Common Weakness Enumeration

CWE-369

Allowed

Divide By Zero

Abstraction: Base · Status: Draft

The product divides a value by zero.

599 vulnerabilities reference this CWE, most recent first.

GHSA-6XX8-4XH5-JH9W

Vulnerability from github – Published: 2022-05-24 19:08 – Updated: 2022-05-24 19:08
VLAI
Details

A Divide-by-zero vulnerability exists in JasPer Image Coding Toolkit 2.0 in jasper/src/libjasper/jpc/jpc_enc.c

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-27845"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-07-15T16:15:00Z",
    "severity": "MODERATE"
  },
  "details": "A Divide-by-zero vulnerability exists in JasPer Image Coding Toolkit 2.0 in jasper/src/libjasper/jpc/jpc_enc.c",
  "id": "GHSA-6xx8-4xh5-jh9w",
  "modified": "2022-05-24T19:08:11Z",
  "published": "2022-05-24T19:08:11Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-27845"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jasper-software/jasper/issues/194"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-742P-Q3M8-X43J

Vulnerability from github – Published: 2026-07-25 12:31 – Updated: 2026-08-13 18:31
VLAI
Details

In the Linux kernel, the following vulnerability has been resolved:

Input: elan_i2c - prevent division by zero and arithmetic underflow

The Elan I2C touchpad driver queries the device for its physical dimensions and trace counts to calculate the device resolution and width. However, if the device firmware or device tree provides invalid zero values for x_traces or y_traces, it results in a fatal division-by-zero exception leading to a kernel panic during device probe.

Add checks to ensure these parameters are non-zero before performing the division. If invalid trace values are detected, fall back to a safe default of 1.

Additionally, prevent an arithmetic underflow in the touch reporting logic. Previously, if the calculated or fallback width was smaller than ETP_FWIDTH_REDUCE (90), the subtraction would underflow, resulting in a massive unsigned integer being reported to userspace. Clamp the adjusted width to a minimum of 0 to safely handle small physical dimensions and fallback scenarios.

Completing the probe with safe fallback values ensures the sysfs nodes are created, keeping the firmware update path intact so a recovery firmware can be flashed to the device.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-64275"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-07-25T10:17:07Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nInput: elan_i2c - prevent division by zero and arithmetic underflow\n\nThe Elan I2C touchpad driver queries the device for its physical\ndimensions and trace counts to calculate the device resolution and width.\nHowever, if the device firmware or device tree provides invalid zero\nvalues for x_traces or y_traces, it results in a fatal division-by-zero\nexception leading to a kernel panic during device probe.\n\nAdd checks to ensure these parameters are non-zero before performing\nthe division. If invalid trace values are detected, fall back to a safe\ndefault of 1.\n\nAdditionally, prevent an arithmetic underflow in the touch reporting\nlogic. Previously, if the calculated or fallback width was smaller than\nETP_FWIDTH_REDUCE (90), the subtraction would underflow, resulting in a\nmassive unsigned integer being reported to userspace. Clamp the adjusted\nwidth to a minimum of 0 to safely handle small physical dimensions and\nfallback scenarios.\n\nCompleting the probe with safe fallback values ensures the sysfs nodes\nare created, keeping the firmware update path intact so a recovery\nfirmware can be flashed to the device.",
  "id": "GHSA-742p-q3m8-x43j",
  "modified": "2026-08-13T18:31:10Z",
  "published": "2026-07-25T12:31:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-64275"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/01e0317c256c560d8dcce2e9825eb6142ee34611"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2f281ff0163a38fdc4cb4061f0c241e643283a5e"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/59d4cc5e7a9785e4bdc9c55273274c6b49d4b58d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/6bac57d8fe2a077b8a85b4140eeb7999078158eb"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/8c1db3418a419e788691746b9c47f863c2fd4890"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/df2b818fa009c10ff6ba875a1663ff001cda9558"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/f6d10af2036d1d4a847a74fe47ebbf93bce3c84c"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/feb4866a42ec94764c7eb58012256f6f37664727"
    }
  ],
  "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-746F-27CQ-G8FJ

Vulnerability from github – Published: 2022-05-17 02:20 – Updated: 2022-05-17 02:20
VLAI
Details

