Total
381 CVE
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2021-4216 | 1 Artifex | 1 Mupdf | 2024-11-21 | 5.5 Medium |
| A Floating point exception (division-by-zero) flaw was found in Mupdf for zero width pages in muraster.c. It is fixed in Mupdf-1.20.0-rc1 upstream. | ||||
| CVE-2021-46312 | 1 Djvulibre Project | 1 Djvulibre | 2024-11-21 | 6.5 Medium |
| An issue was discovered IW44EncodeCodec.cpp in djvulibre 3.5.28 in allows attackers to cause a denial of service via divide by zero. | ||||
| CVE-2021-46310 | 1 Djvulibre Project | 1 Djvulibre | 2024-11-21 | 6.5 Medium |
| An issue was discovered IW44Image.cpp in djvulibre 3.5.28 in allows attackers to cause a denial of service via divide by zero. | ||||
| CVE-2021-46244 | 1 Hdfgroup | 1 Hdf5 | 2024-11-21 | 6.5 Medium |
| A Divide By Zero vulnerability exists in HDF5 v1.13.1-1 vis the function H5T__complete_copy () at /hdf5/src/H5T.c. This vulnerability causes an aritmetic exception, leading to a Denial of Service (DoS). | ||||
| CVE-2021-44917 | 1 Gnuplot | 1 Gnuplot | 2024-11-21 | 5.5 Medium |
| A Divide by Zero vulnerability exists in gnuplot 5.4 in the boundary3d function in graph3d.c, which could cause a Arithmetic exception and application crash. | ||||
| CVE-2021-44500 | 1 Fisglobal | 1 Gt.m | 2024-11-21 | 7.5 High |
| An issue was discovered in FIS GT.M through V7.0-000 (related to the YottaDB code base). A lack of input validation in calls to eb_div in sr_port/eb_muldiv.c allows attackers to crash the application by performing a divide by zero. | ||||
| CVE-2021-42391 | 1 Yandex | 1 Clickhouse | 2024-11-21 | 6.5 Medium |
| Divide-by-zero in Clickhouse's Gorilla compression codec when parsing a malicious query. The first byte of the compressed buffer is used in a modulo operation without being checked for 0. | ||||
| CVE-2021-42390 | 1 Yandex | 1 Clickhouse | 2024-11-21 | 6.5 Medium |
| Divide-by-zero in Clickhouse's DeltaDouble compression codec when parsing a malicious query. The first byte of the compressed buffer is used in a modulo operation without being checked for 0. | ||||
| CVE-2021-42389 | 1 Yandex | 1 Clickhouse | 2024-11-21 | 6.5 Medium |
| Divide-by-zero in Clickhouse's Delta compression codec when parsing a malicious query. The first byte of the compressed buffer is used in a modulo operation without being checked for 0. | ||||
| CVE-2021-41218 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.5 Medium |
| TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `AllToAll` can be made to execute a division by 0. This occurs whenever the `split_count` argument is 0. 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-2021-41209 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.5 Medium |
| TensorFlow is an open source platform for machine learning. In affected versions the implementations for convolution operators trigger a division by 0 if passed empty filter tensor arguments. 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-2021-41207 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.5 Medium |
| TensorFlow is an open source platform for machine learning. In affected versions the implementation of `ParallelConcat` misses some input validation and can produce a division by 0. 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-2021-40211 | 2 Imagemagick, Redhat | 2 Imagemagick, Enterprise Linux | 2024-11-21 | 7.5 High |
| An issue was discovered with ImageMagick 7.1.0-4 via Division by zero in function ReadEnhMetaFile of coders/emf.c. | ||||
| CVE-2021-3941 | 4 Debian, Fedoraproject, Openexr and 1 more | 4 Debian Linux, Fedora, Openexr and 1 more | 2024-11-21 | 6.5 Medium |
| In ImfChromaticities.cpp routine RGBtoXYZ(), there are some division operations such as `float Z = (1 - chroma.white.x - chroma.white.y) * Y / chroma.white.y;` and `chroma.green.y * (X + Z))) / d;` but the divisor is not checked for a 0 value. A specially crafted file could trigger a divide-by-zero condition which could affect the availability of programs linked with OpenEXR. | ||||
| CVE-2021-3432 | 1 Zephyrproject | 1 Zephyr | 2024-11-21 | 4.3 Medium |
| Invalid interval in CONNECT_IND leads to Division by Zero. Zephyr versions >= v1.14.0 Divide By Zero (CWE-369). For more information, see https://github.com/zephyrproject-rtos/zephyr/security/advisories/GHSA-7364-p4wc-8mj4 | ||||
| CVE-2021-37691 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a division by zero error in LSH [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/lsh_projection.cc#L118). We have patched the issue in GitHub commit 0575b640091680cfb70f4dd93e70658de43b94f9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick thiscommit 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-2021-37684 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementations of pooling in TFLite are vulnerable to division by 0 errors as there are no checks for divisors not being 0. We have patched the issue in GitHub commit [dfa22b348b70bb89d6d6ec0ff53973bacb4f4695](https://github.com/tensorflow/tensorflow/commit/dfa22b348b70bb89d6d6ec0ff53973bacb4f4695). 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-2021-37683 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc). There is no check that the divisor tensor does not contain zero elements. We have patched the issue in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. 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-2021-37680 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of fully connected layers in TFLite is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226). We have patched the issue in GitHub commit 718721986aa137691ee23f03638867151f74935f. 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-2021-37675 | 1 Google | 1 Tensorflow | 2024-11-21 | 5.5 Medium |
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. 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. | ||||