Common Weakness Enumeration

CWE-122

Allowed

Heap-based Buffer Overflow

Abstraction: Variant · Status: Draft

A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc().

4096 vulnerabilities reference this CWE, most recent first.

GHSA-62XM-7PJX-WFV7

Vulnerability from github – Published: 2025-11-07 00:30 – Updated: 2025-11-07 15:31
VLAI
Details

Heap buffer overflow in Video in Google Chrome prior to 141.0.7390.54 allowed a remote attacker to potentially perform a sandbox escape via a crafted HTML page. (Chromium security severity: High)

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-11206"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-11-06T22:15:38Z",
    "severity": "HIGH"
  },
  "details": "Heap buffer overflow in Video in Google Chrome prior to 141.0.7390.54 allowed a remote attacker to potentially perform a sandbox escape via a crafted HTML page. (Chromium security severity: High)",
  "id": "GHSA-62xm-7pjx-wfv7",
  "modified": "2025-11-07T15:31:29Z",
  "published": "2025-11-07T00:30:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-11206"
    },
    {
      "type": "WEB",
      "url": "https://chromereleases.googleblog.com/2025/09/stable-channel-update-for-desktop_30.html"
    },
    {
      "type": "WEB",
      "url": "https://issues.chromium.org/issues/444755026"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:L",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-62XQ-66FV-WC89

Vulnerability from github – Published: 2025-02-13 00:33 – Updated: 2025-02-13 00:33
VLAI
Details

Heap-based buffer overflow in BMC Firmware for the Intel(R) Server Board S2600WF, Intel(R) Server Board S2600ST, Intel(R) Server Board S2600BP, before version 02.01.0017 and Intel(R) Server Board M50CYP and Intel(R) Server Board D50TNP before version R01.01.0009 may allow a privileged user to enable escalation of privilege via local access.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-31276"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-02-12T22:15:29Z",
    "severity": "HIGH"
  },
  "details": "Heap-based buffer overflow in BMC Firmware for the Intel(R) Server Board S2600WF, Intel(R) Server Board S2600ST, Intel(R) Server Board S2600BP, before version 02.01.0017 and Intel(R) Server Board M50CYP and Intel(R) Server Board D50TNP before version R01.01.0009 may allow a privileged user to enable escalation of privilege via local access.",
  "id": "GHSA-62xq-66fv-wc89",
  "modified": "2025-02-13T00:33:03Z",
  "published": "2025-02-13T00:33:03Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-31276"
    },
    {
      "type": "WEB",
      "url": "https://intel.com/content/www/us/en/security-center/advisory/intel-sa-00990.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:C/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:H/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-637Q-M772-J8H6

Vulnerability from github – Published: 2026-01-13 18:31 – Updated: 2026-01-13 18:31
VLAI
Details

Time-of-check time-of-use (toctou) race condition in Windows Kernel Memory allows an authorized attacker to elevate privileges locally.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-20809"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-01-13T18:16:07Z",
    "severity": "HIGH"
  },
  "details": "Time-of-check time-of-use (toctou) race condition in Windows Kernel Memory allows an authorized attacker to elevate privileges locally.",
  "id": "GHSA-637q-m772-j8h6",
  "modified": "2026-01-13T18:31:08Z",
  "published": "2026-01-13T18:31:08Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-20809"
    },
    {
      "type": "WEB",
      "url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-20809"
    }
  ],
  "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"
    }
  ]
}

GHSA-63V4-WJQ3-45MP

Vulnerability from github – Published: 2025-09-09 18:31 – Updated: 2025-09-09 18:31
VLAI
Details

Integer overflow or wraparound in Windows Hyper-V allows an authorized attacker to elevate privileges locally.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-54091"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-09-09T17:15:52Z",
    "severity": "HIGH"
  },
  "details": "Integer overflow or wraparound in Windows Hyper-V allows an authorized attacker to elevate privileges locally.",
  "id": "GHSA-63v4-wjq3-45mp",
  "modified": "2025-09-09T18:31:20Z",
  "published": "2025-09-09T18:31:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-54091"
    },
    {
      "type": "WEB",
      "url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2025-54091"
    }
  ],
  "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"
    }
  ]
}

GHSA-63XM-RX5P-XVQR

Vulnerability from github – Published: 2020-09-25 18:28 – Updated: 2024-10-28 20:21
VLAI
Summary
Heap buffer overflow in Tensorflow
Details

Impact

The implementation of SparseFillEmptyRowsGrad uses a double indexing pattern: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L263-L269

It is possible for reverse_index_map(i) to be an index outside of bounds of grad_values, thus resulting in a heap buffer overflow.

