Common Weakness Enumeration

CWE-125

Allowed

Out-of-bounds Read

Abstraction: Base · Status: Draft

The product reads data past the end, or before the beginning, of the intended buffer.

11464 vulnerabilities reference this CWE, most recent first.

GHSA-8GJV-JWGC-CX6R

Vulnerability from github – Published: 2022-10-25 19:00 – Updated: 2024-06-27 18:31
VLAI
Details

An issue was discovered in Connected Vehicle Systems Alliance (COVESA) dlt-daemon through 2.18.8. Due to a faulty DLT file parser, a crafted DLT file that crashes the process can be created. This is due to missing validation checks. There is a heap-based buffer over-read of one byte.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-39836"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-10-25T17:15:00Z",
    "severity": "MODERATE"
  },
  "details": "An issue was discovered in Connected Vehicle Systems Alliance (COVESA) dlt-daemon through 2.18.8. Due to a faulty DLT file parser, a crafted DLT file that crashes the process can be created. This is due to missing validation checks. There is a heap-based buffer over-read of one byte.",
  "id": "GHSA-8gjv-jwgc-cx6r",
  "modified": "2024-06-27T18:31:29Z",
  "published": "2022-10-25T19:00:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-39836"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2024/06/msg00021.html"
    },
    {
      "type": "WEB",
      "url": "https://sec-consult.com/vulnerability-lab/advisory/multiple-memory-corruption-vulnerabilities-in-covesa-dlt-daemon"
    },
    {
      "type": "WEB",
      "url": "https://seclists.org/fulldisclosure/2022/Sep/24"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-8GP4-GV99-3GCW

Vulnerability from github – Published: 2022-05-13 01:50 – Updated: 2022-05-13 01:50
VLAI
Details

ImageMagick 7.0.8-11 Q16 has a heap-based buffer over-read in the MagickCore/quantum-private.h PushShortPixel function when called from the coders/psd.c ParseImageResourceBlocks function.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2018-16413"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-09-03T19:29:00Z",
    "severity": "HIGH"
  },
  "details": "ImageMagick 7.0.8-11 Q16 has a heap-based buffer over-read in the MagickCore/quantum-private.h PushShortPixel function when called from the coders/psd.c ParseImageResourceBlocks function.",
  "id": "GHSA-8gp4-gv99-3gcw",
  "modified": "2022-05-13T01:50:20Z",
  "published": "2022-05-13T01:50:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-16413"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ImageMagick/ImageMagick/issues/1249"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ImageMagick/ImageMagick/issues/1251"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2018/10/msg00002.html"
    },
    {
      "type": "WEB",
      "url": "https://usn.ubuntu.com/4034-1"
    },
    {
      "type": "WEB",
      "url": "https://www.debian.org/security/2018/dsa-4316"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-05/msg00006.html"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/105241"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-8GQ9-69QW-7CCH

Vulnerability from github – Published: 2022-05-24 17:36 – Updated: 2022-05-24 17:36
VLAI
Details

An arbitrary memory read vulnerability in Asylo versions up to 0.6.0 allows an untrusted attacker to make a call to enc_untrusted_recvmsg using an attacker controlled result parameter. The parameter size is unchecked allowing the attacker to read memory locations outside of the intended buffer size including memory addresses within the secure enclave. We recommend upgrading or past commit fa6485c5d16a7355eab047d4a44345a73bc9131e

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-8940"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-12-15T15:15:00Z",
    "severity": "MODERATE"
  },
  "details": "An arbitrary memory read vulnerability in Asylo versions up to 0.6.0 allows an untrusted attacker to make a call to enc_untrusted_recvmsg using an attacker controlled result parameter. The parameter size is unchecked allowing the attacker to read memory locations outside of the intended buffer size including memory addresses within the secure enclave. We recommend upgrading or past commit fa6485c5d16a7355eab047d4a44345a73bc9131e",
  "id": "GHSA-8gq9-69qw-7cch",
  "modified": "2022-05-24T17:36:37Z",
  "published": "2022-05-24T17:36:37Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-8940"
    },
    {
      "type": "WEB",
      "url": "https://github.com/google/asylo/commit/fa6485c5d16a7355eab047d4a44345a73bc9131e"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-8GR4-RXJ5-HXC5

Vulnerability from github – Published: 2026-05-01 15:30 – Updated: 2026-05-01 18:31
VLAI
Details

