Common Weakness Enumeration

CWE-1284

Allowed

Improper Validation of Specified Quantity in Input

Abstraction: Base · Status: Incomplete

The product receives input that is expected to specify a quantity (such as size or length), but it does not validate or incorrectly validates that the quantity has the required properties.

559 vulnerabilities reference this CWE, most recent first.

GHSA-PW7G-JH5J-6W4M

Vulnerability from github – Published: 2026-07-25 03:30 – Updated: 2026-07-25 03:30
VLAI
Details

Knot Resolver before 6.4.1 allows remote code execution via a heap-based buffer overflow in the DoQ (DNS-over-QUIC) receive path.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-66374"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-07-25T01:16:26Z",
    "severity": "HIGH"
  },
  "details": "Knot Resolver before 6.4.1 allows remote code execution via a heap-based buffer overflow in the DoQ (DNS-over-QUIC) receive path.",
  "id": "GHSA-pw7g-jh5j-6w4m",
  "modified": "2026-07-25T03:30:54Z",
  "published": "2026-07-25T03:30:54Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-66374"
    },
    {
      "type": "WEB",
      "url": "https://github.com/venglin/knot-doq"
    },
    {
      "type": "WEB",
      "url": "https://openwall.com/lists/oss-security/2026/07/23/6"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:H/A:L",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-PXH3-RC47-3FVP

Vulnerability from github – Published: 2023-05-16 00:30 – Updated: 2024-04-04 04:11
VLAI
Details

In m4u, there is a possible out of bounds write due to improper input validation. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07771518; Issue ID: ALPS07680084.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-20722"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284",
      "CWE-20"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-05-15T22:15:11Z",
    "severity": "MODERATE"
  },
  "details": "In m4u, there is a possible out of bounds write due to improper input validation. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07771518; Issue ID: ALPS07680084.",
  "id": "GHSA-pxh3-rc47-3fvp",
  "modified": "2024-04-04T04:11:15Z",
  "published": "2023-05-16T00:30:17Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-20722"
    },
    {
      "type": "WEB",
      "url": "https://corp.mediatek.com/product-security-bulletin/May-2023"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-Q36J-3HM6-HH2W

Vulnerability from github – Published: 2026-06-09 15:32 – Updated: 2026-07-09 00:31
VLAI
Details

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

mm/damon/core: disallow non-power of two min_region_sz on damon_start()

Commit d8f867fa0825 ("mm/damon: add damon_ctx->min_sz_region") introduced a bug that allows unaligned DAMON region address ranges. Commit c80f46ac228b ("mm/damon/core: disallow non-power of two min_region_sz") fixed it, but only for damon_commit_ctx() use case. Still, DAMON sysfs interface can emit non-power of two min_region_sz via damon_start(). Fix the path by adding the is_power_of_2() check on damon_start().

The issue was discovered by sashiko [1].

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-52905"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-09T14:16:44Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nmm/damon/core: disallow non-power of two min_region_sz on damon_start()\n\nCommit d8f867fa0825 (\"mm/damon: add damon_ctx-\u003emin_sz_region\") introduced\na bug that allows unaligned DAMON region address ranges.  Commit\nc80f46ac228b (\"mm/damon/core: disallow non-power of two min_region_sz\")\nfixed it, but only for damon_commit_ctx() use case.  Still, DAMON sysfs\ninterface can emit non-power of two min_region_sz via damon_start().  Fix\nthe path by adding the is_power_of_2() check on damon_start().\n\nThe issue was discovered by sashiko [1].",
  "id": "GHSA-q36j-3hm6-hh2w",
  "modified": "2026-07-09T00:31:06Z",
  "published": "2026-06-09T15:32:19Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-52905"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1de2db19a6028abe7d905875922faef5b873de67"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/89b6226b6c2a4add3939f361653a47c212d6ab75"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/95093e5cb4c5b50a5b1a4b79f2942b62744bd66a"
    }
  ],
  "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-Q72P-P7XM-7VMR

Vulnerability from github – Published: 2023-11-15 12:30 – Updated: 2023-11-15 12:30
VLAI
Details

