Common Weakness Enumeration
CWE-369
AllowedDivide By Zero
Abstraction: Base · Status: Draft
The product divides a value by zero.
599 vulnerabilities reference this CWE, most recent first.
GHSA-CC62-FFCM-XV9H
Vulnerability from github – Published: 2022-05-14 01:15 – Updated: 2022-05-14 01:15
VLAI
Details
An issue was discovered in Xpdf 4.01.01. There is an FPE in the function Splash::scaleImageYuXu at Splash.cc for x Bresenham parameters.
Severity
5.5 (Medium)
{
"affected": [],
"aliases": [
"CVE-2019-10020"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2019-03-25T00:29:00Z",
"severity": "MODERATE"
},
"details": "An issue was discovered in Xpdf 4.01.01. There is an FPE in the function Splash::scaleImageYuXu at Splash.cc for x Bresenham parameters.",
"id": "GHSA-cc62-ffcm-xv9h",
"modified": "2022-05-14T01:15:48Z",
"published": "2022-05-14T01:15:48Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2019-10020"
},
{
"type": "WEB",
"url": "https://forum.xpdfreader.com/viewtopic.php?f=3\u0026t=41274"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-CF72-RGJQ-HH5R
Vulnerability from github – Published: 2022-05-02 03:29 – Updated: 2022-05-02 03:29
VLAI
Details
agent/snmp_agent.c in snmpd in net-snmp 5.0.9 in Red Hat Enterprise Linux (RHEL) 3 allows remote attackers to cause a denial of service (daemon crash) via a crafted SNMP GETBULK request that triggers a divide-by-zero error. NOTE: this vulnerability exists because of an incorrect fix for CVE-2008-4309.
{
"affected": [],
"aliases": [
"CVE-2009-1887"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2009-06-26T18:30:00Z",
"severity": "MODERATE"
},
"details": "agent/snmp_agent.c in snmpd in net-snmp 5.0.9 in Red Hat Enterprise Linux (RHEL) 3 allows remote attackers to cause a denial of service (daemon crash) via a crafted SNMP GETBULK request that triggers a divide-by-zero error. NOTE: this vulnerability exists because of an incorrect fix for CVE-2008-4309.",
"id": "GHSA-cf72-rgjq-hh5r",
"modified": "2022-05-02T03:29:36Z",
"published": "2022-05-02T03:29:36Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2009-1887"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=506903"
},
{
"type": "WEB",
"url": "https://oval.cisecurity.org/repository/search/definition/oval%3Aorg.mitre.oval%3Adef%3A8426"
},
{
"type": "WEB",
"url": "https://oval.cisecurity.org/repository/search/definition/oval%3Aorg.mitre.oval%3Adef%3A9716"
},
{
"type": "WEB",
"url": "http://www.mandriva.com/security/advisories?name=MDVSA-2009:156"
},
{
"type": "WEB",
"url": "http://www.redhat.com/support/errata/RHSA-2009-1124.html"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-CFPJ-3Q4C-JHVR
Vulnerability from github – Published: 2021-08-25 14:40 – Updated: 2024-11-13 21:15
VLAI
Summary
Division by zero in TFLite
Details
Impact
The implementation of fully connected layers in TFLite is vulnerable to a division by zero error:
const int batch_size = input_size / filter->dims->data[1];
An attacker can craft a model such that filter->dims->data[1] is 0.
Patches
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.
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. Concurrently, it has also been reported by Yakun Zhang of Baidu Security.
