECK-fail when building new TensorShape objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large TensorShape with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23569
Tensorflow is an Open Source Machine Learning Framework. Multiple operations in TensorFlow can be used to trigger a denial of service via CHECK-fails (i.e., assertion failures). This is similar to TFSA-2021-198 and has similar fixes. We have patched the reported issues in multiple GitHub commits. It is possible that other similar instances exist in TensorFlow, we will issue fixes as these are discovered. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23570
Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, TensorFlow might do a null-dereference if attributes of some mutable arguments to some operations are missing from the proto. This is guarded by a DCHECK. However, DCHECK is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the dereferencing of the null pointer, whereas in the second case it results in a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
CVE-2022-23571
Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a CHECK assertion is invalidated based on user controlled arguments, if the tensors have an invalid dtype and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow processes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23572
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the DCHECK function however, DCHECK is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the ValueOrDie line. This results in an assertion failure as ret contains an error Status, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
CVE-2022-23575
Tensorflow is an Open Source Machine Learning Framework. The implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23576
Tensorflow is an Open Source Machine Learning Framework. The implementation of OpLevelCostEstimator::CalculateOutputSize is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in output_shape.dim() or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23577
Tensorflow is an Open Source Machine Learning Framework. The implementation of GetInitOp is vulnerable to a crash caused by dereferencing a null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23579
Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a SavedModel such that SafeToRemoveIdentity would trigger CHECK failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23580
Tensorflow is an Open Source Machine Learning Framework. During shape inference, TensorFlow can allocate a large vector based on a value from a tensor controlled by the user. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23581
Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a SavedModel such that IsSimplifiableReshape would trigger CHECK failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23582
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that TensorByteSize would trigger CHECK failures. TensorShape constructor throws a CHECK-fail if shape is partial or has a number of elements that would overflow the size of an int. The PartialTensorShape constructor instead does not cause a CHECK-abort if the shape is partial, which is exactly what this function needs to be able to return -1. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23583
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that any binary op would trigger CHECK failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the dtype no longer matches the dtype expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If Tin and Tout don't match the type of data in out and input_* tensors then flat<*> would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a CHECK crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23584
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a use after free behavior when decoding PNG images. After png::CommonFreeDecode(&decode) gets called, the values of decode.width and decode.height are in an unspecified state. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23585
Tensorflow is an Open Source Machine Learning Framework. When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling png::CommonInitDecode(..., &decode), the decode value contains allocated buffers which can only be freed by calling png::CommonFreeDecode(&decode). However, several error case in the function implementation invoke the OP_REQUIRES macro which immediately terminates the execution of the function, without allowing for the memory free to occur. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23586
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that assertions in function.cc would be falsified and crash the Python interpreter. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23588
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that Grappler optimizer would attempt to build a tensor using a reference dtype. This would result in a crash due to a CHECK-fail in the Tensor constructor as reference types are not allowed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23589
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23595
Tensorflow is an Open Source Machine Learning Framework. When building an XLA compilation cache, if default settings are used, TensorFlow triggers a null pointer dereference. In the default scenario, all devices are allowed, so flr->config_proto is nullptr. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23563
Tensorflow is an Open Source Machine Learning Framework. In multiple places, TensorFlow uses tempfile.mktemp to create temporary files. While this is acceptable in testing, in utilities and libraries it is dangerous as a different process can create the file between the check for the filename in mktemp and the actual creation of the file by a subsequent operation (a TOC/TOU type of weakness). In several instances, TensorFlow was supposed to actually create a temporary directory instead of a file. This logic bug is hidden away by the mktemp function usage. We have patched the issue in several commits, replacing mktemp with the safer mkstemp/mkdtemp functions, according to the usage pattern. Users are advised to upgrade as soon as possible.
CVE-2022-23578
Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of ImmutableExecutorState::Initialize. Here, we set item->kernel to nullptr but it is a simple OpKernel* pointer so the memory that was previously allocated to it would leak. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
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CVE details
CVE-2022-23587
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow is vulnerable to an integer overflow during cost estimation for crop and resize. Since the cropping parameters are user controlled, a malicious person can trigger undefined behavior. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21726
Tensorflow is an Open Source Machine Learning Framework. The implementation of
Dequantize
does not fully validate the value ofaxis
and can result in heap OOB accesses. Theaxis
argument can be-1
(the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21727
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for
Dequantize
is vulnerable to an integer overflow weakness. Theaxis
argument can be-1
(the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computesaxis + 1
, an attacker can trigger an integer overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21740
Tensorflow is an Open Source Machine Learning Framework. The implementation of
SparseCountSparseOutput
is vulnerable to a heap overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23558
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in
TfLiteIntArrayCreate
. TheTfLiteIntArrayGetSizeInBytes
returns anint
instead of asize_t. An attacker can control model inputs such that
computed_sizeoverflows the size of
int` datatype. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23559
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in embedding lookup operations. Both
embedding_size
andlookup_size
are products of values provided by the user. Hence, a malicious user could trigger overflows in the multiplication. In certain scenarios, this can then result in heap OOB read/write. Users are advised to upgrade to a patched version.CVE-2022-23560
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would allow limited reads and writes outside of arrays in TFLite. This exploits missing validation in the conversion from sparse tensors to dense tensors. The fix is included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. Users are advised to upgrade as soon as possible.
