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Total
189 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2021-37660 | 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 floating point exception by calling inplace operations with crafted arguments that would result in a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/inplace_ops.cc#L283) has a logic error: it should skip processing if `x` and `v` are empty but the code uses `||` instead of `&&`. We have patched the issue in GitHub commit e86605c0a336c088b638da02135ea6f9f6753618. 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-2021-37653 | 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 trigger a crash via a floating point exception in `tf.raw_ops.ResourceGather`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L725-L731) computes the value of a value, `batch_size`, and then divides by it without checking that this value is not 0. We have patched the issue in GitHub commit ac117ee8a8ea57b73d34665cdf00ef3303bc0b11. 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-2016-9921 | 3 Debian, Qemu, Redhat | 5 Debian Linux, Qemu, Enterprise Linux and 2 more | 2021-08-04 | 2.1 LOW | 6.5 MEDIUM |
| Quick emulator (Qemu) built with the Cirrus CLGD 54xx VGA Emulator support is vulnerable to a divide by zero issue. It could occur while copying VGA data when cirrus graphics mode was set to be VGA. A privileged user inside guest could use this flaw to crash the Qemu process instance on the host, resulting in DoS. | |||||
| CVE-2016-8669 | 4 Debian, Opensuse, Qemu and 1 more | 6 Debian Linux, Leap, Qemu and 3 more | 2021-08-04 | 2.1 LOW | 6.0 MEDIUM |
| The serial_update_parameters function in hw/char/serial.c in QEMU (aka Quick Emulator) allows local guest OS administrators to cause a denial of service (divide-by-zero error and QEMU process crash) via vectors involving a value of divider greater than baud base. | |||||
| CVE-2019-16168 | 7 Canonical, Debian, Fedoraproject and 4 more | 19 Ubuntu Linux, Debian Linux, Fedora and 16 more | 2021-07-31 | 4.3 MEDIUM | 6.5 MEDIUM |
| In SQLite through 3.29.0, whereLoopAddBtreeIndex in sqlite3.c can crash a browser or other application because of missing validation of a sqlite_stat1 sz field, aka a "severe division by zero in the query planner." | |||||
| CVE-2021-27847 | 1 Libvips Project | 1 Libvips | 2021-07-28 | 4.3 MEDIUM | 6.5 MEDIUM |
| Division-By-Zero vulnerability in Libvips 8.10.5 in the function vips_eye_point, eye.c#L83, and function vips_mask_point, mask.c#L85. | |||||
| CVE-2021-29538 | 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. An attacker can cause a division by zero to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L513-L522) computes a divisor based on user provided data (i.e., the shape of the tensors given as arguments). If all shapes are empty then `work_unit_size` is 0. Since there is no check for this case before division, this results in a runtime exception, with potential to be abused for a denial of service. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29549 | 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. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29550 | 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. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29556 | 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. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.Reverse`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/36229ea9e9451dac14a8b1f4711c435a1d84a594/tensorflow/core/kernels/reverse_op.cc#L75-L76) performs a division based on the first dimension of the tensor argument. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-34069 | 1 Tsmuxer Project | 1 Tsmuxer | 2021-06-28 | 4.3 MEDIUM | 5.5 MEDIUM |
| Divide-by-zero bug in tsMuxer 2.6.16 allows attackers to cause a Denial of Service (DoS) by running the application with a crafted file. | |||||
| CVE-2020-27756 | 1 Imagemagick | 1 Imagemagick | 2021-06-02 | 4.3 MEDIUM | 5.5 MEDIUM |