Severity
5.5 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
}
],
"aliases": [
"CVE-2021-37680"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-08-24T16:24:24Z",
"nvd_published_at": "2021-08-12T22:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nThe 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):\n\n```cc\nconst int batch_size = input_size / filter-\u003edims-\u003edata[1];\n```\n\nAn attacker can craft a model such that `filter-\u003edims-\u003edata[1]` is 0.\n\n### Patches\nWe have patched the issue in GitHub commit [718721986aa137691ee23f03638867151f74935f](https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f).\n\nThe 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.\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. Concurrently, it has also been reported by Yakun Zhang of Baidu Security.",
"id": "GHSA-cfpj-3q4c-jhvr",
"modified": "2024-11-13T21:15:32Z",
"published": "2021-08-25T14:40:38Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cfpj-3q4c-jhvr"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37680"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-593.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-791.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-302.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226"
}
],
"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": "Division by zero in TFLite"
}
GHSA-CFX7-2XPC-8W4H
Vulnerability from github – Published: 2021-05-21 14:27 – Updated: 2024-10-31 21:23
VLAI
Summary
Division by zero in TFLite's implementation of `BatchToSpaceNd`
Details
Impact
The implementation of the BatchToSpaceNd TFLite operator is vulnerable to a division by zero error:
TF_LITE_ENSURE_EQ(context, output_batch_size % block_shape[dim], 0);
output_batch_size = output_batch_size / block_shape[dim];
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.
Patches
We have patched the issue in GitHub commit 2c74674348a4708ced58ad6eb1b23354df8ee044.
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.
Severity
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2021-29593"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T15:44:05Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nThe 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):\n\n```cc\nTF_LITE_ENSURE_EQ(context, output_batch_size % block_shape[dim], 0);\noutput_batch_size = output_batch_size / block_shape[dim];\n```\n\nAn attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` is 0.\n\n### Patches\nWe have patched the issue in GitHub commit [2c74674348a4708ced58ad6eb1b23354df8ee044](https://github.com/tensorflow/tensorflow/commit/2c74674348a4708ced58ad6eb1b23354df8ee044).\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-cfx7-2xpc-8w4h",
"modified": "2024-10-31T21:23:54Z",
"published": "2021-05-21T14:27:01Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cfx7-2xpc-8w4h"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29593"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/2c74674348a4708ced58ad6eb1b23354df8ee044"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-521.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-719.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-230.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/b5ed552fe55895aee8bd8b191f744a069957d18d/tensorflow/lite/kernels/batch_to_space_nd.cc#L81-L82"
}
],
"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:L/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 TFLite\u0027s implementation of `BatchToSpaceNd`"
}
GHSA-CGCG-9VHG-7FQ9
Vulnerability from github – Published: 2022-05-17 00:28 – Updated: 2022-05-17 00:28
VLAI
Details
QEMU, possibly before 2.0.0, allows local users to cause a denial of service (divide-by-zero error and crash) via a zero value in the (1) tracks field to the seek_to_sector function in block/parallels.c or (2) extent_size field in the bochs function in block/bochs.c.
Severity
5.5 (Medium)
{
"affected": [],
"aliases": [
"CVE-2014-0142"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2017-08-10T15:29:00Z",
"severity": "MODERATE"
},
"details": "QEMU, possibly before 2.0.0, allows local users to cause a denial of service (divide-by-zero error and crash) via a zero value in the (1) tracks field to the seek_to_sector function in block/parallels.c or (2) extent_size field in the bochs function in block/bochs.c.",
"id": "GHSA-cgcg-9vhg-7fq9",
"modified": "2022-05-17T00:28:35Z",
"published": "2022-05-17T00:28:35Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2014-0142"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHSA-2014:0420"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHSA-2014:0421"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHSA-2014:0434"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHSA-2014:0435"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHSA-2014:0674"
},
{
"type": "WEB",
"url": "https://access.redhat.com/security/cve/CVE-2014-0142"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=1078201"
},
{
"type": "WEB",
"url": "http://git.qemu.org/?p=qemu.git%3Ba=commitdiff%3Bh=8e53abbc20d08ae3ec30c2054e1161314ad9501d"
},
{
"type": "WEB",
"url": "http://git.qemu.org/?p=qemu.git%3Ba=commitdiff%3Bh=9302e863aa8baa5d932fc078967050c055fa1a7f"
},
{
"type": "WEB",
"url": "http://git.qemu.org/?p=qemu.git;a=commitdiff;h=8e53abbc20d08ae3ec30c2054e1161314ad9501d"
},
{
"type": "WEB",
"url": "http://git.qemu.org/?p=qemu.git;a=commitdiff;h=9302e863aa8baa5d932fc078967050c055fa1a7f"
},
{
"type": "WEB",
"url": "http://rhn.redhat.com/errata/RHSA-2014-0420.html"
},
{
"type": "WEB",
"url": "http://rhn.redhat.com/errata/RHSA-2014-0421.html"
},
{
"type": "WEB",
"url": "http://www.debian.org/security/2014/dsa-3044"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-CGX8-MH65-HCP4
Vulnerability from github – Published: 2025-08-29 15:30 – Updated: 2025-08-29 15:30
VLAI
Details
A security vulnerability has been detected in appneta tcpreplay 4.5.1. Impacted is the function calc_sleep_time of the file send_packets.c. Such manipulation leads to divide by zero. An attack has to be approached locally. The exploit has been disclosed publicly and may be used. Upgrading to version 4.5.3-beta3 is recommended to address this issue. It is advisable to upgrade the affected component. The vendor confirms in a GitHub issue reply: "Was able to reproduce in 6fcbf03 but NOT 4.5.3-beta3."
