| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. |
| Redis is an in-memory database that persists on disk. Versions 7.0.0 and above, prior to 7.0.5 are vulnerable to an Integer Overflow. Executing an `XAUTOCLAIM` command on a stream key in a specific state, with a specially crafted `COUNT` argument may cause an integer overflow, a subsequent heap overflow, and potentially lead to remote code execution. This has been patched in Redis version 7.0.5. No known workarounds exist. |
| Besu is a Java-based Ethereum client. In versions newer than 22.1.3 and prior to 22.7.1, Besu is subject to an Incorrect Conversion between Numeric Types. An error in 32 bit signed and unsigned types in the calculation of available gas in the CALL operations (including DELEGATECALL) results in incorrect gas being passed into called contracts and incorrect gas being returned after call execution. Where the amount of gas makes a difference in the success or failure, or if the gas is a negative 64 bit value, the execution will result in a different state root than expected, resulting in a consensus failure in networks with multiple EVM implementations. In networks with a single EVM implementation this can be used to execute with significantly more gas than then transaction requested, possibly exceeding gas limitations. This issue is patched in version 22.7.1. As a workaround, reverting to version 22.1.3 or earlier will prevent incorrect execution. |
| Azure RTOS USBX is a high-performance USB host, device, and on-the-go (OTG) embedded stack, that is fully integrated with Azure RTOS ThreadX. The case is, in [_ux_host_class_pima_read](https://github.com/azure-rtos/usbx/blob/master/common/usbx_host_classes/src/ux_host_class_pima_read.c), there is data length from device response, returned in the very first packet, and read by [L165 code](https://github.com/azure-rtos/usbx/blob/082fd9db09a3669eca3358f10b8837a5c1635c0b/common/usbx_host_classes/src/ux_host_class_pima_read.c#L165), as header_length. Then in [L178 code](https://github.com/azure-rtos/usbx/blob/082fd9db09a3669eca3358f10b8837a5c1635c0b/common/usbx_host_classes/src/ux_host_class_pima_read.c#L178), there is a “if” branch, which check the expression of “(header_length - UX_HOST_CLASS_PIMA_DATA_HEADER_SIZE) > data_length” where if header_length is smaller than UX_HOST_CLASS_PIMA_DATA_HEADER_SIZE, calculation could overflow and then [L182 code](https://github.com/azure-rtos/usbx/blob/082fd9db09a3669eca3358f10b8837a5c1635c0b/common/usbx_host_classes/src/ux_host_class_pima_read.c#L182) the calculation of data_length is also overflow, this way the later [while loop start from L192](https://github.com/azure-rtos/usbx/blob/082fd9db09a3669eca3358f10b8837a5c1635c0b/common/usbx_host_classes/src/ux_host_class_pima_read.c#L192) can move data_pointer to unexpected address and cause write buffer overflow. The fix has been included in USBX release [6.1.12](https://github.com/azure-rtos/usbx/releases/tag/v6.1.12_rel). The following can be used as a workaround: Add check of `header_length`: 1. It must be greater than `UX_HOST_CLASS_PIMA_DATA_HEADER_SIZE`. 1. It should be greater or equal to the current returned data length (`transfer_request -> ux_transfer_request_actual_length`). |
| Heimdal is an implementation of ASN.1/DER, PKIX, and Kerberos. Versions prior to 7.7.1 are vulnerable to a denial of service vulnerability in Heimdal's PKI certificate validation library, affecting the KDC (via PKINIT) and kinit (via PKINIT), as well as any third-party applications using Heimdal's libhx509. Users should upgrade to Heimdal 7.7.1 or 7.8. There are no known workarounds for this issue. |
| xrdp is an open source project which provides a graphical login to remote machines using Microsoft Remote Desktop Protocol (RDP).
xrdp < v0.9.21 contain a Integer Overflow in xrdp_mm_process_rail_update_window_text() function. There are no known workarounds for this issue. Users are advised to upgrade. |
| NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer (nvidia.ko), where an integer overflow may lead to information disclosure, data tampering or denial of service. |
| OpenSSH 7.7 through 7.9 and 8.x before 8.1, when compiled with an experimental key type, has a pre-authentication integer overflow if a client or server is configured to use a crafted XMSS key. This leads to memory corruption and local code execution because of an error in the XMSS key parsing algorithm. NOTE: the XMSS implementation is considered experimental in all released OpenSSH versions, and there is no supported way to enable it when building portable OpenSSH. |
| Integer overflow vulnerability in Samsung decoding library for video thumbnails prior to SMR Dec-2022 Release 1 allows local attacker to perform Out-Of-Bounds Write. |
| In battery, there is a possible escalation of privilege due to an integer overflow. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08485622; Issue ID: ALPS08485622. |
| In battery, there is a possible out of bounds read due to an integer overflow. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08587865; Issue ID: ALPS08486807. |
| In da, there is a possible out of bounds write due to an integer overflow. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08541686; Issue ID: ALPS08541686. |
| In several functions that parse avrc response in avrc_pars_ct.cc and related files, there are possible out of bounds reads due to integer overflows. This could lead to remote information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-12L Android-13Android ID: A-242459126 |
| 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. |
| 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. |
| 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. |
| 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. |
| 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 that `computed_size` overflows 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. |
| cmark-gfm is GitHub's extended version of the C reference implementation of CommonMark. Prior to versions 0.29.0.gfm.3 and 0.28.3.gfm.21, an integer overflow in cmark-gfm's table row parsing `table.c:row_from_string` may lead to heap memory corruption when parsing tables who's marker rows contain more than UINT16_MAX columns. The impact of this heap corruption ranges from Information Leak to Arbitrary Code Execution depending on how and where `cmark-gfm` is used. If `cmark-gfm` is used for rendering remote user controlled markdown, this vulnerability may lead to Remote Code Execution (RCE) in applications employing affected versions of the `cmark-gfm` library. This vulnerability has been patched in the following cmark-gfm versions 0.29.0.gfm.3 and 0.28.3.gfm.21. A workaround is available. The vulnerability exists in the table markdown extensions of cmark-gfm. Disabling the table extension will prevent this vulnerability from being triggered. |
| yajl-ruby is a C binding to the YAJL JSON parsing and generation library. The 1.x branch and the 2.x branch of `yajl` contain an integer overflow which leads to subsequent heap memory corruption when dealing with large (~2GB) inputs. The reallocation logic at `yajl_buf.c#L64` may result in the `need` 32bit integer wrapping to 0 when `need` approaches a value of 0x80000000 (i.e. ~2GB of data), which results in a reallocation of buf->alloc into a small heap chunk. These integers are declared as `size_t` in the 2.x branch of `yajl`, which practically prevents the issue from triggering on 64bit platforms, however this does not preclude this issue triggering on 32bit builds on which `size_t` is a 32bit integer. Subsequent population of this under-allocated heap chunk is based on the original buffer size, leading to heap memory corruption. This vulnerability mostly impacts process availability. Maintainers believe exploitation for arbitrary code execution is unlikely. A patch is available and anticipated to be part of yajl-ruby version 1.4.2. As a workaround, avoid passing large inputs to YAJL. |
