Total
92 CVE
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2022-27189 | 1 F5 | 11 Big-ip Access Policy Manager, Big-ip Advanced Firewall Manager, Big-ip Analytics and 8 more | 2022-05-13 | 7.5 High |
| On F5 BIG-IP 16.1.x versions prior to 16.1.2.2, 15.1.x versions prior to 15.1.5.1, 14.1.x versions prior to 14.1.4.6, 13.1.x versions prior to 13.1.5, and all versions of 12.1.x and 11.6.x, when an Internet Content Adaptation Protocol (ICAP) profile is configured on a virtual server, undisclosed traffic can cause an increase in Traffic Management Microkernel (TMM) memory resource utilization. Note: Software versions which have reached End of Technical Support (EoTS) are not evaluated | ||||
| CVE-2022-27882 | 1 Openbsd | 1 Openbsd | 2022-05-12 | 7.5 High |
| slaacd in OpenBSD 6.9 and 7.0 before 2022-03-22 has an integer signedness error and resultant heap-based buffer overflow triggerable by a crafted IPv6 router advertisement. NOTE: privilege separation and pledge can prevent exploitation. | ||||
| CVE-2020-12417 | 3 Canonical, Mozilla, Opensuse | 5 Ubuntu Linux, Firefox, Firefox Esr and 2 more | 2022-05-03 | 8.8 High |
| Due to confusion about ValueTags on JavaScript Objects, an object may pass through the type barrier, resulting in memory corruption and a potentially exploitable crash. *Note: this issue only affects Firefox on ARM64 platforms.* This vulnerability affects Firefox ESR < 68.10, Firefox < 78, and Thunderbird < 68.10.0. | ||||
| CVE-2019-19317 | 4 Netapp, Oracle, Siemens and 1 more | 5 Cloud Backup, Ontap Select Deploy Administration Utility, Mysql Workbench and 2 more | 2022-04-15 | 9.8 Critical |
| lookupName in resolve.c in SQLite 3.30.1 omits bits from the colUsed bitmask in the case of a generated column, which allows attackers to cause a denial of service or possibly have unspecified other impact. | ||||
| CVE-2021-32996 | 1 Fanuc | 18 R-30ia, R-30ia Firmware, R-30ia Mate and 15 more | 2022-01-13 | 7.5 High |
| The FANUC R-30iA and R-30iB series controllers are vulnerable to integer coercion errors, which cause the device to crash. A restart is required. | ||||
| CVE-2019-14563 | 2 Debian, Tianocore | 2 Debian Linux, Edk2 | 2022-01-01 | 7.8 High |
| Integer truncation in EDK II may allow an authenticated user to potentially enable escalation of privilege via local access. | ||||
| CVE-2021-41272 | 1 Linuxfoundation | 1 Besu | 2021-12-16 | 7.5 High |
| Besu is an Ethereum client written in Java. Starting in version 21.10.0, changes in the implementation of the SHL, SHR, and SAR operations resulted in the introduction of a signed type coercion error in values that represent negative values for 32 bit signed integers. Smart contracts that ask for shifts between approximately 2 billion and 4 billion bits (nonsensical but valid values for the operation) will fail to execute and hence fail to validate. In networks where vulnerable versions are mining with other clients or non-vulnerable versions this will result in a fork and the relevant transactions will not be included in the fork. In networks where vulnerable versions are not mining (such as Rinkeby) no fork will result and the validator nodes will stop accepting blocks. In networks where only vulnerable versions are mining the relevant transaction will not be included in any blocks. When the network adds a non-vulnerable version the network will act as in the first case. Besu 21.10.2 contains a patch for this issue. Besu 21.7.4 is not vulnerable and clients can roll back to that version. There is a workaround available: Once a transaction with the relevant shift operations is included in the canonical chain, the only remediation is to make sure all nodes are on non-vulnerable versions. | ||||
| CVE-2021-3444 | 3 Canonical, Debian, Linux | 3 Ubuntu Linux, Debian Linux, Linux Kernel | 2021-12-02 | 7.8 High |
| The bpf verifier in the Linux kernel did not properly handle mod32 destination register truncation when the source register was known to be 0. A local attacker with the ability to load bpf programs could use this gain out-of-bounds reads in kernel memory leading to information disclosure (kernel memory), and possibly out-of-bounds writes that could potentially lead to code execution. This issue was addressed in the upstream kernel in commit 9b00f1b78809 ("bpf: Fix truncation handling for mod32 dst reg wrt zero") and in Linux stable kernels 5.11.2, 5.10.19, and 5.4.101. | ||||
