Out-of-bounds Read

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.Show less

TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.Show less

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor. We have patched the issue in GitHub commit 87158f43f05f2720a374f3e6d22a7aaa3a33f750. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.Show less

TensorFlow is an end-to-end open source platform for machine learning. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.Show less

The function that is used to parse the Authentication header in Brocade Fabric OS Web application service before Brocade Fabric OS v9.0.1a and v8.2.3a fails to properly process a malformed authentication header from the client, resulting in reading memory addresses outside the intended range. An unauthenticated attacker could discover a request, which could bypass the authentication process.Show less

Bootloader contains a vulnerability in the NV3P server where any user with physical access through USB can trigger an incorrect bounds check, which may lead to buffer overflow, resulting in limited information disclosure, limited data integrity, and denial of service across all components.Show less

Out-of-bounds read in the firmware for Intel(R) Ethernet Adapters 800 Series Controllers and associated adapters before version 1.5.3.0 may allow an unauthenticated user to potentially enable denial of service via adjacent access.Show less

A vulnerability has been identified in JT2Go (All versions < V13.2.0.2), Teamcenter Visualization (All versions < V13.2.0.2). The plmxmlAdapterSE70.dll library in affected applications lacks proper validation of user-supplied data when parsing PAR files. This could result in an out of bounds read past the end of an allocated buffer. An attacker could leverage this vulnerability to leak information in the context of the current process. (ZDI-CAN-13405)Show less

Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An out-of-bounds read was found in Exiv2 versions v0.27.4 and earlier. The out-of-bounds read is triggered when Exiv2 is used to read the metadata of a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service, if they can trick the victim into running Exiv2 on a crafted image file. The bug is fixed in version v0.27.5.Show less

Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An out-of-bounds read was found in Exiv2 versions v0.27.4 and earlier. The out-of-bounds read is triggered when Exiv2 is used to write metadata into a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service by crashing Exiv2, if they can trick the victim into running Exiv2 on a crafted image file. Note that this bug is only triggered when writing the metadata, which is a less frequently used Exiv2 operation than reading the metadata. For example, to trigger the bug in the Exiv2 command-line application, you need to add an extra command-line argument such as insert. The bug is fixed in version v0.27.5.Show less

Exiv2 is a command-line utility and C++ library for reading, writing, deleting, and modifying the metadata of image files. An out-of-bounds read was found in Exiv2 versions v0.27.4 and earlier. The out-of-bounds read is triggered when Exiv2 is used to print the metadata of a crafted image file. An attacker could potentially exploit the vulnerability to cause a denial of service, if they can trick the victim into running Exiv2 on a crafted image file. Note that this bug is only triggered when printing the image ICC profile, which is a less frequently used Exiv2 operation that requires an extra command line option (`-p C`). The bug is fixed in version v0.27.5.Show less

libfetch before 2021-07-26, as used in apk-tools, xbps, and other products, mishandles numeric strings for the FTP and HTTP protocols. The FTP passive mode implementation allows an out-of-bounds read because strtol is used to parse the relevant numbers into address bytes. It does not check if the line ends prematurely. If it does, the for-loop condition checks for the '\0' terminator one byte too late.Show less

An untrusted memory read vulnerability in Asylo versions up to 0.6.1 allows an untrusted attacker to pass a syscall number in MessageReader that is then used by sysno() and can bypass validation. This can allow the attacker to read memory from within the secure enclave. We recommend updating to Asylo 0.6.3 or past https://github.com/google/asylo/commit/90d7619e9dd99bcdb6cd28c7649d741d254d9a1aShow less