Two heap-based out-of-bounds read vulnerabilities in the STL ASCII file parser in Open CASCADE Technology (OCCT) V8_0_0_rc5 exist in RWStl_Reader::ReadAscii because buffers returned by Standard_ReadLineBuffer::ReadLine() are not properly length-validated before strncasecmp or direct byte access. User-assisted attackers can trigger these issues by persuading a victim to open a crafted STL file with extremely short lines, resulting in a denial of service or possible information disclosure.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-42476"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-01T15:16:43Z",
    "severity": "HIGH"
  },
  "details": "Two heap-based out-of-bounds read vulnerabilities in the STL ASCII file parser in Open CASCADE Technology (OCCT) V8_0_0_rc5 exist in RWStl_Reader::ReadAscii because buffers returned by Standard_ReadLineBuffer::ReadLine() are not properly length-validated before strncasecmp or direct byte access. User-assisted attackers can trigger these issues by persuading a victim to open a crafted STL file with extremely short lines, resulting in a denial of service or possible information disclosure.",
  "id": "GHSA-8gr4-rxj5-hxc5",
  "modified": "2026-05-01T18:31:23Z",
  "published": "2026-05-01T15:30:36Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-42476"
    },
    {
      "type": "WEB",
      "url": "https://gist.github.com/sgInnora/dfba083d04906283e9c92aea78e2d94a"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-8GV3-57P6-G35R

Vulnerability from github – Published: 2021-05-21 14:24 – Updated: 2024-11-01 16:58
VLAI
Summary
Heap buffer overflow in `RaggedTensorToTensor`
Details

Impact

An attacker can cause a heap buffer overflow in tf.raw_ops.RaggedTensorToTensor:

import tensorflow as tf

shape = tf.constant([10, 10], shape=[2], dtype=tf.int64)
values = tf.constant(0, shape=[1], dtype=tf.int64)
default_value = tf.constant(0, dtype=tf.int64)
l = [849, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
row = tf.constant(l, shape=[5, 43], dtype=tf.int64)
rows = [row]
types = ['ROW_SPLITS']

tf.raw_ops.RaggedTensorToTensor(
    shape=shape, values=values, default_value=default_value,
    row_partition_tensors=rows, row_partition_types=types) 

This is because the implementation uses the same index to access two arrays in parallel:

for (INDEX_TYPE i = 0; i < row_split_size - 1; ++i) {
  INDEX_TYPE row_length = row_split(i + 1) - row_split(i);
  INDEX_TYPE real_length = std::min(output_size, row_length);
  INDEX_TYPE parent_output_index_current = parent_output_index[i];
  ...
}

Since the user controls the shape of the input arguments, an attacker could trigger a heap OOB access when parent_output_index is shorter than row_split.

Patches

We have patched the issue in GitHub commit a84358aa12f0b1518e606095ab9cfddbf597c121.

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 Ying Wang and Yakun Zhang 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-2021-29560"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T20:23:08Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nAn attacker can cause a heap buffer overflow in `tf.raw_ops.RaggedTensorToTensor`:\n\n```python\nimport tensorflow as tf\n\nshape = tf.constant([10, 10], shape=[2], dtype=tf.int64)\nvalues = tf.constant(0, shape=[1], dtype=tf.int64)\ndefault_value = tf.constant(0, dtype=tf.int64)\nl = [849, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\nrow = tf.constant(l, shape=[5, 43], dtype=tf.int64)\nrows = [row]\ntypes = [\u0027ROW_SPLITS\u0027]\n\ntf.raw_ops.RaggedTensorToTensor(\n    shape=shape, values=values, default_value=default_value,\n    row_partition_tensors=rows, row_partition_types=types) \n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) uses the same index to access two arrays in parallel:\n\n```cc\nfor (INDEX_TYPE i = 0; i \u003c row_split_size - 1; ++i) {\n  INDEX_TYPE row_length = row_split(i + 1) - row_split(i);\n  INDEX_TYPE real_length = std::min(output_size, row_length);\n  INDEX_TYPE parent_output_index_current = parent_output_index[i];\n  ...\n}\n```\n\nSince the user controls the shape of the input arguments, an attacker could trigger a heap OOB access when `parent_output_index` is shorter than `row_split`.\n\n### Patches\nWe have patched the issue in GitHub commit [a84358aa12f0b1518e606095ab9cfddbf597c121](https://github.com/tensorflow/tensorflow/commit/a84358aa12f0b1518e606095ab9cfddbf597c121).\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 Ying Wang and Yakun Zhang of Baidu X-Team.",
  "id": "GHSA-8gv3-57p6-g35r",
  "modified": "2024-11-01T16:58:15Z",
  "published": "2021-05-21T14:24:57Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8gv3-57p6-g35r"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29560"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/a84358aa12f0b1518e606095ab9cfddbf597c121"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-488.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-686.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-197.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    }
  ],
  "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": "Heap buffer overflow in `RaggedTensorToTensor`"
}

GHSA-8GV3-85Q5-PGQ6

Vulnerability from github – Published: 2023-09-04 03:30 – Updated: 2024-04-04 07:24
VLAI
Details

In imgsys_cmdq, there is a possible out of bounds read due to a missing valid range checking. This could lead to local information disclosure with System execution privileges needed. User interaction is needed for exploitation. Patch ID: ALPS07340119; Issue ID: ALPS07340119.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-20843"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-09-04T03:15:11Z",
    "severity": "MODERATE"
  },
  "details": "In imgsys_cmdq, there is a possible out of bounds read due to a missing valid range checking. This could lead to local information disclosure with System execution privileges needed. User interaction is needed for exploitation. Patch ID: ALPS07340119; Issue ID: ALPS07340119.",
  "id": "GHSA-8gv3-85q5-pgq6",
  "modified": "2024-04-04T07:24:47Z",
  "published": "2023-09-04T03:30:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-20843"
    },
    {
      "type": "WEB",
      "url": "https://corp.mediatek.com/product-security-bulletin/September-2023"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:H/UI:R/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-8GVG-JJRH-M7JM

Vulnerability from github – Published: 2024-02-15 15:30 – Updated: 2024-02-15 18:30
VLAI
Details

Acrobat Reader versions 20.005.30539, 23.008.20470 and earlier are affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. An attacker could leverage this vulnerability to bypass mitigations such as ASLR. Exploitation of this issue requires user interaction in that a victim must open a malicious file.

