CWE-369
AllowedDivide By Zero
Abstraction: Base · Status: Draft
The product divides a value by zero.
609 vulnerabilities reference this CWE, most recent first.
CVE-2019-5637 (GCVE-0-2019-5637)
Vulnerability from cvelistv5 – Published: 2019-11-21 19:16 – Updated: 2024-09-17 01:35- CWE-369 - Divide By Zero
| URL | Tags |
|---|---|
| https://blog.rapid7.com/2019/10/08/r7-2019-32-den… | x_refsource_MISC |
| https://download.beckhoff.com/download/Document/p… | x_refsource_CONFIRM |
| Vendor | Product | Version | |
|---|---|---|---|
| Beckhoff | TwinCAT 2 |
Affected:
2304 , ≤ 2304
(custom)
|
|
| Beckhoff | TwinCAT 3.1 |
Affected:
4204.0 , ≤ 4204.0
(custom)
|
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GHSA-22FX-6R9M-R8H9
Vulnerability from github – Published: 2023-05-05 18:30 – Updated: 2025-01-29 22:00A Segmentation fault caused by a floating point exception exists in libheif 1.15.1 using crafted heif images via the heif::Fraction::round() function in box.cc, which causes a denial of service.
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GHSA-22G8-27FC-WWMW
Vulnerability from github – Published: 2026-07-16 21:30 – Updated: 2026-07-16 21:30A divide-by-zero vulnerability in the Productivity Suite allows a local attacker to cause a division by zero leading to a system crash.
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"id": "GHSA-22g8-27fc-wwmw",
"modified": "2026-07-16T21:30:39Z",
"published": "2026-07-16T21:30:39Z",
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"url": "https://github.com/cisagov/CSAF/blob/develop/csaf_files/OT/white/2026/icsa-26-197-04.json"
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"type": "WEB",
"url": "https://www.automationdirect.com/support/software-downloads"
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GHSA-22JV-7GJ6-846J
Vulnerability from github – Published: 2023-04-24 06:31 – Updated: 2024-03-25 03:31An issue was discovered in drivers/mtd/ubi/cdev.c in the Linux kernel 6.2. There is a divide-by-zero error in do_div(sz,mtd->erasesize), used indirectly by ctrl_cdev_ioctl, when mtd->erasesize is 0.
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"modified": "2024-03-25T03:31:43Z",
"published": "2023-04-24T06:31:20Z",
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},
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"type": "WEB",
"url": "https://security.netapp.com/advisory/ntap-20230929-0003"
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GHSA-2454-3WFW-H893
Vulnerability from github – Published: 2022-05-14 01:27 – Updated: 2025-04-20 03:41The startread function in wav.c in Sound eXchange (SoX) 14.4.2 allows remote attackers to cause a denial of service (divide-by-zero error and application crash) via a crafted wav file.
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"id": "GHSA-2454-3wfw-h893",
"modified": "2025-04-20T03:41:40Z",
"published": "2022-05-14T01:27:34Z",
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"type": "ADVISORY",
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"url": "https://lists.debian.org/debian-lts-announce/2017/11/msg00043.html"
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"url": "https://lists.debian.org/debian-lts-announce/2019/03/msg00007.html"
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"url": "https://security.gentoo.org/glsa/201810-02"
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"url": "https://www.exploit-db.com/exploits/42398"
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GHSA-248Q-W8JQ-JXJ9
Vulnerability from github – Published: 2026-07-28 15:32 – Updated: 2026-07-28 18:33The logic to handle periodic Viridian STIMERs performs a division with an unchecked user-controlled divisor value, that can be set to zero to cause a #DE fault.
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"details": "The logic to handle periodic Viridian STIMERs performs a division with an\nunchecked user-controlled divisor value, that can be set to zero to cause a #DE\nfault.",
"id": "GHSA-248q-w8jq-jxj9",
"modified": "2026-07-28T18:33:02Z",
"published": "2026-07-28T15:32:17Z",
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"url": "https://xenbits.xenproject.org/xsa/advisory-504.html"
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"url": "http://www.openwall.com/lists/oss-security/2026/07/28/20"
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GHSA-269W-VFJC-88W7
Vulnerability from github – Published: 2022-05-24 19:02 – Updated: 2022-05-24 19:02Mikrotik 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.