Improper Input Validation in Checkmk <2.2.0p15, <2.1.0p37, <=2.0.0p39 allows priviledged attackers to cause partial denial of service of the UI via too long hostnames.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-23549"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284",
      "CWE-20"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-11-15T11:15:08Z",
    "severity": "LOW"
  },
  "details": "Improper Input Validation in Checkmk \u003c2.2.0p15, \u003c2.1.0p37, \u003c=2.0.0p39 allows priviledged attackers to cause partial denial of service of the UI via too long hostnames.",
  "id": "GHSA-q72p-p7xm-7vmr",
  "modified": "2023-11-15T12:30:30Z",
  "published": "2023-11-15T12:30:30Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-23549"
    },
    {
      "type": "WEB",
      "url": "https://checkmk.com/werk/16219"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-Q8QR-V893-9JP2

Vulnerability from github – Published: 2025-09-06 18:30 – Updated: 2025-09-06 18:30
VLAI
Details

Improper input validation in AMD Power Management Firmware (PMFW) could allow a privileged attacker from Guest VM to send arbitrary input data potentially causing a GPU Reset condition.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-36346"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-09-06T18:15:39Z",
    "severity": "MODERATE"
  },
  "details": "Improper input validation in AMD Power Management Firmware (PMFW) could allow a privileged attacker from Guest VM to send arbitrary input data potentially causing a GPU Reset condition.",
  "id": "GHSA-q8qr-v893-9jp2",
  "modified": "2025-09-06T18:30:33Z",
  "published": "2025-09-06T18:30:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-36346"
    },
    {
      "type": "WEB",
      "url": "https://www.amd.com/en/resources/product-security/bulletin/AMD-SB-6018.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:C/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-QCCM-7JQ2-92V7

Vulnerability from github – Published: 2024-08-31 09:30 – Updated: 2024-08-31 09:30
VLAI
Details

NVIDIA CUDA Toolkit contains a vulnerability in command 'cuobjdump' where a user may cause a crash or produce incorrect output by passing a malformed ELF file. A successful exploit of this vulnerability may lead to a limited denial of service or data tampering.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-0111"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-08-31T09:15:06Z",
    "severity": "MODERATE"
  },
  "details": "NVIDIA CUDA Toolkit contains a vulnerability in command \u0027cuobjdump\u0027 where a user may cause a crash or produce incorrect output by passing a malformed ELF file. A successful exploit of this vulnerability may lead to a limited denial of service or data tampering.",
  "id": "GHSA-qccm-7jq2-92v7",
  "modified": "2024-08-31T09:30:44Z",
  "published": "2024-08-31T09:30:44Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-0111"
    },
    {
      "type": "WEB",
      "url": "https://nvidia.custhelp.com/app/answers/detail/a_id/5564"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:L",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-QF97-64QX-GQHQ

Vulnerability from github – Published: 2023-01-26 21:30 – Updated: 2023-02-01 18:30
VLAI
Details

In Condition of Condition.java, there is a possible way to grant notification access due to improper input validation. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-12L Android-13Android ID: A-242846316

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-20493"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284",
      "CWE-20"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-01-26T21:15:00Z",
    "severity": "HIGH"
  },
  "details": "In Condition of Condition.java, there is a possible way to grant notification access due to improper input validation. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-12L Android-13Android ID: A-242846316",
  "id": "GHSA-qf97-64qx-gqhq",
  "modified": "2023-02-01T18:30:31Z",
  "published": "2023-01-26T21:30:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-20493"
    },
    {
      "type": "WEB",
      "url": "https://source.android.com/security/bulletin/2023-01-01"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-QFPC-5PJR-MH26

Vulnerability from github – Published: 2021-08-25 14:41 – Updated: 2024-11-13 21:14
VLAI
Summary
Missing validation in shape inference for `Dequantize`
Details

Impact

The shape inference code for tf.raw_ops.Dequantize has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments:

import tensorflow as tf

tf.compat.v1.disable_v2_behavior()
tf.raw_ops.Dequantize(
  input_tensor = tf.constant(-10.0, dtype=tf.float32),
  input_tensor = tf.cast(input_tensor, dtype=tf.quint8),
  min_range = tf.constant([], shape=[0], dtype=tf.float32),
  max_range = tf.constant([], shape=[0], dtype=tf.float32),
  mode  = 'MIN_COMBINED',
  narrow_range=False,
  axis=-10,
  dtype=tf.dtypes.float32)

The shape inference implementation uses axis to select between two different values for minmax_rank which is then used to retrieve tensor dimensions. However, code assumes that axis can be either -1 or a value greater than -1, with no validation for the other values.