Severity
{
"affected": [],
"aliases": [
"CVE-2025-9649"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-08-29T14:15:50Z",
"severity": "MODERATE"
},
"details": "A security vulnerability has been detected in appneta tcpreplay 4.5.1. Impacted is the function calc_sleep_time of the file send_packets.c. Such manipulation leads to divide by zero. An attack has to be approached locally. The exploit has been disclosed publicly and may be used. Upgrading to version 4.5.3-beta3 is recommended to address this issue. It is advisable to upgrade the affected component. The vendor confirms in a GitHub issue reply: \"Was able to reproduce in 6fcbf03 but NOT 4.5.3-beta3.\"",
"id": "GHSA-cgx8-mh65-hcp4",
"modified": "2025-08-29T15:30:38Z",
"published": "2025-08-29T15:30:38Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-9649"
},
{
"type": "WEB",
"url": "https://github.com/appneta/tcpreplay/issues/968"
},
{
"type": "WEB",
"url": "https://github.com/appneta/tcpreplay/issues/968#issuecomment-3226338070"
},
{
"type": "WEB",
"url": "https://drive.google.com/file/d/16QQtZvUrMbF-i_1cGt5hNWmkn-YVyBOM/view?usp=sharing"
},
{
"type": "WEB",
"url": "https://vuldb.com/?ctiid.321855"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.321855"
},
{
"type": "WEB",
"url": "https://vuldb.com/?submit.630493"
},
{
"type": "WEB",
"url": "https://vuldb.com/?submit.630494"
}
],
"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:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-CH3R-HJXG-J657
Vulnerability from github – Published: 2024-06-08 15:31 – Updated: 2024-07-17 18:31
VLAI
Details
In the Linux kernel, the following vulnerability has been resolved:
drm/amd/display: Fix division by zero in setup_dsc_config
When slice_height is 0, the division by slice_height in the calculation of the number of slices will cause a division by zero driver crash. This leaves the kernel in a state that requires a reboot. This patch adds a check to avoid the division by zero.
The stack trace below is for the 6.8.4 Kernel. I reproduced the issue on a Z16 Gen 2 Lenovo Thinkpad with a Apple Studio Display monitor connected via Thunderbolt. The amdgpu driver crashed with this exception when I rebooted the system with the monitor connected.
kernel: ? die (arch/x86/kernel/dumpstack.c:421 arch/x86/kernel/dumpstack.c:434 arch/x86/kernel/dumpstack.c:447) kernel: ? do_trap (arch/x86/kernel/traps.c:113 arch/x86/kernel/traps.c:154) kernel: ? setup_dsc_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1053) amdgpu kernel: ? do_error_trap (./arch/x86/include/asm/traps.h:58 arch/x86/kernel/traps.c:175) kernel: ? setup_dsc_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1053) amdgpu kernel: ? exc_divide_error (arch/x86/kernel/traps.c:194 (discriminator 2)) kernel: ? setup_dsc_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1053) amdgpu kernel: ? asm_exc_divide_error (./arch/x86/include/asm/idtentry.h:548) kernel: ? setup_dsc_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1053) amdgpu kernel: dc_dsc_compute_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1109) amdgpu
After applying this patch, the driver no longer crashes when the monitor is connected and the system is rebooted. I believe this is the same issue reported for 3113.
