Total
391 CVE
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2021-42389 | 1 Clickhouse | 1 Clickhouse | 2025-06-25 | 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-2024-56073 | 1 Pavel-odintsov | 1 Fastnetmon | 2025-06-20 | 7.5 High |
| An issue was discovered in FastNetMon Community Edition through 1.2.7. Zero-length templates for Netflow v9 allow remote attackers to cause a denial of service (divide-by-zero error and application crash). | ||||
| CVE-2024-26774 | 2 Linux, Redhat | 2 Linux Kernel, Enterprise Linux | 2025-06-19 | 5.5 Medium |
| In the Linux kernel, the following vulnerability has been resolved: ext4: avoid dividing by 0 in mb_update_avg_fragment_size() when block bitmap corrupt Determine if bb_fragments is 0 instead of determining bb_free to eliminate the risk of dividing by zero when the block bitmap is corrupted. | ||||
| CVE-2025-38072 | 1 Linux | 1 Linux Kernel | 2025-06-18 | 4.1 Medium |
| In the Linux kernel, the following vulnerability has been resolved: libnvdimm/labels: Fix divide error in nd_label_data_init() If a faulty CXL memory device returns a broken zero LSA size in its memory device information (Identify Memory Device (Opcode 4000h), CXL spec. 3.1, 8.2.9.9.1.1), a divide error occurs in the libnvdimm driver: Oops: divide error: 0000 [#1] PREEMPT SMP NOPTI RIP: 0010:nd_label_data_init+0x10e/0x800 [libnvdimm] Code and flow: 1) CXL Command 4000h returns LSA size = 0 2) config_size is assigned to zero LSA size (CXL pmem driver): drivers/cxl/pmem.c: .config_size = mds->lsa_size, 3) max_xfer is set to zero (nvdimm driver): drivers/nvdimm/label.c: max_xfer = min_t(size_t, ndd->nsarea.max_xfer, config_size); 4) A subsequent DIV_ROUND_UP() causes a division by zero: drivers/nvdimm/label.c: /* Make our initial read size a multiple of max_xfer size */ drivers/nvdimm/label.c: read_size = min(DIV_ROUND_UP(read_size, max_xfer) * max_xfer, drivers/nvdimm/label.c- config_size); Fix this by checking the config size parameter by extending an existing check. | ||||
| CVE-2023-52313 | 1 Paddlepaddle | 1 Paddlepaddle | 2025-06-17 | 4.7 Medium |
| FPE in paddle.argmin and paddle.argmax in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service. | ||||
| CVE-2023-46849 | 3 Debian, Fedoraproject, Openvpn | 4 Debian Linux, Fedora, Openvpn and 1 more | 2025-06-11 | 7.5 High |
| Using the --fragment option in certain configuration setups OpenVPN version 2.6.0 to 2.6.6 allows an attacker to trigger a divide by zero behaviour which could cause an application crash, leading to a denial of service. | ||||
| CVE-2023-38674 | 1 Paddlepaddle | 1 Paddlepaddle | 2025-06-06 | 4.7 Medium |
| FPE in paddle.nanmedian in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service. | ||||
| CVE-2023-52305 | 1 Paddlepaddle | 1 Paddlepaddle | 2025-06-03 | 4.7 Medium |
| FPE in paddle.topk in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service. | ||||
| CVE-2023-52306 | 1 Paddlepaddle | 1 Paddlepaddle | 2025-06-03 | 4.7 Medium |
| FPE in paddle.lerp in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service. | ||||
| CVE-2025-48754 | 2025-05-28 | 2.9 Low | ||
| In the memory_pages crate 0.1.0 for Rust, division by zero can occur. | ||||
| CVE-2023-38675 | 1 Paddlepaddle | 1 Paddlepaddle | 2025-05-21 | 4.7 Medium |
| FPE in paddle.linalg.matrix_rank in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service. | ||||
| CVE-2025-4637 | 2025-05-16 | N/A | ||
| Divide By Zero vulnerability in davisking dlib allows remote attackers to cause a denial of service via a crafted file. .This issue affects dlib: before <19.24.7. | ||||
| CVE-2024-57598 | 1 Axiosys | 1 Bento4 | 2025-05-15 | 6.5 Medium |
| A floating point exception (divide-by-zero) vulnerability was discovered in Bento4 1.6.0-641 in function AP4_TfraAtom() of Ap4TfraAtom.cpp which allows a remote attacker to cause a denial of service vulnerability. | ||||
| CVE-2024-8063 | 1 Ollama | 1 Ollama | 2025-05-13 | 7.5 High |
| A divide by zero vulnerability exists in ollama/ollama version v0.3.3. The vulnerability occurs when importing GGUF models with a crafted type for `block_count` in the Modelfile. This can lead to a denial of service (DoS) condition when the server processes the model, causing it to crash. | ||||
| CVE-2023-52308 | 1 Paddlepaddle | 1 Paddlepaddle | 2025-05-09 | 4.7 Medium |
| FPE in paddle.amin in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service. | ||||
| CVE-2022-21741 | 1 Google | 1 Tensorflow | 2025-05-05 | 6.5 Medium |
| Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | ||||
| CVE-2022-21735 | 1 Google | 1 Tensorflow | 2025-05-05 | 6.5 Medium |
| Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalMaxPool` can be made to crash a TensorFlow process via a division by 0. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | ||||
| CVE-2022-21725 | 1 Google | 1 Tensorflow | 2025-05-05 | 6.5 Medium |
| Tensorflow is an Open Source Machine Learning Framework. The estimator for the cost of some convolution operations can be made to execute a division by 0. The function fails to check that the stride argument is strictly positive. Hence, the fix is to add a check for the stride argument to ensure it is valid. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | ||||
| CVE-2025-21898 | 1 Linux | 1 Linux Kernel | 2025-05-04 | 5.5 Medium |
| In the Linux kernel, the following vulnerability has been resolved: ftrace: Avoid potential division by zero in function_stat_show() Check whether denominator expression x * (x - 1) * 1000 mod {2^32, 2^64} produce zero and skip stddev computation in that case. For now don't care about rec->counter * rec->counter overflow because rec->time * rec->time overflow will likely happen earlier. | ||||
| CVE-2024-49977 | 2 Linux, Redhat | 2 Linux Kernel, Enterprise Linux | 2025-05-04 | 5.5 Medium |
| In the Linux kernel, the following vulnerability has been resolved: net: stmmac: Fix zero-division error when disabling tc cbs The commit b8c43360f6e4 ("net: stmmac: No need to calculate speed divider when offload is disabled") allows the "port_transmit_rate_kbps" to be set to a value of 0, which is then passed to the "div_s64" function when tc-cbs is disabled. This leads to a zero-division error. When tc-cbs is disabled, the idleslope, sendslope, and credit values the credit values are not required to be configured. Therefore, adding a return statement after setting the txQ mode to DCB when tc-cbs is disabled would prevent a zero-division error. | ||||