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{
  "affected": [],
  "aliases": [
    "CVE-2024-20735"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-02-15T13:15:48Z",
    "severity": "MODERATE"
  },
  "details": "Acrobat Reader versions 20.005.30539, 23.008.20470 and earlier are affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. An attacker could leverage this vulnerability to bypass mitigations such as ASLR. Exploitation of this issue requires user interaction in that a victim must open a malicious file.",
  "id": "GHSA-8gvg-jjrh-m7jm",
  "modified": "2024-02-15T18:30:41Z",
  "published": "2024-02-15T15:30:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-20735"
    },
    {
      "type": "WEB",
      "url": "https://helpx.adobe.com/security/products/acrobat/apsb24-07.html"
    },
    {
      "type": "WEB",
      "url": "https://www.talosintelligence.com/vulnerability_reports/TALOS-2023-1905"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-8GW5-C82W-7VMP

Vulnerability from github – Published: 2024-12-12 12:31 – Updated: 2024-12-12 12:31
VLAI
Details

Read/Write vulnerability in the image decoding module Impact: Successful exploitation of this vulnerability will affect availability.

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{
  "affected": [],
  "aliases": [
    "CVE-2024-54107"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125",
      "CWE-20"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-12-12T12:15:25Z",
    "severity": "HIGH"
  },
  "details": "Read/Write vulnerability in the image decoding module\nImpact: Successful exploitation of this vulnerability will affect availability.",
  "id": "GHSA-8gw5-c82w-7vmp",
  "modified": "2024-12-12T12:31:16Z",
  "published": "2024-12-12T12:31:16Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-54107"
    },
    {
      "type": "WEB",
      "url": "https://consumer.huawei.com/en/support/bulletin/2024/12"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-8GW8-R4QF-MQMQ

Vulnerability from github – Published: 2022-05-13 01:44 – Updated: 2022-05-13 01:44
VLAI
Details

In Qualcomm Android for MSM, Firefox OS for MSM, and QRD Android with all Android releases from CAF using the Linux kernel before security patch level 2018-04-05, while processing PTT commands, ptt_sock_send_msg_to_app() is invoked without validating the packet length. If the packet length is invalid, then a buffer over-read can occur.

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{
  "affected": [],
  "aliases": [
    "CVE-2017-15853"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-04-03T17:29:00Z",
    "severity": "MODERATE"
  },
  "details": "In Qualcomm Android for MSM, Firefox OS for MSM, and QRD Android with all Android releases from CAF using the Linux kernel before security patch level 2018-04-05, while processing PTT commands, ptt_sock_send_msg_to_app() is invoked without validating the packet length. If the packet length is invalid, then a buffer over-read can occur.",
  "id": "GHSA-8gw8-r4qf-mqmq",
  "modified": "2022-05-13T01:44:01Z",
  "published": "2022-05-13T01:44:01Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-15853"
    },
    {
      "type": "WEB",
      "url": "https://source.android.com/security/bulletin/pixel/2018-04-01"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-8GWJ-4MVC-6737

Vulnerability from github – Published: 2025-04-07 12:33 – Updated: 2025-04-07 12:33
VLAI
Details

Memory corruption while IOCTL call is invoked from user-space to read board data.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-21438"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-04-07T11:15:52Z",
    "severity": "HIGH"
  },
  "details": "Memory corruption while IOCTL call is invoked from user-space to read board data.",
  "id": "GHSA-8gwj-4mvc-6737",
  "modified": "2025-04-07T12:33:19Z",
  "published": "2025-04-07T12:33:19Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-21438"
    },
    {
      "type": "WEB",
      "url": "https://docs.qualcomm.com/product/publicresources/securitybulletin/april-2025-bulletin.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/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.
  • To reduce the likelihood of introducing an out-of-bounds read, ensure that you validate and ensure correct calculations for any length argument, buffer size calculation, or offset. Be especially careful of relying on a sentinel (i.e. special character such as NUL) in untrusted inputs.
Mitigation
Architecture and Design

Strategy: Language Selection

Use a language that provides appropriate memory abstractions.

CAPEC-540: Overread Buffers

An adversary attacks a target by providing input that causes an application to read beyond the boundary of a defined buffer. This typically occurs when a value influencing where to start or stop reading is set to reflect positions outside of the valid memory location of the buffer. This type of attack may result in exposure of sensitive information, a system crash, or arbitrary code execution.