| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Memory corruption in MODEM UIM due to usage of out of range pointer offset while decoding command from card in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables |
| Possible memory corruption in kernel while performing memory access due to hypervisor not correctly invalidated the processor translation caches in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile |
| Information disclosure in video due to buffer over-read while parsing avi files in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wearables |
| Azure RTOS USBX is a USB host, device, and on-the-go (OTG) embedded stack, that is fully integrated with Azure RTOS ThreadX. Prior to version 6.1.12, the USB DFU UPLOAD functionality may be utilized to introduce a buffer overflow resulting in overwrite of memory contents. In particular cases this may allow an attacker to bypass security features or execute arbitrary code. The implementation of `ux_device_class_dfu_control_request` function prevents buffer overflow during handling of DFU UPLOAD command when current state is `UX_SYSTEM_DFU_STATE_DFU_IDLE`. This issue has been patched, please upgrade to version 6.1.12. As a workaround, add the `UPLOAD_LENGTH` check in all possible states. |
| Azure RTOS FileX is a FAT-compatible file system that’s fully integrated with Azure RTOS ThreadX. In versions before 6.2.0, the Fault Tolerant feature of Azure RTOS FileX includes integer under and overflows which may be exploited to achieve buffer overflow and modify memory contents. When a valid log file with correct ID and checksum is detected by the `_fx_fault_tolerant_enable` function an attempt to recover the previous failed write operation is taken by call of `_fx_fault_tolerant_apply_logs`. This function iterates through the log entries and performs required recovery operations. When properly crafted a log including entries of type `FX_FAULT_TOLERANT_DIR_LOG_TYPE` may be utilized to introduce unexpected behavior. This issue has been patched in version 6.2.0. A workaround to fix line 218 in fx_fault_tolerant_apply_logs.c is documented in the GHSA. |
| TensorFlow is an open source platform for machine learning. When the `BaseCandidateSamplerOp` function receives a value in `true_classes` larger than `range_max`, a heap oob read occurs. We have patched the issue in GitHub commit b389f5c944cadfdfe599b3f1e4026e036f30d2d4. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. When `tf.raw_ops.FusedResizeAndPadConv2D` is given a large tensor shape, it overflows. We have patched the issue in GitHub commit d66e1d568275e6a2947de97dca7a102a211e01ce. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. When `tf.raw_ops.ImageProjectiveTransformV2` is given a large output shape, it overflows. We have patched the issue in GitHub commit 8faa6ea692985dbe6ce10e1a3168e0bd60a723ba. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9. |
| TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels > output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. If `MirrorPadGrad` is given outsize input `paddings`, TensorFlow will give a heap OOB error. We have patched the issue in GitHub commit 717ca98d8c3bba348ff62281fdf38dcb5ea1ec92. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. If `ThreadUnsafeUnigramCandidateSampler` is given input `filterbank_channel_count` greater than the allowed max size, TensorFlow will crash. We have patched the issue in GitHub commit 39ec7eaf1428e90c37787e5b3fbd68ebd3c48860. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. If `FractionMaxPoolGrad` is given outsize inputs `row_pooling_sequence` and `col_pooling_sequence`, TensorFlow will crash. We have patched the issue in GitHub commit d71090c3e5ca325bdf4b02eb236cfb3ee823e927. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1. |
| TensorFlow is an open source platform for machine learning. When `tf.raw_ops.ResizeNearestNeighborGrad` is given a large `size` input, it overflows. We have patched the issue in GitHub commit 00c821af032ba9e5f5fa3fe14690c8d28a657624. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. |
| XWiki Platform is a generic wiki platform offering runtime services for applications built on top of it. Any user with view rights on commonly accessible documents including the menu macro can execute arbitrary Groovy, Python or Velocity code in XWiki leading to full access to the XWiki installation due to improper escaping of the macro content and parameters of the menu macro. The problem has been patched in XWiki 14.6RC1, 13.10.8 and 14.4.3. The patch (commit `2fc20891`) for the document `Menu.MenuMacro` can be manually applied or a XAR archive of a patched version can be imported. The menu macro was basically unchanged since XWiki 11.6 so on XWiki 11.6 or later the patch for version of 13.10.8 (commit `59ccca24a`) can most likely be applied, on XWiki version 14.0 and later the versions in XWiki 14.6 and 14.4.3 should be appropriate. |
| OP-TEE Trusted OS is the secure side implementation of OP-TEE project, a Trusted Execution Environment. Versions prior to 3.19.0, contain an Improper Validation of Array Index vulnerability. The function `cleanup_shm_refs()` is called by both `entry_invoke_command()` and `entry_open_session()`. The commands `OPTEE_MSG_CMD_OPEN_SESSION` and `OPTEE_MSG_CMD_INVOKE_COMMAND` can be executed from the normal world via an OP-TEE SMC. This function is not validating the `num_params` argument, which is only limited to `OPTEE_MSG_MAX_NUM_PARAMS` (127) in the function `get_cmd_buffer()`. Therefore, an attacker in the normal world can craft an SMC call that will cause out-of-bounds reading in `cleanup_shm_refs` and potentially freeing of fake-objects in the function `mobj_put()`. A normal-world attacker with permission to execute SMC instructions may exploit this flaw. Maintainers believe this problem permits local privilege escalation from the normal world to the secure world. Version 3.19.0 contains a fix for this issue. There are no known workarounds. |
| Netty project is an event-driven asynchronous network application framework. Starting in version 4.1.83.Final and prior to 4.1.86.Final, when calling `DefaultHttpHeadesr.set` with an _iterator_ of values, header value validation was not performed, allowing malicious header values in the iterator to perform HTTP Response Splitting. This issue has been patched in version 4.1.86.Final. Integrators can work around the issue by changing the `DefaultHttpHeaders.set(CharSequence, Iterator<?>)` call, into a `remove()` call, and call `add()` in a loop over the iterator of values. |
| An integer underflow was discovered in Fort 1.6.3 and 1.6.4 before 1.6.5. A malicious RPKI repository that descends from a (trusted) Trust Anchor can serve (via rsync or RRDP) a Manifest RPKI object containing an empty fileList. Fort dereferences (and, shortly afterwards, writes to) this array during a shuffle attempt, before the validation that would normally reject it when empty. This out-of-bounds access is caused by an integer underflow that causes the surrounding loop to iterate infinitely. Because the product is permanently stuck attempting to overshuffle an array that doesn't actually exist, a crash is nearly guaranteed. |