Patches

We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15195"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-119",
      "CWE-122",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-09-25T17:15:00Z",
    "nvd_published_at": "2020-09-25T19:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nThe implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L263-L269\n\nIt is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow.\n\n### Patches\nWe have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions.\n\nWe recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by members of the Aivul Team from Qihoo 360.",
  "id": "GHSA-63xm-rx5p-xvqr",
  "modified": "2024-10-28T20:21:02Z",
  "published": "2020-09-25T18:28:29Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-63xm-rx5p-xvqr"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15195"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-275.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-310.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-118.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:N/SC:H/SI:H/SA:H",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Heap buffer overflow in Tensorflow"
}

GHSA-6465-93FG-6PFR

Vulnerability from github – Published: 2025-12-31 09:30 – Updated: 2025-12-31 09:30
VLAI
Details

FontForge SFD File Parsing Heap-based Buffer Overflow Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of FontForge. 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 SFD files. The issue results from the lack of proper validation of the length of user-supplied data prior to copying it to a heap-based buffer. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-28543.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-15275"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-12-31T07:15:51Z",
    "severity": "HIGH"
  },
  "details": "FontForge SFD File Parsing Heap-based Buffer Overflow Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of FontForge. 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 SFD files. The issue results from the lack of proper validation of the length of user-supplied data prior to copying it to a heap-based buffer. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-28543.",
  "id": "GHSA-6465-93fg-6pfr",
  "modified": "2025-12-31T09:30:18Z",
  "published": "2025-12-31T09:30:18Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-15275"
    },
    {
      "type": "WEB",
      "url": "https://www.zerodayinitiative.com/advisories/ZDI-25-1189"
    }
  ],
  "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-64HF-WV63-57H5

Vulnerability from github – Published: 2024-08-14 18:32 – Updated: 2024-08-14 18:32
VLAI
Details

Buffer overflow in some Zoom Workplace Apps, SDKs, Rooms Clients, and Rooms Controllers may allow an authenticated user to conduct a denial of service via network access.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-42438"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-08-14T17:15:17Z",
    "severity": "MODERATE"
  },
  "details": "Buffer overflow in some Zoom Workplace Apps, SDKs, Rooms Clients, and Rooms Controllers may allow an authenticated user to conduct a denial of service via network access.",
  "id": "GHSA-64hf-wv63-57h5",
  "modified": "2024-08-14T18:32:43Z",
  "published": "2024-08-14T18:32:43Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-42438"
    },
    {
      "type": "WEB",
      "url": "https://www.zoom.com/en/trust/security-bulletin/zsb-24031"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-64Q7-6GWG-J7H7

Vulnerability from github – Published: 2022-05-24 17:44 – Updated: 2022-05-24 17:44
VLAI
Details

Adobe Animate version 21.0.3 (and earlier) is affected by a Heap-based Buffer Overflow vulnerability. An unauthenticated attacker could leverage this vulnerability to achieve arbitrary code execution in the context of the current user. Exploitation of this issue requires user interaction in that a victim must open a malicious file.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-21077"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-03-12T19:15:00Z",
    "severity": "HIGH"
  },
  "details": "Adobe Animate version 21.0.3 (and earlier) is affected by a Heap-based Buffer Overflow vulnerability. An unauthenticated attacker could leverage this vulnerability to achieve arbitrary code execution in the context of the current user. Exploitation of this issue requires user interaction in that a victim must open a malicious file.",
  "id": "GHSA-64q7-6gwg-j7h7",
  "modified": "2022-05-24T17:44:29Z",
  "published": "2022-05-24T17:44:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-21077"
    },
    {
      "type": "WEB",
      "url": "https://helpx.adobe.com/security/products/animate/apsb21-21.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-654Q-R256-5C4P

