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.

11503 vulnerabilities reference this CWE, most recent first.

GHSA-6G35-P5GH-6QH4

Vulnerability from github – Published: 2026-08-03 03:31 – Updated: 2026-08-03 21:31
VLAI
Details

In Modem, there is a possible out of bounds read due to a missing bounds check. This could lead to remote denial of service, if a UE has connected to a rogue base station controlled by the attacker, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY00741071; Issue ID: MSV-7620.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-20479"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-03T03:16:42Z",
    "severity": "HIGH"
  },
  "details": "In Modem, there is a possible out of bounds read due to a missing bounds check. This could lead to remote denial of service, if a UE has connected to a rogue base station controlled by the attacker, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY00741071; Issue ID: MSV-7620.",
  "id": "GHSA-6g35-p5gh-6qh4",
  "modified": "2026-08-03T21:31:33Z",
  "published": "2026-08-03T03:31:57Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-20479"
    },
    {
      "type": "WEB",
      "url": "https://www.mediatek.com/product-security-bulletin/August-2026"
    }
  ],
  "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"
    }
  ]
}

GHSA-6G5Q-GCP5-PCWQ

Vulnerability from github – Published: 2025-05-26 21:30 – Updated: 2025-05-26 21:30
VLAI
Details

A vulnerability was found in Open Asset Import Library Assimp 5.4.3 and classified as problematic. This issue affects the function MDLImporter::InternReadFile_Quake1 of the file assimp/code/AssetLib/MDL/MDLLoader.cpp. The manipulation leads to out-of-bounds read. It is possible to launch the attack on the local host. The exploit has been disclosed to the public and may be used. The project decided to collect all Fuzzer bugs in a main-issue to address them in the future.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-5200"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-119",
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-05-26T19:15:19Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability was found in Open Asset Import Library Assimp 5.4.3 and classified as problematic. This issue affects the function MDLImporter::InternReadFile_Quake1 of the file assimp/code/AssetLib/MDL/MDLLoader.cpp. The manipulation leads to out-of-bounds read. It is possible to launch the attack on the local host. The exploit has been disclosed to the public and may be used. The project decided to collect all Fuzzer bugs in a main-issue to address them in the future.",
  "id": "GHSA-6g5q-gcp5-pcwq",
  "modified": "2025-05-26T21:30:31Z",
  "published": "2025-05-26T21:30:31Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-5200"
    },
    {
      "type": "WEB",
      "url": "https://github.com/assimp/assimp/issues/6128"
    },
    {
      "type": "WEB",
      "url": "https://github.com/assimp/assimp/issues/6172"
    },
    {
      "type": "WEB",
      "url": "https://github.com/user-attachments/files/20208985/line-452-reproducer.zip"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?ctiid.310289"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?id.310289"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?submit.578005"
    }
  ],
  "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: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-6G7G-W4F8-9C9X

Vulnerability from github – Published: 2026-03-18 13:00 – Updated: 2026-04-27 16:35
VLAI
Summary
github.com/buger/jsonparser has a denial of service vulnerability
Details

The Delete function fails to properly validate offsets when processing malformed JSON input. This can lead to a negative slice index and a runtime panic, allowing a denial of service attack.

Show details on source website

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 1.1.1"
      },
      "package": {
        "ecosystem": "Go",
        "name": "github.com/buger/jsonparser"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-32285"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125",
      "CWE-129"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-03-18T13:00:19Z",
    "nvd_published_at": "2026-03-26T20:16:12Z",
    "severity": "HIGH"
  },
  "details": "The Delete function fails to properly validate offsets when processing malformed JSON input. This can lead to a negative slice index and a runtime panic, allowing a denial of service attack.",
  "id": "GHSA-6g7g-w4f8-9c9x",
  "modified": "2026-04-27T16:35:20Z",
  "published": "2026-03-18T13:00:19Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-32285"
    },
    {
      "type": "WEB",
      "url": "https://github.com/buger/jsonparser/issues/275"
    },
    {
      "type": "WEB",
      "url": "https://github.com/golang/vulndb/issues/4514"
    },
    {
      "type": "WEB",
      "url": "https://github.com/buger/jsonparser/pull/276"
    },
    {
      "type": "WEB",
      "url": "https://github.com/buger/jsonparser/commit/a69e7e01cd4ad67bdfd3ac2c080b9212af16f4b0"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/buger/jsonparser"
    },
    {
      "type": "WEB",
      "url": "https://github.com/buger/jsonparser/releases/tag/v1.1.2"
    },
    {
      "type": "WEB",
      "url": "https://pkg.go.dev/vuln/GO-2026-4514"
    },
    {
      "type": "WEB",
      "url": "https://securityinfinity.com/research/buger-jsonparser-negative-slice-panic-dos-2026"
    }
  ],
  "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"
    }
  ],
  "summary": "github.com/buger/jsonparser has a denial of service vulnerability"
}