Patches

We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764.

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 Yakun Zhang of Baidu Security.

Show details on source website

{
  "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-2021-37677"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284",
      "CWE-20"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-08-24T15:50:15Z",
    "nvd_published_at": "2021-08-12T23:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nThe shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments:\n\n```python\nimport tensorflow as tf\n\ntf.compat.v1.disable_v2_behavior()\ntf.raw_ops.Dequantize(\n  input_tensor = tf.constant(-10.0, dtype=tf.float32),\n  input_tensor = tf.cast(input_tensor, dtype=tf.quint8),\n  min_range = tf.constant([], shape=[0], dtype=tf.float32),\n  max_range = tf.constant([], shape=[0], dtype=tf.float32),\n  mode  = \u0027MIN_COMBINED\u0027,\n  narrow_range=False,\n  axis=-10,\n  dtype=tf.dtypes.float32)\n```\n\nThe shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values.\n\n### Patches\nWe have patched the issue in GitHub commit [da857cfa0fde8f79ad0afdbc94e88b5d4bbec764](https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764).\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 Yakun Zhang of Baidu Security.",
  "id": "GHSA-qfpc-5pjr-mh26",
  "modified": "2024-11-13T21:14:00Z",
  "published": "2021-08-25T14:41:23Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37677"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-590.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-788.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-299.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": "Missing validation in shape inference for `Dequantize`"
}

GHSA-QG44-88JP-H8XV

Vulnerability from github – Published: 2026-06-12 09:31 – Updated: 2026-06-12 09:31
VLAI
Details

The SSH service of CelloOS developed by Cellopoint has an Improper Access Control vulnerability, allowing authenticated remote attackers to bypass the enforced command restrictions and execute operating system commands outside the originally authorized scope.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-12059"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1284"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-12T07:16:19Z",
    "severity": "HIGH"
  },
  "details": "The SSH service of CelloOS developed by Cellopoint has an Improper Access Control vulnerability, allowing authenticated remote attackers to bypass the enforced command restrictions and execute operating system commands outside the originally authorized scope.",
  "id": "GHSA-qg44-88jp-h8xv",
  "modified": "2026-06-12T09:31:55Z",
  "published": "2026-06-12T09:31:55Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-12059"
    },
    {
      "type": "WEB",
      "url": "https://www.twcert.org.tw/en/cp-139-10965-3ce75-2.html"
    },
    {
      "type": "WEB",
      "url": "https://www.twcert.org.tw/tw/cp-132-10966-3258e-1.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/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-QHHP-8CC7-VF7W

Vulnerability from github – Published: 2022-06-21 00:00 – Updated: 2023-06-26 18:30
VLAI
Details

NHI’s health insurance web service component has insufficient validation for input string length, which can result in heap-based buffer overflow attack. A remote attacker can exploit this vulnerability to flood the memory space reserved for the program, in order to terminate service without authentication, which requires a system restart to recover service.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-45918"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122",
      "CWE-1284",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-06-20T06:15:00Z",
    "severity": "HIGH"
  },
  "details": "NHI\u2019s health insurance web service component has insufficient validation for input string length, which can result in heap-based buffer overflow attack. A remote attacker can exploit this vulnerability to flood the memory space reserved for the program, in order to terminate service without authentication, which requires a system restart to recover service.",
  "id": "GHSA-qhhp-8cc7-vf7w",
  "modified": "2023-06-26T18:30:21Z",
  "published": "2022-06-21T00:00:48Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-45918"
    },
    {
      "type": "WEB",
      "url": "https://www.twcert.org.tw/tw/cp-132-6227-eaf49-1.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

Mitigation MIT-5
Implementation

Strategy: Input Validation

  • Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
  • When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue."
  • Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

No CAPEC attack patterns related to this CWE.