| CVE-2021-41202 | 1 Google | 1 Tensorflow | 2021-11-09 | 5.5 Medium |
| TensorFlow is an open source platform for machine learning. In affected versions while calculating the size of the output within the `tf.range` kernel, there is a conditional statement of type `int64 = condition ? int64 : double`. Due to C++ implicit conversion rules, both branches of the condition will be cast to `double` and the result would be truncated before the assignment. This result in overflows. 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-2019-16778 | 1 Google | 1 Tensorflow | 2021-10-29 | 9.8 Critical |
| In TensorFlow before 1.15, a heap buffer overflow in UnsortedSegmentSum can be produced when the Index template argument is int32. In this case data_size and num_segments fields are truncated from int64 to int32 and can produce negative numbers, resulting in accessing out of bounds heap memory. This is unlikely to be exploitable and was detected and fixed internally in TensorFlow 1.15 and 2.0. | ||||
| CVE-2021-36357 | 1 Openpowerfoundation | 1 Skiboot | 2021-10-27 | 9.8 Critical |
| An issue was discovered in OpenPOWER 2.6 firmware. unpack_timestamp() calls le32_to_cpu() for endian conversion of a uint16_t "year" value, resulting in a type mismatch that can truncate a higher integer value to a smaller one, and bypass a timestamp check. The fix is to use the right endian conversion function. | ||||
| CVE-2021-37669 | 1 Google | 1 Tensorflow | 2021-08-19 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. 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-2021-37679 | 1 Google | 1 Tensorflow | 2021-08-19 | 7.8 High |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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-2021-37661 | 1 Google | 1 Tensorflow | 2021-08-18 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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-2021-37646 | 1 Google | 1 Tensorflow | 2021-08-18 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. 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-2021-37645 | 1 Google | 1 Tensorflow | 2021-08-18 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range. | ||||
| CVE-2021-38187 | 1 Anymap Project | 1 Anymap | 2021-08-16 | 9.8 Critical |
| An issue was discovered in the anymap crate through 0.12.1 for Rust. It violates soundness via conversion of a *u8 to a *u64. | ||||
| CVE-2021-29539 | 1 Google | 1 Tensorflow | 2021-07-27 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.ImmutableConst`(https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument. | ||||
| CVE-2021-32461 | 2 Microsoft, Trendmicro | 2 Windows, Password Manager | 2021-07-23 | 7.8 High |
| Trend Micro Password Manager (Consumer) version 5.0.0.1217 and below is vulnerable to an Integer Truncation Privilege Escalation vulnerability which could allow a local attacker to trigger a buffer overflow and escalate privileges on affected installations. An attacker must first obtain the ability to execute low-privileged code on the target system in order to exploit this vulnerability. | ||||
| CVE-2020-2908 | 2 Opensuse, Oracle | 2 Leap, Vm Virtualbox | 2021-07-21 | 8.2 High |
| Vulnerability in the Oracle VM VirtualBox product of Oracle Virtualization (component: Core). Supported versions that are affected are Prior to 5.2.40, prior to 6.0.20 and prior to 6.1.6. Easily exploitable vulnerability allows high privileged attacker with logon to the infrastructure where Oracle VM VirtualBox executes to compromise Oracle VM VirtualBox. While the vulnerability is in Oracle VM VirtualBox, attacks may significantly impact additional products. Successful attacks of this vulnerability can result in takeover of Oracle VM VirtualBox. CVSS 3.0 Base Score 8.2 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.0/AV:L/AC:L/PR:H/UI:N/S:C/C:H/I:H/A:H). | ||||