GHSA-6GHV-673H-JF67

Vulnerability from github – Published: 2024-08-13 18:31 – Updated: 2024-08-13 18:31
VLAI
Details

Windows Bluetooth Driver Information Disclosure Vulnerability

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-38123"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-08-13T18:15:13Z",
    "severity": "MODERATE"
  },
  "details": "Windows Bluetooth Driver Information Disclosure Vulnerability",
  "id": "GHSA-6ghv-673h-jf67",
  "modified": "2024-08-13T18:31:16Z",
  "published": "2024-08-13T18:31:16Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-38123"
    },
    {
      "type": "WEB",
      "url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2024-38123"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-6GJ2-XQ9H-5X4G

Vulnerability from github – Published: 2022-05-17 02:32 – Updated: 2022-05-17 02:32
VLAI
Details

Adobe Acrobat Reader versions 11.0.19 and earlier, 15.006.30280 and earlier, 15.023.20070 and earlier have a memory address leak vulnerability in the JPEG 2000 parser engine.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2017-3021"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-04-12T14:59:00Z",
    "severity": "MODERATE"
  },
  "details": "Adobe Acrobat Reader versions 11.0.19 and earlier, 15.006.30280 and earlier, 15.023.20070 and earlier have a memory address leak vulnerability in the JPEG 2000 parser engine.",
  "id": "GHSA-6gj2-xq9h-5x4g",
  "modified": "2022-05-17T02:32:44Z",
  "published": "2022-05-17T02:32:44Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-3021"
    },
    {
      "type": "WEB",
      "url": "https://helpx.adobe.com/security/products/acrobat/apsb17-11.html"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/97554"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id/1038228"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-6GJ3-G642-MV4H

Vulnerability from github – Published: 2024-05-03 03:31 – Updated: 2024-05-03 03:31
VLAI
Details

PDF-XChange Editor U3D File Parsing Out-Of-Bounds Read Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of PDF-XChange Editor. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.

The specific flaw exists within the parsing of U3D files. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-20930.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-42057"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-05-03T03:15:40Z",
    "severity": "HIGH"
  },
  "details": "PDF-XChange Editor U3D File Parsing Out-Of-Bounds Read Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of PDF-XChange Editor. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the parsing of U3D files. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-20930.",
  "id": "GHSA-6gj3-g642-mv4h",
  "modified": "2024-05-03T03:31:01Z",
  "published": "2024-05-03T03:31:01Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-42057"
    },
    {
      "type": "WEB",
      "url": "https://www.tracker-software.com/support/security-bulletins.html"
    },
    {
      "type": "WEB",
      "url": "https://www.zerodayinitiative.com/advisories/ZDI-23-1363"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-6GJ8-W93H-3R46

Vulnerability from github – Published: 2022-05-24 17:35 – Updated: 2022-05-24 17:35
VLAI
Details

An exploitable vulnerability exists in the way Pixar OpenUSD 20.05 handles parses certain encoded types. A specially crafted malformed file can trigger an arbitrary out of bounds memory access in SdfPath Type Index. This vulnerability could be used to bypass mitigations and aid further exploitation. To trigger this vulnerability, the victim needs to access an attacker-provided malformed file.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-13498"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-12-02T18:15:00Z",
    "severity": "MODERATE"
  },
  "details": "An exploitable vulnerability exists in the way Pixar OpenUSD 20.05 handles parses certain encoded types. A specially crafted malformed file can trigger an arbitrary out of bounds memory access in SdfPath Type Index. This vulnerability could be used to bypass mitigations and aid further exploitation. To trigger this vulnerability, the victim needs to access an attacker-provided malformed file.",
  "id": "GHSA-6gj8-w93h-3r46",
  "modified": "2022-05-24T17:35:06Z",
  "published": "2022-05-24T17:35:06Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-13498"
    },
    {
      "type": "WEB",
      "url": "https://talosintelligence.com/vulnerability_reports/TALOS-2020-1105"
    }
  ],
  "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-6GMV-PJP9-P8W8

Vulnerability from github – Published: 2022-02-09 18:29 – Updated: 2024-11-13 22:10
VLAI
Summary
Out of bounds read in Tensorflow
Details

Impact

The implementation of shape inference for ReverseSequence does not fully validate the value of batch_dim and can result in a heap OOB read:

import tensorflow as tf

@tf.function
def test():
  y = tf.raw_ops.ReverseSequence(
    input = ['aaa','bbb'],
    seq_lengths = [1,1,1],
    seq_dim = -10,
    batch_dim = -10 )
  return y

test()

There is a check to make sure the value of batch_dim does not go over the rank of the input, but there is no check for negative values:

  const int32_t input_rank = c->Rank(input);
  if (batch_dim >= input_rank) {
    return errors::InvalidArgument( 
        "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank);
  }
  // ...

