| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| On May 4, 2022, the following vulnerability in the ClamAV scanning library versions 0.103.5 and earlier and 0.104.2 and earlier was disclosed: A vulnerability in Clam AntiVirus (ClamAV) versions 0.103.4, 0.103.5, 0.104.1, and 0.104.2 could allow an authenticated, local attacker to cause a denial of service condition on an affected device. For a description of this vulnerability, see the ClamAV blog. |
| Incorrect Synchronization in GitHub repository polonel/trudesk prior to 1.2.3. |
| Access of Uninitialized Pointer in GitHub repository radareorg/radare2 prior to 5.7.0. |
| Use of Out-of-range Pointer Offset in GitHub repository vim/vim prior to 8.2.4774. |
| A flaw was found in the opj2_decompress program in openjpeg2 2.4.0 in the way it handles an input directory with a large number of files. When it fails to allocate a buffer to store the filenames of the input directory, it calls free() on an uninitialized pointer, leading to a segmentation fault and a denial of service. |
| A flaw was found in the Linux kernel in net/netfilter/nf_tables_core.c:nft_do_chain, which can cause a use-after-free. This issue needs to handle 'return' with proper preconditions, as it can lead to a kernel information leak problem caused by a local, unprivileged attacker. |
| Use of Out-of-range Pointer Offset in GitHub repository vim/vim prior to 8.2.4440. |
| Use of Out-of-range Pointer Offset in GitHub repository vim/vim prior to 8.2.4418. |
| Use of Out-of-range Pointer Offset in Homebrew mruby prior to 3.2. |
| Use of Out-of-range Pointer Offset in GitHub repository vim/vim prior to 8.2. |
| A flaw was found in the Linux kernel’s implementation of reading the SVC RDMA counters. Reading the counter sysctl panics the system. This flaw allows a local attacker with local access to cause a denial of service while the system reboots. The issue is specific to CentOS/RHEL. |
| An exposed dangerous function vulnerability exists in Ivanti Avalanche before 6.3.3 allows an attacker with access to the Inforail Service to perform an arbitrary file write. |
| An issue was discovered in AhciBusDxe in the kernel 5.0 through 5.5 in Insyde InsydeH2O. There is an SMM callout that allows an attacker to access the System Management Mode and execute arbitrary code. This occurs because of Inclusion of Functionality from an Untrusted Control Sphere. |
| SAS/Intrnet 9.4 build 1520 and earlier allows Local File Inclusion. The samples library (included by default) in the appstart.sas file, allows end-users of the application to access the sample.webcsf1.sas program, which contains user-controlled macro variables that are passed to the DS2CSF macro. Users can escape the context of the configured user-controllable variable and append additional functions native to the macro but not included as variables within the library. This includes a function that retrieves files from the host OS. |
| 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). |
| nextcloud news-android is an Android client for the Nextcloud news/feed reader app. In affected versions the Nextcloud News for Android app has a security issue by which a malicious application installed on the same device can send it an arbitrary Intent that gets reflected back, unintentionally giving read and write access to non-exported Content Providers in Nextcloud News for Android. Users should upgrade to version 0.9.9.63 or higher as soon as possible. |
| 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. |
| 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. |
| 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. |
| 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. |