| In ParseMetaGeometry() of MagickCore/geometry.c, image height and width calculations can lead to divide-by-zero conditions which also lead to undefined behavior. This flaw can be triggered by a crafted input file processed by ImageMagick and could impact application availability. The patch uses multiplication in addition to the function `PerceptibleReciprocal()` in order to prevent such divide-by-zero conditions. This flaw affects ImageMagick versions prior to 7.0.9-0. | |||||
| CVE-2020-27750 | 2 Debian, Imagemagick | 2 Debian Linux, Imagemagick | 2021-06-02 | 4.3 MEDIUM | 5.5 MEDIUM |
| A flaw was found in ImageMagick in MagickCore/colorspace-private.h and MagickCore/quantum.h. An attacker who submits a crafted file that is processed by ImageMagick could trigger undefined behavior in the form of values outside the range of type `unsigned char` and math division by zero. This would most likely lead to an impact to application availability, but could potentially cause other problems related to undefined behavior. This flaw affects ImageMagick versions prior to 7.0.8-68. | |||||
| CVE-2020-27760 | 2 Debian, Imagemagick | 2 Debian Linux, Imagemagick | 2021-06-02 | 4.3 MEDIUM | 5.5 MEDIUM |
| In `GammaImage()` of /MagickCore/enhance.c, depending on the `gamma` value, it's possible to trigger a divide-by-zero condition when a crafted input file is processed by ImageMagick. This could lead to an impact to application availability. The patch uses the `PerceptibleReciprocal()` to prevent the divide-by-zero from occurring. This flaw affects ImageMagick versions prior to ImageMagick 7.0.8-68. | |||||
| CVE-2021-20176 | 2 Debian, Imagemagick | 2 Debian Linux, Imagemagick | 2021-06-02 | 4.3 MEDIUM | 5.5 MEDIUM |
| A divide-by-zero flaw was found in ImageMagick 6.9.11-57 and 7.0.10-57 in gem.c. This flaw allows an attacker who submits a crafted file that is processed by ImageMagick to trigger undefined behavior through a division by zero. The highest threat from this vulnerability is to system availability. | |||||
| CVE-2020-20264 | 1 Mikrotik | 1 Routeros | 2021-06-01 | 4.0 MEDIUM | 6.5 MEDIUM |
| Mikrotik RouterOs before 6.47 (stable tree) in the /ram/pckg/advanced-tools/nova/bin/netwatch process. An authenticated remote attacker can cause a Denial of Service due to a divide by zero error. | |||||
| CVE-2020-20448 | 1 Ffmpeg | 1 Ffmpeg | 2021-05-27 | 4.0 MEDIUM | 6.5 MEDIUM |
| FFmpeg 4.1.3 is affected by a Divide By Zero issue via libavcodec/ratecontrol.c, which allows a remote malicious user to cause a Denial of Service. | |||||
| CVE-2020-20253 | 1 Mikrotik | 1 Routeros | 2021-05-25 | 4.0 MEDIUM | 6.5 MEDIUM |
| Mikrotik RouterOs before 6.47 (stable tree) suffers from a divison by zero vulnerability in the /nova/bin/lcdstat process. An authenticated remote attacker can cause a Denial of Service due to a divide by zero error. | |||||
| CVE-2021-29522 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero. Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29517 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. A malicious user could trigger a division by 0 in `Conv3D` implementation. The implementation(https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv_ops_3d.cc#L143-L145) does a modulo operation based on user controlled input. Thus, when `filter` has a 0 as the fifth element, this results in a division by 0. Additionally, if the shape of the two tensors is not valid, an Eigen assertion can be triggered, resulting in a program crash. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29524 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/496c2630e51c1a478f095b084329acedb253db6b/tensorflow/core/kernels/conv_grad_shape_utils.cc#L130) does a modulus operation where the divisor is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29526 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29528 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29554 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected. | |||||
