| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| ACCEL-PPP 1.12.0 has an out-of-bounds read in triton_context_schedule if the client exits after authentication. |
| An out-of-bounds access in GffLine::GffLine in gff.cpp in GCLib 0.12.7 allows an attacker to cause a segmentation fault or possibly have unspecified other impact via a crafted GFF file. |
| Go before 1.16.10 and 1.17.x before 1.17.3 allows an archive/zip Reader.Open panic via a crafted ZIP archive containing an invalid name or an empty filename field. |
| x509_constraints_parse_mailbox in lib/libcrypto/x509/x509_constraints.c in LibreSSL through 3.4.0 has a stack-based buffer over-read. When the input exceeds DOMAIN_PART_MAX_LEN, the buffer lacks '\0' termination. |
| sqclass.cpp in Squirrel through 2.2.5 and 3.x through 3.1 allows an out-of-bounds read (in the core interpreter) that can lead to Code Execution. If a victim executes an attacker-controlled squirrel script, it is possible for the attacker to break out of the squirrel script sandbox even if all dangerous functionality such as File System functions has been disabled. An attacker might abuse this bug to target (for example) Cloud services that allow customization via SquirrelScripts, or distribute malware through video games that embed a Squirrel Engine. |
| A vulnerability has been identified in NX 1980 Series (All versions < V1984), Solid Edge SE2021 (All versions < SE2021MP8). The affected application is vulnerable to an out of bounds read past the end of an allocated buffer when parsing JT files. An attacker could leverage this vulnerability to leak information in the context of the current process (ZDI-CAN-13703). |
| A vulnerability has been identified in NX 1980 Series (All versions < V1984), Solid Edge SE2021 (All versions < SE2021MP8). The affected application is vulnerable to an out of bounds read past the end of an allocated buffer when parsing JT files. An attacker could leverage this vulnerability to leak information in the context of the current process (ZDI-CAN-13565). |
| TensorFlow is an open source platform for machine learning. In affected versions the `ImmutableConst` operation in TensorFlow can be tricked into reading arbitrary memory contents. This is because the `tstring` TensorFlow string class has a special case for memory mapped strings but the operation itself does not offer any support for this datatype. 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 implementation of `SparseBinCount` is vulnerable to a heap OOB access. This is because of missing validation between the elements of the `values` argument and the shape of the sparse output. 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 implementation of `SparseFillEmptyRows` can be made to trigger a heap OOB access. This occurs whenever the size of `indices` does not match the size of `values`. 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 implementation of `FusedBatchNorm` kernels is vulnerable to a 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 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` can trigger a read outside of bounds of heap allocated array. 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 `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected. |
| TensorFlow is an open source platform for machine learning. In affected versions the shape inference functions for `SparseCountSparseOutput` can trigger a read outside of bounds of heap allocated array. 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 functions for the `QuantizeAndDequantizeV*` operations can trigger a read outside of bounds of heap allocated array. 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. |
| Redis is an open source, in-memory database that persists on disk. An integer overflow bug in the underlying string library can be used to corrupt the heap and potentially result with denial of service or remote code execution. The vulnerability involves changing the default proto-max-bulk-len configuration parameter to a very large value and constructing specially crafted network payloads or commands. The problem is fixed in Redis versions 6.2.6, 6.0.16 and 5.0.14. An additional workaround to mitigate the problem without patching the redis-server executable is to prevent users from modifying the proto-max-bulk-len configuration parameter. This can be done using ACL to restrict unprivileged users from using the CONFIG SET command. |
| In Eclipse Wakaama, ever since its inception until 2021-01-14, the CoAP parsing code does not properly sanitize network-received data. |
| A stack-based buffer under-read in htmldoc before 1.9.12, allows attackers to cause a denial of service via a crafted BMP image to image_load_bmp. |
| The GD Graphics Library (aka LibGD) through 2.3.2 has an out-of-bounds read because of the lack of certain gdGetBuf and gdPutBuf return value checks. |
