Filtered by CWE-824
Filtered by vendor Subscriptions
Total 237 CVE
CVE Vendors Products Updated CVSS v3.1
CVE-2021-42702 1 Inkscape 1 Inkscape 2024-11-21 3.3 Low
Inkscape version 0.91 can access an uninitialized pointer, which may allow an attacker to have access to unauthorized information.
CVE-2021-41538 1 Siemens 13 Nx 1957, Nx 1957 Firmware, Nx 1961 and 10 more 2024-11-21 3.3 Low
A vulnerability has been identified in NX 1953 Series (All versions < V1973.3700), NX 1980 Series (All versions < V1988), Solid Edge SE2021 (All versions < SE2021MP8). The affected application is vulnerable to information disclosure by unexpected access to an uninitialized pointer while parsing user-supplied OBJ files. An attacker could leverage this vulnerability to leak information from unexpected memory locations (ZDI-CAN-13770).
CVE-2021-41219 1 Google 1 Tensorflow 2024-11-21 7.8 High
TensorFlow is an open source platform for machine learning. In affected versions the code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to `nullptr`. This occurs whenever the dimensions of `a` or `b` are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in heap OOB access. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CVE-2021-41214 1 Google 1 Tensorflow 2024-11-21 7.8 High
TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` has an undefined behavior due to binding a reference to `nullptr`. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CVE-2021-41208 1 Google 1 Tensorflow 2024-11-21 8.8 High
TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing `nullptr`s or via `CHECK`-failures) as well as abuse undefined behavior (binding references to `nullptr`s). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CVE-2021-41204 1 Google 1 Tensorflow 2024-11-21 5.5 Medium
TensorFlow is an open source platform for machine learning. In affected versions during TensorFlow's Grappler optimizer phase, constant folding might attempt to deep copy a resource tensor. This results in a segfault, as these tensors are supposed to not change. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CVE-2021-41201 1 Google 1 Tensorflow 2024-11-21 7.8 High
TensorFlow is an open source platform for machine learning. In affeced versions during execution, `EinsumHelper::ParseEquation()` is supposed to set the flags in `input_has_ellipsis` vector and `*output_has_ellipsis` boolean to indicate whether there is ellipsis in the corresponding inputs and output. However, the code only changes these flags to `true` and never assigns `false`. This results in unitialized variable access if callers assume that `EinsumHelper::ParseEquation()` always sets these flags. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CVE-2021-3608 3 Debian, Fedoraproject, Qemu 3 Debian Linux, Fedora, Qemu 2024-11-21 6.0 Medium
A flaw was found in the QEMU implementation of VMWare's paravirtual RDMA device in versions prior to 6.1.0. The issue occurs while handling a "PVRDMA_REG_DSRHIGH" write from the guest and may result in a crash of QEMU or cause undefined behavior due to the access of an uninitialized pointer. The highest threat from this vulnerability is to system availability.
CVE-2021-3595 4 Debian, Fedoraproject, Libslirp Project and 1 more 4 Debian Linux, Fedora, Libslirp and 1 more 2024-11-21 3.8 Low
An invalid pointer initialization issue was found in the SLiRP networking implementation of QEMU. The flaw exists in the tftp_input() function and could occur while processing a udp packet that is smaller than the size of the 'tftp_t' structure. This issue may lead to out-of-bounds read access or indirect host memory disclosure to the guest. The highest threat from this vulnerability is to data confidentiality. This flaw affects libslirp versions prior to 4.6.0.
CVE-2021-3594 4 Debian, Fedoraproject, Libslirp Project and 1 more 4 Debian Linux, Fedora, Libslirp and 1 more 2024-11-21 3.8 Low
An invalid pointer initialization issue was found in the SLiRP networking implementation of QEMU. The flaw exists in the udp_input() function and could occur while processing a udp packet that is smaller than the size of the 'udphdr' structure. This issue may lead to out-of-bounds read access or indirect host memory disclosure to the guest. The highest threat from this vulnerability is to data confidentiality. This flaw affects libslirp versions prior to 4.6.0.
CVE-2021-3593 4 Debian, Fedoraproject, Libslirp Project and 1 more 4 Debian Linux, Fedora, Libslirp and 1 more 2024-11-21 3.8 Low
An invalid pointer initialization issue was found in the SLiRP networking implementation of QEMU. The flaw exists in the udp6_input() function and could occur while processing a udp packet that is smaller than the size of the 'udphdr' structure. This issue may lead to out-of-bounds read access or indirect host memory disclosure to the guest. The highest threat from this vulnerability is to data confidentiality. This flaw affects libslirp versions prior to 4.6.0.
CVE-2021-3592 4 Debian, Fedoraproject, Libslirp Project and 1 more 4 Debian Linux, Fedora, Libslirp and 1 more 2024-11-21 3.8 Low
An invalid pointer initialization issue was found in the SLiRP networking implementation of QEMU. The flaw exists in the bootp_input() function and could occur while processing a udp packet that is smaller than the size of the 'bootp_t' structure. A malicious guest could use this flaw to leak 10 bytes of uninitialized heap memory from the host. The highest threat from this vulnerability is to data confidentiality. This flaw affects libslirp versions prior to 4.6.0.
CVE-2021-38409 1 Fujielectric 2 V-server, V-simulator 2024-11-21 7.8 High
Fuji Electric V-Server Lite and Tellus Lite V-Simulator prior to v4.0.12.0 is vulnerable to an access of uninitialized pointer, which may allow an attacker read from or write to unexpected memory locations, leading to a denial-of-service.
CVE-2021-38205 2 Debian, Linux 2 Debian Linux, Linux Kernel 2024-11-21 3.3 Low
drivers/net/ethernet/xilinx/xilinx_emaclite.c in the Linux kernel before 5.13.3 makes it easier for attackers to defeat an ASLR protection mechanism because it prints a kernel pointer (i.e., the real IOMEM pointer).
CVE-2021-37676 1 Google 1 Tensorflow 2024-11-21 7.8 High
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.SparseFillEmptyRows`. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/sparse_ops.cc#L608-L634) does not validate that the input arguments are not empty tensors. We have patched the issue in GitHub commit 578e634b4f1c1c684d4b4294f9e5281b2133b3ed. 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.
CVE-2021-37671 1 Google 1 Tensorflow 2024-11-21 7.8 High
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.Map*` and `tf.raw_ops.OrderedMap*` operations. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L222-L248) has a check in place to ensure that `indices` is in ascending order, but does not check that `indices` is not empty. We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. 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.
CVE-2021-37667 1 Google 1 Tensorflow 2024-11-21 7.8 High
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.UnicodeEncode`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that this tensor is not empty. We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6. 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.
CVE-2021-37666 1 Google 1 Tensorflow 2024-11-21 7.8 High
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.RaggedTensorToVariant`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L129) has an incomplete validation of the splits values, missing the case when the argument would be empty. We have patched the issue in GitHub commit be7a4de6adfbd303ce08be4332554dff70362612. 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.
CVE-2021-37662 1 Google 1 Tensorflow 2024-11-21 7.1 High
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can generate undefined behavior via a reference binding to nullptr in `BoostedTreesCalculateBestGainsPerFeature` and similar attack can occur in `BoostedTreesCalculateBestFeatureSplitV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) does not validate the input values. We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit 429f009d2b2c09028647dd4bb7b3f6f414bbaad7. 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.
CVE-2021-37658 1 Google 1 Tensorflow 2024-11-21 7.1 High
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixSetDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit ff8894044dfae5568ecbf2ed514c1a37dc394f1b. 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.