Common Weakness Enumeration

CWE-787

Allowed-with-Review

Out-of-bounds Write

Abstraction: Base · Status: Draft

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

15108 vulnerabilities reference this CWE, most recent first.

GHSA-WCHC-GWPX-CHQH

Vulnerability from github – Published: 2024-05-03 03:30 – Updated: 2024-05-03 03:30
VLAI
Details

D-Link DAP-2622 DDP Reset Auth Username Stack-based Buffer Overflow Remote Code Execution Vulnerability. This vulnerability allows network-adjacent attackers to execute arbitrary code on affected installations of D-Link DAP-2622 routers. Authentication is not required to exploit this vulnerability.

The specific flaw exists within the DDP service. The issue results from the lack of proper validation of the length of user-supplied data prior to copying it to a fixed-length stack-based buffer. An attacker can leverage this vulnerability to execute code in the context of root. Was ZDI-CAN-20056.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-35729"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-121",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-05-03T02:15:36Z",
    "severity": "HIGH"
  },
  "details": "D-Link DAP-2622 DDP Reset Auth Username Stack-based Buffer Overflow Remote Code Execution Vulnerability. This vulnerability allows network-adjacent attackers to execute arbitrary code on affected installations of D-Link DAP-2622 routers. Authentication is not required to exploit this vulnerability.\n\nThe specific flaw exists within the DDP service. The issue results from the lack of proper validation of the length of user-supplied data prior to copying it to a fixed-length stack-based buffer. An attacker can leverage this vulnerability to execute code in the context of root. Was ZDI-CAN-20056.",
  "id": "GHSA-wchc-gwpx-chqh",
  "modified": "2024-05-03T03:30:52Z",
  "published": "2024-05-03T03:30:52Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-35729"
    },
    {
      "type": "WEB",
      "url": "https://supportannouncement.us.dlink.com/announcement/publication.aspx?name=SAP10349"
    },
    {
      "type": "WEB",
      "url": "https://www.zerodayinitiative.com/advisories/ZDI-23-1235"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:A/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-WCMQ-57JJ-6QWC

Vulnerability from github – Published: 2023-05-26 21:30 – Updated: 2025-11-04 00:30
VLAI
Details

NetScaler file parser crash in Wireshark 4.0.0 to 4.0.5 and 3.6.0 to 3.6.13 allows denial of service via crafted capture file

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-2858"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-05-26T21:15:18Z",
    "severity": "MODERATE"
  },
  "details": "NetScaler file parser crash in Wireshark 4.0.0 to 4.0.5 and 3.6.0 to 3.6.13 allows denial of service via crafted capture file",
  "id": "GHSA-wcmq-57jj-6qwc",
  "modified": "2025-11-04T00:30:37Z",
  "published": "2023-05-26T21:30:23Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-2858"
    },
    {
      "type": "WEB",
      "url": "https://gitlab.com/gitlab-org/cves/-/blob/master/2023/CVE-2023-2858.json"
    },
    {
      "type": "WEB",
      "url": "https://gitlab.com/wireshark/wireshark/-/issues/19081"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2023/06/msg00004.html"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2024/09/msg00049.html"
    },
    {
      "type": "WEB",
      "url": "https://security.gentoo.org/glsa/202309-02"
    },
    {
      "type": "WEB",
      "url": "https://www.debian.org/security/2023/dsa-5429"
    },
    {
      "type": "WEB",
      "url": "https://www.wireshark.org/security/wnpa-sec-2023-15.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:L",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-WCPQ-PW24-JXJP

Vulnerability from github – Published: 2024-07-09 21:30 – Updated: 2024-07-09 21:30
VLAI
Details

A vulnerability was discovered in Samsung Wearable Processor and Modems with versions Exynos 9110, Exynos Modem 5123, Exynos Modem 5300 that allows an out-of-bounds write in the heap in 2G (no auth).

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-50807"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-07-09T19:15:11Z",
    "severity": "HIGH"
  },
  "details": "A vulnerability was discovered in Samsung Wearable Processor and Modems with versions Exynos 9110, Exynos Modem 5123, Exynos Modem 5300 that allows an out-of-bounds write in the heap in 2G (no auth).",
  "id": "GHSA-wcpq-pw24-jxjp",
  "modified": "2024-07-09T21:30:35Z",
  "published": "2024-07-09T21:30:35Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-50807"
    },
    {
      "type": "WEB",
      "url": "https://semiconductor.samsung.com/support/quality-support/product-security-updates"
    },
    {
      "type": "WEB",
      "url": "https://semiconductor.samsung.com/support/quality-support/product-security-updates/cve-2023-50807"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-WCQG-52WC-66QC