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"details": "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.",
"id": "GHSA-269w-vfjc-88w7",
"modified": "2022-05-24T19:02:48Z",
"published": "2022-05-24T19:02:48Z",
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{
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"url": "https://github.com/cq674350529/pocs_slides/blob/master/pocs/MikroTik/vul_netwatch/README.md"
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"url": "https://seclists.org/fulldisclosure/2021/May/11"
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GHSA-26J7-6W8W-7922
Vulnerability from github – Published: 2021-05-21 14:26 – Updated: 2024-11-13 16:01Impact
Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling ComputePaddingHeightWidth.
Since users can craft special models which will have params->stride_{height,width} be zero, this will result in a division by zero.
Patches
We have patched the issue in GitHub commit 5f7975d09eac0f10ed8a17dbb6f5964977725adc.
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.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
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{
"fixed": "2.3.3"
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],
"type": "ECOSYSTEM"
}
]
},
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},
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},
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},
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},
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}
],
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}
]
}
],
"aliases": [
"CVE-2021-29586"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T17:03:33Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nOptimized 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).\n\nSince users can craft special models which will have `params-\u003estride_{height,width}` be zero, this will result in a division by zero.\n \n### Patches\nWe have patched the issue in GitHub commit [5f7975d09eac0f10ed8a17dbb6f5964977725adc](https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc).\n \nThe 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.\n \n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by members of the Aivul Team from Qihoo 360.",
"id": "GHSA-26j7-6w8w-7922",
"modified": "2024-11-13T16:01:10Z",
"published": "2021-05-21T14:26:43Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-26j7-6w8w-7922"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29586"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-514.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-712.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-223.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Division by zero in optimized pooling implementations in TFLite"
}
GHSA-275C-W5MQ-V5M2
Vulnerability from github – Published: 2024-01-03 09:30 – Updated: 2024-11-22 18:20FPE in paddle.argmin and paddle.argmax in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service.
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"github_reviewed": true,
"github_reviewed_at": "2024-01-03T22:02:51Z",
"nvd_published_at": "2024-01-03T09:15:11Z",
"severity": "MODERATE"
},
"details": "FPE in paddle.argmin and paddle.argmax\u00a0in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service.\n\n\n\n",
"id": "GHSA-275c-w5mq-v5m2",
"modified": "2024-11-22T18:20:23Z",
"published": "2024-01-03T09:30:33Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-52313"
},
{
"type": "WEB",
"url": "https://github.com/PaddlePaddle/Paddle/commit/6ef71779197ad6faf51ac295022ab5008d81372f"
},
{
"type": "PACKAGE",
"url": "https://github.com/PaddlePaddle/Paddle"
},
{
"type": "WEB",
"url": "https://github.com/PaddlePaddle/Paddle/blob/develop/security/advisory/pdsa-2023-022.md"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/paddlepaddle/PYSEC-2024-145.yaml"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:N/I:N/A:L",
"type": "CVSS_V3"
}
],
"summary": "PaddlePaddle floating point exception in paddle.argmin and paddle.argmax"
}
GHSA-27QF-JWM8-G7F3
Vulnerability from github – Published: 2021-08-25 14:39 – Updated: 2024-11-13 21:25Impact
An attacker can craft a TFLite model that would trigger a division by zero error in LSH implementation.
int RunningSignBit(const TfLiteTensor* input, const TfLiteTensor* weight,
float seed) {
int input_item_bytes = input->bytes / SizeOfDimension(input, 0);
// ...
}
There is no check that the first dimension of the input is non zero.
Patches
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.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Yakun Zhang of Baidu Security.
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}
],
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"2.5.0"
]
}
],
"aliases": [
"CVE-2021-37691"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-08-24T18:17:31Z",
"nvd_published_at": "2021-08-12T23:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nAn 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).\n\n```cc\nint RunningSignBit(const TfLiteTensor* input, const TfLiteTensor* weight,\n float seed) {\n int input_item_bytes = input-\u003ebytes / SizeOfDimension(input, 0);\n // ...\n}\n```\n \nThere is no check that the first dimension of the input is non zero.\n \n### Patches\nWe have patched the issue in GitHub commit [0575b640091680cfb70f4dd93e70658de43b94f9](https://github.com/tensorflow/tensorflow/commit/0575b640091680cfb70f4dd93e70658de43b94f9).\n\nThe 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.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Yakun Zhang of Baidu Security.",
"id": "GHSA-27qf-jwm8-g7f3",
"modified": "2024-11-13T21:25:37Z",
"published": "2021-08-25T14:39:17Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-27qf-jwm8-g7f3"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37691"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/0575b640091680cfb70f4dd93e70658de43b94f9"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-604.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-802.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-313.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
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"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "FPE in LSH in TFLite"
}
No mitigation information available for this CWE.
No CAPEC attack patterns related to this CWE.