Total
68 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2021-36357 | 1 Openpowerfoundation | 1 Skiboot | 2021-10-27 | 7.5 HIGH | 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 | 2.1 LOW | 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 | 4.6 MEDIUM | 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 | 2.1 LOW | 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 | 2.1 LOW | 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 | 2.1 LOW | 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 | 7.5 HIGH | 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 | 2.1 LOW | 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 | 7.2 HIGH | 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-2020-13985 | 1 Contiki-os | 1 Contiki | 2021-07-21 | 5.0 MEDIUM | 7.5 HIGH |
| An issue was discovered in Contiki through 3.0. A memory corruption vulnerability exists in the uIP TCP/IP stack component when handling RPL extension headers of IPv6 network packets in rpl_remove_header in net/rpl/rpl-ext-header.c. | |||||
| CVE-2019-9749 | 1 Treasuredata | 1 Fluent Bit | 2021-07-21 | 5.0 MEDIUM | 7.5 HIGH |
| An issue was discovered in the MQTT input plugin in Fluent Bit through 1.0.4. When this plugin acts as an MQTT broker (server), it mishandles incoming network messages. After processing a crafted packet, the plugin's mqtt_packet_drop function (in /plugins/in_mqtt/mqtt_prot.c) executes the memmove() function with a negative size parameter. That leads to a crash of the whole Fluent Bit server via a SIGSEGV signal. | |||||
| CVE-2020-35926 | 1 Nanorand Project | 1 Nanorand | 2021-07-21 | 7.5 HIGH | 9.8 CRITICAL |
| An issue was discovered in the nanorand crate before 0.5.1 for Rust. It caused any random number generator (even ChaCha) to return all zeroes because integer truncation was mishandled. | |||||
| CVE-2020-2908 | 2 Opensuse, Oracle | 2 Leap, Vm Virtualbox | 2021-07-21 | 4.6 MEDIUM | 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). | |||||
| CVE-2019-10624 | 1 Qualcomm | 24 Apq8096au, Apq8096au Firmware, Msm8996au and 21 more | 2021-07-21 | 4.6 MEDIUM | 7.8 HIGH |
| While handling the vendor command there is an integer truncation issue that could yield a buffer overflow due to int data type copied to u8 data type in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer Electronics Connectivity, Snapdragon Industrial IOT, Snapdragon Mobile in APQ8096AU, MSM8996AU, QCA6574AU, QCN7605, Rennell, SC8180X, SDM710, SDX55, SM7150, SM8150, SM8250, SXR2130 | |||||
| CVE-2021-23997 | 1 Mozilla | 1 Firefox | 2021-07-02 | 6.8 MEDIUM | 8.8 HIGH |
| Due to unexpected data type conversions, a use-after-free could have occurred when interacting with the font cache. We presume that with enough effort this could have been exploited to run arbitrary code. This vulnerability affects Firefox < 88. | |||||
| CVE-2010-2807 | 3 Apple, Canonical, Freetype | 5 Iphone Os, Mac Os X, Tvos and 2 more | 2021-04-06 | 6.8 MEDIUM | N/A |
| FreeType before 2.4.2 uses incorrect integer data types during bounds checking, which allows remote attackers to cause a denial of service (application crash) or possibly execute arbitrary code via a crafted font file. | |||||
| CVE-2018-8786 | 5 Canonical, Debian, Fedoraproject and 2 more | 10 Ubuntu Linux, Debian Linux, Fedora and 7 more | 2020-09-28 | 7.5 HIGH | 9.8 CRITICAL |
| FreeRDP prior to version 2.0.0-rc4 contains an Integer Truncation that leads to a Heap-Based Buffer Overflow in function update_read_bitmap_update() and results in a memory corruption and probably even a remote code execution. | |||||
| CVE-2020-1913 | 1 Facebook | 1 Hermes | 2020-09-15 | 6.8 MEDIUM | 8.1 HIGH |
| An Integer signedness error in the JavaScript Interpreter in Facebook Hermes prior to commit 2c7af7ec481ceffd0d14ce2d7c045e475fd71dc6 allows attackers to cause a denial of service attack or a potential RCE via crafted JavaScript. Note that this is only exploitable if the application using Hermes permits evaluation of untrusted JavaScript. Hence, most React Native applications are not affected. | |||||
| CVE-2017-12140 | 1 Imagemagick | 1 Imagemagick | 2020-09-07 | 7.1 HIGH | 6.5 MEDIUM |
| The ReadDCMImage function in coders\dcm.c in ImageMagick 7.0.6-1 has an integer signedness error leading to excessive memory consumption via a crafted DCM file. | |||||
| CVE-2019-16200 | 1 Gnu | 1 Serveez | 2020-08-24 | 5.0 MEDIUM | 7.5 HIGH |
| GNU Serveez through 0.2.2 has an Information Leak. An attacker may send an HTTP POST request to the /cgi-bin/reader URI. The attacker must include a Content-length header with a large positive value that, when represented in 32 bit binary, evaluates to a negative number. The problem exists in the http_cgi_write function under http-cgi.c; however, exploitation might show svz_envblock_add in libserveez/passthrough.c as the location of the heap-based buffer over-read. | |||||