The insert_note_steps function in readmidi.c in TiMidity++ 2.14.0 allows remote attackers to cause a denial of service (divide-by-zero error and application crash) via a crafted mid file. NOTE: a crash might be relevant when using the --background option.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2017-11546"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-07-31T13:29:00Z",
    "severity": "MODERATE"
  },
  "details": "The insert_note_steps function in readmidi.c in TiMidity++ 2.14.0 allows remote attackers to cause a denial of service (divide-by-zero error and application crash) via a crafted mid file. NOTE: a crash might be relevant when using the --background option.",
  "id": "GHSA-746f-27cq-g8fj",
  "modified": "2022-05-17T02:20:33Z",
  "published": "2022-05-17T02:20:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-11546"
    },
    {
      "type": "WEB",
      "url": "http://seclists.org/fulldisclosure/2017/Jul/83"
    }
  ],
  "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-747G-7PF6-5Q6P

Vulnerability from github – Published: 2025-09-24 15:31 – Updated: 2025-09-24 15:31
VLAI
Details

NVIDIA CUDA Toolkit for all platforms contains a vulnerability in nvJPEG where a local authenticated user may cause a divide by zero error by submitting a specially crafted JPEG file. A successful exploit of this vulnerability may lead to denial of service.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-23273"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-09-24T14:15:47Z",
    "severity": "LOW"
  },
  "details": "NVIDIA CUDA Toolkit for all platforms contains a vulnerability in nvJPEG where a local authenticated user may cause a divide by zero error by submitting a specially crafted JPEG file. A successful exploit of this vulnerability may lead to denial of service.",
  "id": "GHSA-747g-7pf6-5q6p",
  "modified": "2025-09-24T15:31:13Z",
  "published": "2025-09-24T15:31:13Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-23273"
    },
    {
      "type": "WEB",
      "url": "https://nvidia.custhelp.com/app/answers/detail/a_id/5661"
    },
    {
      "type": "WEB",
      "url": "https://www.cve.org/CVERecord?id=CVE-2025-23273"
    }
  ],
  "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"
    }
  ]
}

GHSA-74CG-P8Q3-4C3Q

Vulnerability from github – Published: 2026-07-01 15:35 – Updated: 2026-07-01 15:35
VLAI
Details

FatFs R0.16 and earlier contains a divide-by-zero in exFAT sync logic bug when crafted metadata causes n_fatent - 2 to be zero during write/sync operations. This maps to CWE-369 (Divide By Zero). Estimated CVSS v3.1 vector: CVSS:3.1/AV:P/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H (4.6, Medium). Network-delivered update media can make this remote in some pipelines. The estimated CISA SSVC vectors are Exploitation: PoC, Technical Impact: Partial.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-6683"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-07-01T15:17:12Z",
    "severity": "MODERATE"
  },
  "details": "FatFs R0.16 and earlier contains a divide-by-zero in exFAT sync logic bug when crafted metadata causes n_fatent - 2 to be zero during write/sync operations. This maps to CWE-369 (Divide By Zero). Estimated CVSS v3.1 vector: CVSS:3.1/AV:P/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H (4.6, Medium). Network-delivered update media can make this remote in some pipelines. The estimated CISA SSVC vectors are Exploitation: PoC, Technical Impact: Partial.",
  "id": "GHSA-74cg-p8q3-4c3q",
  "modified": "2026-07-01T15:35:20Z",
  "published": "2026-07-01T15:35:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-6683"
    },
    {
      "type": "WEB",
      "url": "https://elm-chan.org/fsw/ff"
    },
    {
      "type": "WEB",
      "url": "https://github.com/runZeroInc/vulns-2026-fatfs-chance"
    },
    {
      "type": "WEB",
      "url": "https://www.runzero.com/advisories/fatfs-exfat-divide-by-zero-cve-2026-6683"
    },
    {
      "type": "WEB",
      "url": "https://www.runzero.com/blog/fatfs-bugs"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:P/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-74X6-C8F2-MFPM

Vulnerability from github – Published: 2022-05-13 01:16 – Updated: 2022-05-13 01:16
VLAI
Details