| CVE-2021-29527 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedConv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/00e9a4d67d76703fa1aee33dac582acf317e0e81/tensorflow/core/kernels/quantized_conv_ops.cc#L257-L259) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29548 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the op's contract(https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization). The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29573 | 1 Google | 1 Tensorflow | 2021-05-20 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` is vulnerable to a division by 0. The implementation(https://github.com/tensorflow/tensorflow/blob/279bab6efa22752a2827621b7edb56a730233bd8/tensorflow/core/kernels/maxpooling_op.cc#L1033-L1034) fails to validate that the batch dimension of the tensor is non-zero, before dividing by this quantity. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29557 | 1 Google | 1 Tensorflow | 2021-05-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.SparseMatMul`. The division by 0 occurs deep in Eigen code because the `b` tensor is empty. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29555 | 1 Google | 1 Tensorflow | 2021-05-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.FusedBatchNorm`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/828f346274841fa7505f7020e88ca36c22e557ab/tensorflow/core/kernels/fused_batch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor. Since this is controlled by the user, an attacker can trigger a denial of service. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29602 | 1 Google | 1 Tensorflow | 2021-05-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `DepthwiseConv` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.cc#L287-L288). An attacker can craft a model such that `input`'s fourth dimension would be 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-29604 | 1 Google | 1 Tensorflow | 2021-05-18 | 2.1 LOW | 5.5 MEDIUM |
| TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of hashtable lookup is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/hashtable_lookup.cc#L114-L115) An attacker can craft a model such that `values`'s first dimension would be 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | |||||
| CVE-2021-20205 | 2 Fedoraproject, Libjpeg-turbo | 2 Fedora, Libjpeg-turbo | 2021-05-04 | 4.3 MEDIUM | 6.5 MEDIUM |
| Libjpeg-turbo versions 2.0.91 and 2.0.90 is vulnerable to a denial of service vulnerability caused by a divide by zero when processing a crafted GIF image. | |||||
| CVE-2021-28856 | 1 Entropymine | 1 Deark | 2021-04-21 | 4.3 MEDIUM | 5.5 MEDIUM |
| In Deark before v1.5.8, a specially crafted input file can cause a division by zero in (src/fmtutil.c) because of the value of pixelsize. | |||||
| CVE-2021-20246 | 4 Debian, Fedoraproject, Imagemagick and 1 more | 4 Debian Linux, Fedora, Imagemagick and 1 more | 2021-03-25 | 7.1 HIGH | 5.5 MEDIUM |
| A flaw was found in ImageMagick in MagickCore/resample.c. An attacker who submits a crafted file that is processed by ImageMagick could trigger undefined behavior in the form of math division by zero. The highest threat from this vulnerability is to system availability. | |||||
| CVE-2021-20244 | 4 Debian, Fedoraproject, Imagemagick and 1 more | 4 Debian Linux, Fedora, Imagemagick and 1 more | 2021-03-25 | 7.1 HIGH | 5.5 MEDIUM |
| A flaw was found in ImageMagick in MagickCore/visual-effects.c. An attacker who submits a crafted file that is processed by ImageMagick could trigger undefined behavior in the form of math division by zero. The highest threat from this vulnerability is to system availability. | |||||
| CVE-2021-20241 | 2 Debian, Imagemagick | 2 Debian Linux, Imagemagick | 2021-03-25 | 4.3 MEDIUM | 5.5 MEDIUM |
| A flaw was found in ImageMagick in coders/jp2.c. An attacker who submits a crafted file that is processed by ImageMagick could trigger undefined behavior in the form of math division by zero. The highest threat from this vulnerability is to system availability. | |||||
| CVE-2021-25675 | 1 Siemens | 1 Simatic S7-plcsim | 2021-03-18 | 2.1 LOW | 5.5 MEDIUM |
| A vulnerability has been identified in SIMATIC S7-PLCSIM V5.4 (All versions). An attacker with local access to the system could cause a Denial-of-Service condition in the application when it is used to open a specially crafted file. As a consequence, a divide by zero operation could occur and cause the application to terminate unexpectedly and must be restarted to restore the service. | |||||
