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Total
265 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| 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-2021-29600 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `OneHot` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/f61c57bd425878be108ec787f4d96390579fb83e/tensorflow/lite/kernels/one_hot.cc#L68-L72). An attacker can craft a model such that at least one of the dimensions of `indices` would be 0. In turn, the `prefix_dim_size` value would become 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-2021-29586 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling `ComputePaddingHeightWidth`(https://github.com/tensorflow/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90). Since users can craft special models which will have `params->stride_{height,width}` be zero, this will result in a division by zero. 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-2021-29525 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b40060c9f697b044e3107917c797ba052f4506ab/tensorflow/core/kernels/conv_grad_input_ops.h#L625-L655) 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-2021-29597 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `SpaceToBatchNd` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/412c7d9bb8f8a762c5b266c9e73bfa165f29aac8/tensorflow/lite/kernels/space_to_batch_nd.cc#L82-L83). An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` 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-2021-29598 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `SVDF` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/7f283ff806b2031f407db64c4d3edcda8fb9f9f5/tensorflow/lite/kernels/svdf.cc#L99-L102). An attacker can craft a model such that `params->rank` 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-2021-29594 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. TFLite's convolution code(https://github.com/tensorflow/tensorflow/blob/09c73bca7d648e961dd05898292d91a8322a9d45/tensorflow/lite/kernels/conv.cc) has multiple division where the divisor is controlled by the user and not checked to be non-zero. 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-2021-29593 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `BatchToSpaceNd` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/b5ed552fe55895aee8bd8b191f744a069957d18d/tensorflow/lite/kernels/batch_to_space_nd.cc#L81-L82). An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` 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-2021-29596 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `EmbeddingLookup` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/e4b29809543b250bc9b19678ec4776299dd569ba/tensorflow/lite/kernels/embedding_lookup.cc#L73-L74). An attacker can craft a model such that the first dimension of the `value` input 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-2021-29588 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The optimized implementation of the `TransposeConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L5221-L5222). An attacker can craft a model such that `stride_{h,w}` values are 0. Code calling this function must validate these arguments. 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-2021-29599 | 1 Google | 1 Tensorflow | 2021-05-19 | 4.6 MEDIUM | 7.8 HIGH |
| TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `Split` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/e2752089ef7ce9bcf3db0ec618ebd23ea119d0c7/tensorflow/lite/kernels/split.cc#L63-L65). An attacker can craft a model such that `num_splits` 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-2021-29557 | 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-2021-20310 | 1 Imagemagick | 1 Imagemagick | 2021-05-17 | 7.8 HIGH | 7.5 HIGH |
| A flaw was found in ImageMagick in versions before 7.0.11, where a division by zero ConvertXYZToJzazbz() of MagickCore/colorspace.c may trigger undefined behavior via a crafted image file that is submitted by an attacker and processed by an application using ImageMagick. The highest threat from this vulnerability is to system availability. | |||||
| CVE-2021-20311 | 1 Imagemagick | 1 Imagemagick | 2021-05-17 | 7.8 HIGH | 7.5 HIGH |
| A flaw was found in ImageMagick in versions before 7.0.11, where a division by zero in sRGBTransformImage() in the MagickCore/colorspace.c may trigger undefined behavior via a crafted image file that is submitted by an attacker processed by an application using ImageMagick. The highest threat from this vulnerability is to system availability. | |||||
| 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-2020-11145 | 1 Qualcomm | 413 Apq8009, Apq8009w, Apq8017 and 410 more | 2021-01-29 | 5.0 MEDIUM | 7.5 HIGH |
| Divide by zero issue can happen while updating delta extension header due to improper validation of master SN and extension header SN in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables | |||||
| 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-2020-25708 | 2 Libvncserver Project, Redhat | 2 Libvncserver, Enterprise Linux | 2020-12-02 | 5.0 MEDIUM | 7.5 HIGH |
| A divide by zero issue was found to occur in libvncserver-0.9.12. A malicious client could use this flaw to send a specially crafted message that, when processed by the VNC server, would lead to a floating point exception, resulting in a denial of service. | |||||
| CVE-2014-9756 | 3 Canonical, Libsndfile Project, Opensuse | 4 Ubuntu Linux, Libsndfile, Leap and 1 more | 2020-11-20 | 5.0 MEDIUM | N/A |
| The psf_fwrite function in file_io.c in libsndfile allows attackers to cause a denial of service (divide-by-zero error and application crash) via unspecified vectors related to the headindex variable. | |||||
| 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-2019-14494 | 3 Canonical, Fedoraproject, Freedesktop | 3 Ubuntu Linux, Fedora, Poppler | 2020-11-09 | 4.3 MEDIUM | 7.5 HIGH |
| An issue was discovered in Poppler through 0.78.0. There is a divide-by-zero error in the function SplashOutputDev::tilingPatternFill at SplashOutputDev.cc. | |||||
| 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-2020-16161 | 1 Gopro | 1 Gpmf-parser | 2020-10-29 | 5.0 MEDIUM | 7.5 HIGH |
| GoPro gpmf-parser 1.5 has a division-by-zero vulnerability in GPMF_ScaledData(). Parsing malicious input can result in a crash. | |||||
| CVE-2020-16160 | 1 Gopro | 1 Gpmf-parser | 2020-10-29 | 5.0 MEDIUM | 7.5 HIGH |
| GoPro gpmf-parser 1.5 has a division-by-zero vulnerability in GPMF_Decompress(). Parsing malicious input can result in a crash. | |||||