An issue was discovered in Qt 5.11. A malformed PPM image causes a division by zero and a crash in qppmhandler.cpp.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2018-19872"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-03-21T16:00:00Z",
    "severity": "MODERATE"
  },
  "details": "An issue was discovered in Qt 5.11. A malformed PPM image causes a division by zero and a crash in qppmhandler.cpp.",
  "id": "GHSA-74x6-c8f2-mfpm",
  "modified": "2022-05-13T01:16:05Z",
  "published": "2022-05-13T01:16:05Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-19872"
    },
    {
      "type": "WEB",
      "url": "https://bugreports.qt.io/browse/QTBUG-69449"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2020/09/msg00023.html"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2020/09/msg00024.html"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2C5FHCR4A636BLTAXL76WWDJLOAHGNYG"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FO7IBY7YYKNMRD5OI3JNNUI42WEM7NUV"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/XS6G3ZDFCHWFQD4CFXWFPHREOHBBDTD7"
    },
    {
      "type": "WEB",
      "url": "https://usn.ubuntu.com/4275-1"
    },
    {
      "type": "WEB",
      "url": "http://blog.qt.io/blog/2018/12/04/qt-5-11-3-released-important-security-updates"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-04/msg00080.html"
    }
  ],
  "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-765F-R4FQ-WX9X

Vulnerability from github – Published: 2022-05-14 03:18 – Updated: 2022-05-14 03:18
VLAI
Details

A division by zero was discovered in H5D__btree_decode_key in H5Dbtree.c in the HDF HDF5 1.10.2 library. It could allow a remote denial of service attack.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2018-11203"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-05-16T15:29:00Z",
    "severity": "MODERATE"
  },
  "details": "A division by zero was discovered in H5D__btree_decode_key in H5Dbtree.c in the HDF HDF5 1.10.2 library. It could allow a remote denial of service attack.",
  "id": "GHSA-765f-r4fq-wx9x",
  "modified": "2022-05-14T03:18:06Z",
  "published": "2022-05-14T03:18:06Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-11203"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Twi1ight/fuzzing-pocs/tree/master/hdf5"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-76W3-FGP7-3HF7

Vulnerability from github – Published: 2026-05-06 12:30 – Updated: 2026-05-12 21:31
VLAI
Details

In the Linux kernel, the following vulnerability has been resolved:

net/sched: act_skbedit: fix divide-by-zero in tcf_skbedit_hash()

Commit 38a6f0865796 ("net: sched: support hash selecting tx queue") added SKBEDIT_F_TXQ_SKBHASH support. The inclusive range size is computed as:

mapping_mod = queue_mapping_max - queue_mapping + 1;

The range size can be 65536 when the requested range covers all possible u16 queue IDs (e.g. queue_mapping=0 and queue_mapping_max=U16_MAX). That value cannot be represented in a u16 and previously wrapped to 0, so tcf_skbedit_hash() could trigger a divide-by-zero:

queue_mapping += skb_get_hash(skb) % params->mapping_mod;

Compute mapping_mod in a wider type and reject ranges larger than U16_MAX to prevent params->mapping_mod from becoming 0 and avoid the crash.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-43238"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-06T12:16:44Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nnet/sched: act_skbedit: fix divide-by-zero in tcf_skbedit_hash()\n\nCommit 38a6f0865796 (\"net: sched: support hash selecting tx queue\")\nadded SKBEDIT_F_TXQ_SKBHASH support. The inclusive range size is\ncomputed as:\n\nmapping_mod = queue_mapping_max - queue_mapping + 1;\n\nThe range size can be 65536 when the requested range covers all possible\nu16 queue IDs (e.g. queue_mapping=0 and queue_mapping_max=U16_MAX).\nThat value cannot be represented in a u16 and previously wrapped to 0,\nso tcf_skbedit_hash() could trigger a divide-by-zero:\n\nqueue_mapping += skb_get_hash(skb) % params-\u003emapping_mod;\n\nCompute mapping_mod in a wider type and reject ranges larger than U16_MAX\nto prevent params-\u003emapping_mod from becoming 0 and avoid the crash.",
  "id": "GHSA-76w3-fgp7-3hf7",
  "modified": "2026-05-12T21:31:26Z",
  "published": "2026-05-06T12:30:34Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-43238"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/015cebdfcb97b5347fb7f598ea712a281cb35840"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/3c2b95b26860bd6f8e2310d31ea1200d3f8f173e"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/4ece5eb4836f8ff03b9004dc2430a7169f282851"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/59809fda4da7730cfe84a948033f47eb45db073d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/9c735a7d98c982a786b0db71eb6566ee00aaa04f"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/be054cc66f739a9ba615dba9012a07fab8e7dd6f"
    }
  ],
  "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-772P-X54P-HJRV