Severity
5.5 (Medium)
{
"affected": [],
"aliases": [
"CVE-2024-36969"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-06-08T13:15:58Z",
"severity": "MODERATE"
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\ndrm/amd/display: Fix division by zero in setup_dsc_config\n\nWhen slice_height is 0, the division by slice_height in the calculation\nof the number of slices will cause a division by zero driver crash. This\nleaves the kernel in a state that requires a reboot. This patch adds a\ncheck to avoid the division by zero.\n\nThe stack trace below is for the 6.8.4 Kernel. I reproduced the issue on\na Z16 Gen 2 Lenovo Thinkpad with a Apple Studio Display monitor\nconnected via Thunderbolt. The amdgpu driver crashed with this exception\nwhen I rebooted the system with the monitor connected.\n\nkernel: ? die (arch/x86/kernel/dumpstack.c:421 arch/x86/kernel/dumpstack.c:434 arch/x86/kernel/dumpstack.c:447)\nkernel: ? do_trap (arch/x86/kernel/traps.c:113 arch/x86/kernel/traps.c:154)\nkernel: ? setup_dsc_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1053) amdgpu\nkernel: ? do_error_trap (./arch/x86/include/asm/traps.h:58 arch/x86/kernel/traps.c:175)\nkernel: ? setup_dsc_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1053) amdgpu\nkernel: ? exc_divide_error (arch/x86/kernel/traps.c:194 (discriminator 2))\nkernel: ? setup_dsc_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1053) amdgpu\nkernel: ? asm_exc_divide_error (./arch/x86/include/asm/idtentry.h:548)\nkernel: ? setup_dsc_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1053) amdgpu\nkernel: dc_dsc_compute_config (drivers/gpu/drm/amd/amdgpu/../display/dc/dsc/dc_dsc.c:1109) amdgpu\n\nAfter applying this patch, the driver no longer crashes when the monitor\nis connected and the system is rebooted. I believe this is the same\nissue reported for 3113.",
"id": "GHSA-ch3r-hjxg-j657",
"modified": "2024-07-17T18:31:00Z",
"published": "2024-06-08T15:31:18Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-36969"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/130afc8a886183a94cf6eab7d24f300014ff87ba"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/308de6be0c9c7ba36915c0d398e771725c0ea911"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/7e4f50dfc98c49b3dc6875a35c3112522fb25639"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/91402e0e5de9124a3108db7a14163fcf9a6d322f"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/a32c8f951c8a456c1c251e1dcdf21787f8066445"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/f187fcbbb8f8bf10c6687f0beae22509369f7563"
}
],
"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"
}
]
}
GHSA-CH4F-829C-V5PW
Vulnerability from github – Published: 2021-08-25 14:43 – Updated: 2024-11-13 17:19
VLAI
Summary
Division by 0 in `ResourceScatterDiv`
Details
Impact
The implementation of tf.raw_ops.ResourceScatterDiv is vulnerable to a division by 0 error:
import tensorflow as tf
v= tf.Variable([1,2,3])
tf.raw_ops.ResourceScatterDiv(
resource=v.handle,
indices=[1],
updates=[0])
The implementation uses a common class for all binary operations but fails to treat the division by 0 case separately.
Patches
We have patched the issue in GitHub commit 4aacb30888638da75023e6601149415b39763d76.
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.
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.