| CVE-2021-27550 | 1 Polarisoffice | 1 Polaris Office | 2021-02-26 | 4.3 MEDIUM | 5.5 MEDIUM |
| Polaris Office v9.102.66 is affected by a divide-by-zero error in PolarisOffice.exe and EngineDLL.dll that may cause a local denial of service. To exploit the vulnerability, someone must open a crafted PDF file. | |||||
| CVE-2020-12371 | 1 Intel | 1 Graphics Drivers | 2021-02-22 | 2.1 LOW | 5.5 MEDIUM |
| Divide by zero in some Intel(R) Graphics Drivers before version 26.20.100.8141 may allow a privileged user to potentially enable a denial of service via local access. | |||||
| CVE-2018-14395 | 2 Debian, Ffmpeg | 2 Debian Linux, Ffmpeg | 2021-02-05 | 4.3 MEDIUM | 6.5 MEDIUM |
| libavformat/movenc.c in FFmpeg 3.2 and 4.0.2 allows attackers to cause a denial of service (application crash caused by a divide-by-zero error) with a user crafted audio file when converting to the MOV audio format. | |||||
| CVE-2019-1010315 | 1 Wavpack | 1 Wavpack | 2021-01-15 | 4.3 MEDIUM | 5.5 MEDIUM |
| WavPack 5.1 and earlier is affected by: CWE 369: Divide by Zero. The impact is: Divide by zero can lead to sudden crash of a software/service that tries to parse a .wav file. The component is: ParseDsdiffHeaderConfig (dsdiff.c:282). The attack vector is: Maliciously crafted .wav file. The fixed version is: After commit https://github.com/dbry/WavPack/commit/4c0faba32fddbd0745cbfaf1e1aeb3da5d35b9fc. | |||||
| CVE-2018-11212 | 7 Canonical, Debian, Ijg and 4 more | 13 Ubuntu Linux, Debian Linux, Libjpeg and 10 more | 2021-01-07 | 4.3 MEDIUM | 6.5 MEDIUM |
| An issue was discovered in libjpeg 9a and 9d. The alloc_sarray function in jmemmgr.c allows remote attackers to cause a denial of service (divide-by-zero error) via a crafted file. | |||||
| CVE-2016-10053 | 1 Imagemagick | 1 Imagemagick | 2020-11-16 | 4.3 MEDIUM | 5.5 MEDIUM |
| The WriteTIFFImage function in coders/tiff.c in ImageMagick before 6.9.5-8 allows remote attackers to cause a denial of service (divide-by-zero error and application crash) via a crafted file. | |||||
| CVE-2016-9922 | 1 Qemu | 1 Qemu | 2020-11-10 | 2.1 LOW | 5.5 MEDIUM |
| The cirrus_do_copy function in hw/display/cirrus_vga.c in QEMU (aka Quick Emulator), when cirrus graphics mode is VGA, allows local guest OS privileged users to cause a denial of service (divide-by-zero error and QEMU process crash) via vectors involving blit pitch values. | |||||
| CVE-2017-17381 | 2 Debian, Qemu | 2 Debian Linux, Qemu | 2020-11-10 | 2.1 LOW | 6.5 MEDIUM |
| The Virtio Vring implementation in QEMU allows local OS guest users to cause a denial of service (divide-by-zero error and QEMU process crash) by unsetting vring alignment while updating Virtio rings. | |||||
| CVE-2019-10018 | 1 Xpdfreader | 1 Xpdf | 2020-11-09 | 4.3 MEDIUM | 5.5 MEDIUM |
| An issue was discovered in Xpdf 4.01.01. There is an FPE in the function PostScriptFunction::exec at Function.cc for the psOpIdiv case. | |||||
| CVE-2017-14634 | 2 Debian, Libsndfile Project | 2 Debian Linux, Libsndfile | 2020-10-29 | 4.3 MEDIUM | 6.5 MEDIUM |
| In libsndfile 1.0.28, a divide-by-zero error exists in the function double64_init() in double64.c, which may lead to DoS when playing a crafted audio file. | |||||
| CVE-2016-8667 | 3 Debian, Opensuse, Qemu | 3 Debian Linux, Leap, Qemu | 2020-10-21 | 2.1 LOW | 6.0 MEDIUM |
| The rc4030_write function in hw/dma/rc4030.c in QEMU (aka Quick Emulator) allows local guest OS administrators to cause a denial of service (divide-by-zero error and QEMU process crash) via a large interval timer reload value. | |||||
| CVE-2018-19872 | 3 Fedoraproject, Opensuse, Qt | 3 Fedora, Leap, Qt | 2020-09-28 | 4.3 MEDIUM | 5.5 MEDIUM |
| An issue was discovered in Qt 5.11. A malformed PPM image causes a division by zero and a crash in qppmhandler.cpp. | |||||
| CVE-2016-10506 | 1 Uclouvain | 1 Openjpeg | 2020-09-09 | 4.3 MEDIUM | 6.5 MEDIUM |
| Division-by-zero vulnerabilities in the functions opj_pi_next_cprl, opj_pi_next_pcrl, and opj_pi_next_rpcl in pi.c in OpenJPEG before 2.2.0 allow remote attackers to cause a denial of service (application crash) via crafted j2k files. | |||||