Vulnerability from github – Published: 2021-05-21 14:21 – Updated: 2024-10-28 21:26
VLAI
Summary
Division by zero in `Conv3D`
Details

Impact

A malicious user could trigger a division by 0 in Conv3D implementation:

import tensorflow as tf

input_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
filter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)

tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 23, 1])

The implementation does a modulo operation based on user controlled input:

  const int64 out_depth = filter.dim_size(4);
  OP_REQUIRES(context, in_depth % filter_depth == 0, ...);

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:

import tensorflow as tf

input_tensor = tf.constant([], shape=[2, 2, 2, 2, 0], dtype=tf.float32)
filter_tensor = tf.constant([], shape=[0, 0, 2, 6, 2], dtype=tf.float32)

tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 39, 34, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])

The shape of the two tensors must follow the constraints specified in the op description.

Patches

We have patched the issue in GitHub commit 799f835a3dfa00a4d852defa29b15841eea9d64f.

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 Yakun Zhang and Ying Wang of Baidu X-Team.

Show details on source website

{
  "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-2021-29517"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T23:32:11Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nA malicious user could trigger a division by 0 in `Conv3D` implementation:\n\n```python\nimport tensorflow as tf\n\ninput_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)\nfilter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)\n\ntf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding=\u0027VALID\u0027, data_format=\u0027NDHWC\u0027, dilations=[1, 1, 1, 23, 1])\n```\n\nThe [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:\n\n```cc\n  const int64 out_depth = filter.dim_size(4);\n  OP_REQUIRES(context, in_depth % filter_depth == 0, ...);\n```\n\nThus, when `filter` has a 0 as the fifth element, this results in a division by 0.\n\nAdditionally, if the shape of the two tensors is not valid, an Eigen assertion can be triggered, resulting in a program crash:\n\n```python\nimport tensorflow as tf\n\ninput_tensor = tf.constant([], shape=[2, 2, 2, 2, 0], dtype=tf.float32)\nfilter_tensor = tf.constant([], shape=[0, 0, 2, 6, 2], dtype=tf.float32)\n\ntf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 39, 34, 1], padding=\u0027VALID\u0027, data_format=\u0027NDHWC\u0027, dilations=[1, 1, 1, 1, 1])\n```\n\nThe shape of the two tensors must follow the constraints specified in the [op description](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Conv3D).\n\n### Patches\nWe have patched the issue in GitHub commit [799f835a3dfa00a4d852defa29b15841eea9d64f](https://github.com/tensorflow/tensorflow/commit/799f835a3dfa00a4d852defa29b15841eea9d64f).\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 Yakun Zhang and Ying Wang of Baidu X-Team.",
  "id": "GHSA-772p-x54p-hjrv",
  "modified": "2024-10-28T21:26:22Z",
  "published": "2021-05-21T14:21:01Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-772p-x54p-hjrv"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29517"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/799f835a3dfa00a4d852defa29b15841eea9d64f"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-445.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-643.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-154.yaml"
    }
  ],
  "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 `Conv3D`"
}

GHSA-779V-R8GR-3GPC

Vulnerability from github – Published: 2022-05-14 03:46 – Updated: 2022-05-14 03:46
VLAI
Details

In GNU Libextractor 1.4, there is a Divide-By-Zero in EXTRACTOR_wav_extract_method in wav_extractor.c via a zero sample rate.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2017-15266"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-10-11T17:29:00Z",
    "severity": "MODERATE"
  },
  "details": "In GNU Libextractor 1.4, there is a Divide-By-Zero in EXTRACTOR_wav_extract_method in wav_extractor.c via a zero sample rate.",
  "id": "GHSA-779v-r8gr-3gpc",
  "modified": "2022-05-14T03:46:34Z",
  "published": "2022-05-14T03:46:34Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-15266"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=1499599"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2017/12/msg00000.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.gnu.org/archive/html/bug-libextractor/2017-10/msg00002.html"
    },
    {
      "type": "WEB",
      "url": "http://openwall.com/lists/oss-security/2017/10/11/1"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/101271"
    }
  ],
  "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"
    }
  ]
}

No mitigation information available for this CWE.

No CAPEC attack patterns related to this CWE.