Vulnerability from github – Published: 2022-07-16 00:00 – Updated: 2022-07-16 00:00
VLAI
Details

Adobe Character Animator version 4.4.7 (and earlier) and 22.4 (and earlier) are affected by a Heap-based Buffer Overflow vulnerability that could result in arbitrary code execution in the context of the current user. Exploitation of this issue requires user interaction in that a victim must open a malicious file.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-34241"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-07-15T16:15:00Z",
    "severity": "HIGH"
  },
  "details": "Adobe Character Animator version 4.4.7 (and earlier) and 22.4 (and earlier) are affected by a Heap-based Buffer Overflow vulnerability that could result in arbitrary code execution in the context of the current user. Exploitation of this issue requires user interaction in that a victim must open a malicious file.",
  "id": "GHSA-654q-r256-5c4p",
  "modified": "2022-07-16T00:00:29Z",
  "published": "2022-07-16T00:00:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-34241"
    },
    {
      "type": "WEB",
      "url": "https://helpx.adobe.com/security/products/character_animator/apsb22-34.html"
    }
  ],
  "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-6564-XVQW-FC42

Vulnerability from github – Published: 2024-04-09 18:30 – Updated: 2024-04-09 18:30
VLAI
Details

Windows Routing and Remote Access Service (RRAS) Remote Code Execution Vulnerability

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-26200"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-04-09T17:15:37Z",
    "severity": "HIGH"
  },
  "details": "Windows Routing and Remote Access Service (RRAS) Remote Code Execution Vulnerability",
  "id": "GHSA-6564-xvqw-fc42",
  "modified": "2024-04-09T18:30:25Z",
  "published": "2024-04-09T18:30:25Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-26200"
    },
    {
      "type": "WEB",
      "url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2024-26200"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

Mitigation

Pre-design: Use a language or compiler that performs automatic bounds checking.

Mitigation
Architecture and Design

Use an abstraction library to abstract away risky APIs. Not a complete solution.

Mitigation MIT-10
Operation Build and Compilation

Strategy: Environment Hardening

  • Use automatic buffer overflow detection mechanisms that are offered by certain compilers or compiler extensions. Examples include: the Microsoft Visual Studio /GS flag, Fedora/Red Hat FORTIFY_SOURCE GCC flag, StackGuard, and ProPolice, which provide various mechanisms including canary-based detection and range/index checking.
  • D3-SFCV (Stack Frame Canary Validation) from D3FEND [REF-1334] discusses canary-based detection in detail.
Mitigation MIT-11
Operation Build and Compilation

Strategy: Environment Hardening

  • Run or compile the software using features or extensions that randomly arrange the positions of a program's executable and libraries in memory. Because this makes the addresses unpredictable, it can prevent an attacker from reliably jumping to exploitable code.
  • Examples include Address Space Layout Randomization (ASLR) [REF-58] [REF-60] and Position-Independent Executables (PIE) [REF-64]. Imported modules may be similarly realigned if their default memory addresses conflict with other modules, in a process known as "rebasing" (for Windows) and "prelinking" (for Linux) [REF-1332] using randomly generated addresses. ASLR for libraries cannot be used in conjunction with prelink since it would require relocating the libraries at run-time, defeating the whole purpose of prelinking.
  • For more information on these techniques see D3-SAOR (Segment Address Offset Randomization) from D3FEND [REF-1335].
Mitigation
Implementation

Implement and perform bounds checking on input.

Mitigation
Implementation

Strategy: Libraries or Frameworks

Do not use dangerous functions such as gets. Look for their safe equivalent, which checks for the boundary.

Mitigation
Operation

Use OS-level preventative functionality. This is not a complete solution, but it provides some defense in depth.

CAPEC-92: Forced Integer Overflow

This attack forces an integer variable to go out of range. The integer variable is often used as an offset such as size of memory allocation or similarly. The attacker would typically control the value of such variable and try to get it out of range. For instance the integer in question is incremented past the maximum possible value, it may wrap to become a very small, or negative number, therefore providing a very incorrect value which can lead to unexpected behavior. At worst the attacker can execute arbitrary code.