Severity
5.5 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
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},
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"name": "tensorflow"
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}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
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}
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],
"versions": [
"2.5.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
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{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
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}
]
},
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"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
}
],
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}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
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{
"introduced": "2.5.0"
},
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}
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}
],
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"2.5.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
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{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
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}
]
},
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"ecosystem": "PyPI",
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},
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{
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{
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],
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}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
}
],
"aliases": [
"CVE-2021-37642"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-08-23T18:58:49Z",
"nvd_published_at": "2021-08-12T18:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nThe implementation of `tf.raw_ops.ResourceScatterDiv` is vulnerable to a division by 0 error:\n\n```python\nimport tensorflow as tf\n\nv= tf.Variable([1,2,3])\ntf.raw_ops.ResourceScatterDiv(\n resource=v.handle,\n indices=[1],\n updates=[0])\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/resource_variable_ops.cc#L865) uses a common class for all binary operations but fails to treat the division by 0 case separately.\n\n### Patches\nWe have patched the issue in GitHub commit [4aacb30888638da75023e6601149415b39763d76](https://github.com/tensorflow/tensorflow/commit/4aacb30888638da75023e6601149415b39763d76).\n\nThe 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.\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-ch4f-829c-v5pw",
"modified": "2024-11-13T17:19:29Z",
"published": "2021-08-25T14:43:56Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ch4f-829c-v5pw"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37642"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/4aacb30888638da75023e6601149415b39763d76"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-555.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-753.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-264.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"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": "Division by 0 in `ResourceScatterDiv`"
}
GHSA-CJRR-3F69-P92J
Vulnerability from github – Published: 2025-04-01 18:30 – Updated: 2025-11-03 21:33
VLAI
Details
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.
Severity
5.5 (Medium)
{
"affected": [],
"aliases": [
"CVE-2025-21898"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-04-01T16:15:20Z",
"severity": "MODERATE"
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\nftrace: Avoid potential division by zero in function_stat_show()\n\nCheck whether denominator expression x * (x - 1) * 1000 mod {2^32, 2^64}\nproduce zero and skip stddev computation in that case.\n\nFor now don\u0027t care about rec-\u003ecounter * rec-\u003ecounter overflow because\nrec-\u003etime * rec-\u003etime overflow will likely happen earlier.",
"id": "GHSA-cjrr-3f69-p92j",
"modified": "2025-11-03T21:33:20Z",
"published": "2025-04-01T18:30:50Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-21898"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/3d738b53ed6cddb68e68c9874520a4bf846163b5"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/5b3d32f607f0478b414b16516cf27f9170cf66c8"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/746cc474a95473591853927b3a9792a2d671155b"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/992775227843c9376773784b8b362add44592ad7"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/9cdac46fa7e854e587eb5f393fe491b6d7a9bdf6"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/a1a7eb89ca0b89dc1c326eeee2596f263291aca3"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/ca381f60a3bb7cfaa618d73ca411610bd7fc3149"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/f58a3f8e284d0bdf94164a8e61cd4e70d337a1a3"
},
{
"type": "WEB",
"url": "https://lists.debian.org/debian-lts-announce/2025/05/msg00030.html"
},
{
"type": "WEB",
"url": "https://lists.debian.org/debian-lts-announce/2025/05/msg00045.html"
}
],
"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"
}
]
}
GHSA-CM5X-837X-JF3C
Vulnerability from github – Published: 2021-08-25 14:42 – Updated: 2024-11-13 20:54
VLAI
Summary
Division by 0 in inplace operations
Details
Impact
An attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0:
import tensorflow as tf
tf.raw_ops.InplaceSub(x=[],i=[-99,-1,-1],v=[1,1,1])
The implementation has a logic error: it should skip processing if x and v are empty but the code uses || instead of &&.
Patches
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.
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.
Severity
5.5 (Medium)
{
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"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
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},
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},
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],
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}
],
"aliases": [
"CVE-2021-37660"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-08-24T13:20:38Z",
"nvd_published_at": "2021-08-12T18:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nAn attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.InplaceSub(x=[],i=[-99,-1,-1],v=[1,1,1])\n```\n\nThe [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 `\u0026\u0026`.\n\n### Patches\nWe have patched the issue in GitHub commit [e86605c0a336c088b638da02135ea6f9f6753618](https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618).\n\nThe 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.\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-cm5x-837x-jf3c",
"modified": "2024-11-13T20:54:13Z",
"published": "2021-08-25T14:42:44Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cm5x-837x-jf3c"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37660"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-573.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-771.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-282.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"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": "Division by 0 in inplace operations"
}
No mitigation information available for this CWE.
No CAPEC attack patterns related to this CWE.