  DimensionHandle batch_dim_dim = c->Dim(input, batch_dim);

Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of Dim would access elements before the start of an array:

  DimensionHandle Dim(ShapeHandle s, int64_t idx) {
    if (!s.Handle() || s->rank_ == kUnknownRank) {
      return UnknownDim();
    }
    return DimKnownRank(s, idx);
  } 
·
  static DimensionHandle DimKnownRank(ShapeHandle s, int64_t idx) {
    CHECK_NE(s->rank_, kUnknownRank);
    if (idx < 0) {
      return s->dims_[s->dims_.size() + idx];
    }
    return s->dims_[idx];
  }

Patches

We have patched the issue in GitHub commit 37c01fb5e25c3d80213060460196406c43d31995.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Yu Tian of Qihoo 360 AIVul Team.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-21728"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-03T18:29:10Z",
    "nvd_published_at": "2022-02-03T11:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact \nThe [implementation of shape inference for `ReverseSequence`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671) does not fully validate the value of `batch_dim` and can result in a heap OOB read:\n\n```python\nimport tensorflow as tf\n\n@tf.function\ndef test():\n  y = tf.raw_ops.ReverseSequence(\n    input = [\u0027aaa\u0027,\u0027bbb\u0027],\n    seq_lengths = [1,1,1],\n    seq_dim = -10,\n    batch_dim = -10 )\n  return y\n    \ntest()\n```\n\nThere is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values:\n\n```cc\n  const int32_t input_rank = c-\u003eRank(input);\n  if (batch_dim \u003e= input_rank) {\n    return errors::InvalidArgument( \n        \"batch_dim must be \u003c input rank: \", batch_dim, \" vs. \", input_rank);\n  }\n  // ...\n  \n  DimensionHandle batch_dim_dim = c-\u003eDim(input, batch_dim);\n``` \n    \nNegative dimensions are allowed in some cases to mimic Python\u0027s negative indexing (i.e., indexing from the end of the array), however if the value is too negative then [the implementation of `Dim`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428) would access elements before the start of an array:\n\n```cc\n  DimensionHandle Dim(ShapeHandle s, int64_t idx) {\n    if (!s.Handle() || s-\u003erank_ == kUnknownRank) {\n      return UnknownDim();\n    }\n    return DimKnownRank(s, idx);\n  } \n\u00b7\n  static DimensionHandle DimKnownRank(ShapeHandle s, int64_t idx) {\n    CHECK_NE(s-\u003erank_, kUnknownRank);\n    if (idx \u003c 0) {\n      return s-\u003edims_[s-\u003edims_.size() + idx];\n    }\n    return s-\u003edims_[idx];\n  }\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37c01fb5e25c3d80213060460196406c43d31995](https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Yu Tian of Qihoo 360 AIVul Team.",
  "id": "GHSA-6gmv-pjp9-p8w8",
  "modified": "2024-11-13T22:10:33Z",
  "published": "2022-02-09T18:29:24Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-21728"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-52.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-107.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Out of bounds read in Tensorflow"
}

GHSA-6GVG-8X78-PFQV

Vulnerability from github – Published: 2022-05-13 01:42 – Updated: 2022-05-13 01:42
VLAI
Details

The White Board protocol parser in tcpdump before 4.9.2 has a buffer over-read in print-wb.c:wb_prep(), several functions.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2017-13014"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-09-14T06:29:00Z",
    "severity": "CRITICAL"
  },
  "details": "The White Board protocol parser in tcpdump before 4.9.2 has a buffer over-read in print-wb.c:wb_prep(), several functions.",
  "id": "GHSA-6gvg-8x78-pfqv",
  "modified": "2022-05-13T01:42:54Z",
  "published": "2022-05-13T01:42:54Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-13014"
    },
    {
      "type": "WEB",
      "url": "https://github.com/the-tcpdump-group/tcpdump/commit/cc356512f512e7fa423b3674db4bb31dbe40ffec"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHEA-2018:0705"
    },
    {
      "type": "WEB",
      "url": "https://security.gentoo.org/glsa/201709-23"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/HT208221"
    },
    {
      "type": "WEB",
      "url": "http://www.debian.org/security/2017/dsa-3971"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id/1039307"
    },
    {
      "type": "WEB",
      "url": "http://www.tcpdump.org/tcpdump-changes.txt"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-6GVX-HWP2-7MFQ

Vulnerability from github – Published: 2024-05-20 18:31 – Updated: 2024-07-03 18:42
VLAI
Details

Buffer Overflow vulnerability in Waxlab wax v.0.9-3 and before allows an attacker to cause a denial of service via the Lua library component.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-31714"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-121",
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-05-20T18:15:10Z",
    "severity": "HIGH"
  },
  "details": "Buffer Overflow vulnerability in Waxlab wax v.0.9-3 and before allows an attacker to cause a denial of service via the Lua library component.",
  "id": "GHSA-6gvx-hwp2-7mfq",
  "modified": "2024-07-03T18:42:38Z",
  "published": "2024-05-20T18:31:23Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-31714"
    },
    {
      "type": "WEB",
      "url": "https://github.com/lakemoon602/vuln/blob/main/wax.md"
    }
  ],
  "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.
  • 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.