CVE-2022-23561
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23562
Tensorflow is an Open Source Machine Learning Framework. The implementation of
Range
suffers from integer overflows. These can trigger undefined behavior or, in some scenarios, extremely large allocations. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23566
Tensorflow is an Open Source Machine Learning Framework. TensorFlow is vulnerable to a heap OOB write in
Grappler
. Theset_output
function writes to an array at the specified index. Hence, this gives a malicious user a write primitive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23573
Tensorflow is an Open Source Machine Learning Framework. The implementation of
AssignOp
can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23574
Tensorflow is an Open Source Machine Learning Framework. There is a typo in TensorFlow's
SpecializeType
which results in heap OOB read/write. Due to a typo,arg
is initialized to thei
th mutable argument in a loop where the loop index isj
. Hence it is possible to assign toarg
from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.CVE-2022-21728
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for
ReverseSequence
does not fully validate the value ofbatch_dim
and can result in a heap OOB read. There is a check to make sure the value ofbatch_dim
does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation ofDim
would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21730
Tensorflow is an Open Source Machine Learning Framework. The implementation of
FractionalAvgPoolGrad
does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23590
Tensorflow is an Open Source Machine Learning Framework. A
GraphDef
from a TensorFlowSavedModel
can be maliciously altered to cause a TensorFlow process to crash due to encountering aStatusOr
value that is an error and forcibly extracting the value from it. We have patched the issue in multiple GitHub commits and these will be included in TensorFlow 2.8.0 and TensorFlow 2.7.1, as both are affected.CVE-2022-23591
Tensorflow is an Open Source Machine Learning Framework. The
GraphDef
format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, aGraphDef
containing a fragment such as the following can be consumed when loading aSavedModel
. This would result in a stack overflow during execution as resolving eachNodeDef
means resolving the function itself and its nodes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21725
Tensorflow is an Open Source Machine Learning Framework. The estimator for the cost of some convolution operations can be made to execute a division by 0. The function fails to check that the stride argument is strictly positive. Hence, the fix is to add a check for the stride argument to ensure it is valid. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-21729
Tensorflow is an Open Source Machine Learning Framework. The implementation of
UnravelIndex
is vulnerable to a division by zero caused by an integer overflow bug. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21731
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for
ConcatV2
can be used to trigger a denial of service attack via a segfault caused by a type confusion. Theaxis
argument is translated intoconcat_dim
in theConcatShapeHelper
helper function. Then, a value formin_rank
is computed based onconcat_dim
. This is then used to validate that thevalues
tensor has at least the required rank. However,WithRankAtLeast
receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact thatmin_rank
is a 32-bits value and the value ofaxis
, therank
argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21732
Tensorflow is an Open Source Machine Learning Framework. The implementation of
ThreadPoolHandle
can be used to trigger a denial of service attack by allocating too much memory. This is because thenum_threads
argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21733
Tensorflow is an Open Source Machine Learning Framework. The implementation of
StringNGrams
can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation onpad_witdh
and that result in computing a negative value forngram_width
which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21734
Tensorflow is an Open Source Machine Learning Framework. The implementation of
MapStage
is vulnerable aCHECK
-fail if the key tensor is not a scalar. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21735
Tensorflow is an Open Source Machine Learning Framework. The implementation of
FractionalMaxPool
can be made to crash a TensorFlow process via a division by 0. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21736
Tensorflow is an Open Source Machine Learning Framework. The implementation of
SparseTensorSliceDataset
has an undefined behavior: under certain condition it can be made to dereference anullptr
value. The 3 input arguments toSparseTensorSliceDataset
represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21737
Tensorflow is an Open Source Machine Learning Framework. The implementation of
*Bincount
operations allows malicious users to cause denial of service by passing in arguments which would trigger aCHECK
-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results inCHECK
failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21738
Tensorflow is an Open Source Machine Learning Framework. The implementation of
SparseCountSparseOutput
can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21739
Tensorflow is an Open Source Machine Learning Framework. The implementation of
QuantizedMaxPool
has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-21741
Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23557
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would trigger a division by zero in
BiasAndClamp
implementation. There is no check that thebias_size
is non zero. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23564
Tensorflow is an Open Source Machine Learning Framework. When decoding a resource handle tensor from protobuf, a TensorFlow process can encounter cases where a
CHECK
assertion is invalidated based on user controlled arguments. This allows attackers to cause denial of services in TensorFlow processes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23565
Tensorflow is an Open Source Machine Learning Framework. An attacker can trigger denial of service via assertion failure by altering a
SavedModel
on disk such thatAttrDef
s of some operation are duplicated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23567
Tensorflow is an Open Source Machine Learning Framework. The implementations of
Sparse*Cwise*
ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) orCHECK
-fails when building newTensorShape
objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a largeTensorShape
with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23568
Tensorflow is an Open Source Machine Learning Framework. The implementation of
AddManySparseToTensorsMap
is vulnerable to an integer overflow which results in aCHECK
-fail when building newTensorShape
objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a largeTensorShape
with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23569
Tensorflow is an Open Source Machine Learning Framework. Multiple operations in TensorFlow can be used to trigger a denial of service via
CHECK
-fails (i.e., assertion failures). This is similar to TFSA-2021-198 and has similar fixes. We have patched the reported issues in multiple GitHub commits. It is possible that other similar instances exist in TensorFlow, we will issue fixes as these are discovered. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23570
Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, TensorFlow might do a null-dereference if attributes of some mutable arguments to some operations are missing from the proto. This is guarded by a
DCHECK
. However,DCHECK
is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the dereferencing of the null pointer, whereas in the second case it results in a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.CVE-2022-23571
Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a
CHECK
assertion is invalidated based on user controlled arguments, if the tensors have an invaliddtype
and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow processes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23572
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the
DCHECK
function however,DCHECK
is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to theValueOrDie
line. This results in an assertion failure asret
contains an errorStatus
, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.CVE-2022-23575
Tensorflow is an Open Source Machine Learning Framework. The implementation of
OpLevelCostEstimator::CalculateTensorSize
is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23576
Tensorflow is an Open Source Machine Learning Framework. The implementation of
OpLevelCostEstimator::CalculateOutputSize
is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions inoutput_shape.dim()
or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23577
Tensorflow is an Open Source Machine Learning Framework. The implementation of
GetInitOp
is vulnerable to a crash caused by dereferencing a null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23579
Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a
SavedModel
such thatSafeToRemoveIdentity
would triggerCHECK
failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23580
Tensorflow is an Open Source Machine Learning Framework. During shape inference, TensorFlow can allocate a large vector based on a value from a tensor controlled by the user. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVE-2022-23581
Tensorflow is an Open Source Machine Learning Framework. The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a
SavedModel
such thatIsSimplifiableReshape
would triggerCHECK
failures. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23582
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a
SavedModel
such thatTensorByteSize
would triggerCHECK
failures.TensorShape
constructor throws aCHECK
-fail if shape is partial or has a number of elements that would overflow the size of anint
. ThePartialTensorShape
constructor instead does not cause aCHECK
-abort if the shape is partial, which is exactly what this function needs to be able to return-1
. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23583
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a
SavedModel
such that any binary op would triggerCHECK
failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that thedtype
no longer matches thedtype
expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. IfTin
andTout
don't match the type of data inout
andinput_*
tensors thenflat<*>
would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in aCHECK
crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23584
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a use after free behavior when decoding PNG images. After
png::CommonFreeDecode(&decode)
gets called, the values ofdecode.width
anddecode.height
are in an unspecified state. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23585
Tensorflow is an Open Source Machine Learning Framework. When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling
png::CommonInitDecode(..., &decode)
, thedecode
value contains allocated buffers which can only be freed by callingpng::CommonFreeDecode(&decode)
. However, several error case in the function implementation invoke theOP_REQUIRES
macro which immediately terminates the execution of the function, without allowing for the memory free to occur. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23586
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a
SavedModel
such that assertions infunction.cc
would be falsified and crash the Python interpreter. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23588
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a
SavedModel
such that Grappler optimizer would attempt to build a tensor using a referencedtype
. This would result in a crash due to aCHECK
-fail in theTensor
constructor as reference types are not allowed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23589
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a
SavedModel
file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, theGraphDef
might not have the required nodes for the binary operation. If a node is missing, the correposningmul_*child
would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue duringIsIdentityConsumingSwitch
. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23595
Tensorflow is an Open Source Machine Learning Framework. When building an XLA compilation cache, if default settings are used, TensorFlow triggers a null pointer dereference. In the default scenario, all devices are allowed, so
flr->config_proto
isnullptr
. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.CVE-2022-23563
Tensorflow is an Open Source Machine Learning Framework. In multiple places, TensorFlow uses
tempfile.mktemp
to create temporary files. While this is acceptable in testing, in utilities and libraries it is dangerous as a different process can create the file between the check for the filename inmktemp
and the actual creation of the file by a subsequent operation (a TOC/TOU type of weakness). In several instances, TensorFlow was supposed to actually create a temporary directory instead of a file. This logic bug is hidden away by themktemp
function usage. We have patched the issue in several commits, replacingmktemp
with the safermkstemp
/mkdtemp
functions, according to the usage pattern. Users are advised to upgrade as soon as possible.CVE-2022-23578
Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of
ImmutableExecutorState::Initialize
. Here, we setitem->kernel
tonullptr
but it is a simpleOpKernel*
pointer so the memory that was previously allocated to it would leak. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.Scanned versions: nixos-21.11: 2128d0aa28e.
Cc @abbradar Cc @jyp