Vulnerability from github – Published: 2023-08-07 06:30 – Updated: 2024-04-04 06:35
VLAI
Details

In wlan service, 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: ALPS07453587; Issue ID: ALPS07453587.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-20815"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-08-07T04:15:14Z",
    "severity": "MODERATE"
  },
  "details": "In wlan service, 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: ALPS07453587; Issue ID: ALPS07453587.",
  "id": "GHSA-wcqg-52wc-66qc",
  "modified": "2024-04-04T06:35:24Z",
  "published": "2023-08-07T06:30:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-20815"
    },
    {
      "type": "WEB",
      "url": "https://corp.mediatek.com/product-security-bulletin/August-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-WCRH-739X-W6V5

Vulnerability from github – Published: 2024-10-02 18:31 – Updated: 2024-10-02 18:31
VLAI
Details

A vulnerability in the web-based management interface of Cisco Small Business RV042, RV042G, RV320, and RV325 Routers could allow an authenticated, Administrator-level, remote attacker to cause an unexpected reload of an affected device, resulting in a denial of service (DoS) condition. To exploit this vulnerability, an attacker would need to have valid Administrator credentials on the affected device.   This vulnerability is due to improper validation of user input that is in incoming HTTP packets. An attacker could exploit this vulnerability by sending a crafted HTTP request to the web-based management interface of the affected device. A successful exploit could allow the attacker to cause an unexpected reload of the device, resulting in a DoS condition.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-20523"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-121",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-10-02T17:15:19Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability in the web-based management interface of Cisco Small Business RV042, RV042G, RV320, and RV325 Routers could allow an authenticated, Administrator-level, remote attacker to cause an unexpected reload of an affected device, resulting in a denial of service (DoS) condition. To exploit this vulnerability, an attacker would need to have valid Administrator credentials on the affected device.\n\u0026nbsp;\nThis vulnerability is due to improper validation of user input that is in incoming HTTP packets. An attacker could exploit this vulnerability by sending a crafted HTTP request to the web-based management interface of the affected device. A successful exploit could allow the attacker to cause an unexpected reload of the device, resulting in a DoS condition.",
  "id": "GHSA-wcrh-739x-w6v5",
  "modified": "2024-10-02T18:31:33Z",
  "published": "2024-10-02T18:31:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-20523"
    },
    {
      "type": "WEB",
      "url": "https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-sb-rv04x_rv32x_vulns-yJ2OSDhV"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:C/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-WCV5-68F6-32PR

Vulnerability from github – Published: 2026-01-16 00:30 – Updated: 2026-01-16 00:30
VLAI
Details

Buffer overflow in XPS font fpgm data processing on Small Office Multifunction Printers and Laser Printers() which may allow an attacker on the network segment to trigger the affected product being unresponsive or to execute arbitrary code. : Satera LBP670C Series/Satera MF750C Series firmware v06.02 and earlier sold in Japan.Color imageCLASS LBP630C/Color imageCLASS MF650C Series/imageCLASS LBP230 Series/imageCLASS X LBP1238 II/imageCLASS MF450 Series/imageCLASS X MF1238 II/imageCLASS X MF1643i II/imageCLASS X MF1643iF II firmware v06.02 and earlier sold in US.i-SENSYS LBP630C Series/i-SENSYS MF650C Series/i-SENSYS LBP230 Series/1238P II/1238Pr II/i-SENSYS MF450 Series/i-SENSYS MF550 Series/1238i II/1238iF II/imageRUNNER 1643i II/imageRUNNER 1643iF II firmware v06.02 and earlier sold in Europe.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-14235"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-01-16T00:16:27Z",
    "severity": "CRITICAL"
  },
  "details": "Buffer overflow in XPS font fpgm data processing on Small Office Multifunction Printers and Laser Printers(*) which may allow an attacker on the network segment to trigger the affected product being unresponsive or to execute arbitrary code. *: Satera LBP670C Series/Satera MF750C Series firmware v06.02 and earlier sold in Japan.Color imageCLASS LBP630C/Color imageCLASS MF650C Series/imageCLASS LBP230 Series/imageCLASS X LBP1238 II/imageCLASS MF450 Series/imageCLASS X MF1238 II/imageCLASS X MF1643i II/imageCLASS X MF1643iF II firmware v06.02 and earlier sold in US.i-SENSYS LBP630C Series/i-SENSYS MF650C Series/i-SENSYS LBP230 Series/1238P II/1238Pr II/i-SENSYS MF450 Series/i-SENSYS MF550 Series/1238i II/1238iF II/imageRUNNER 1643i II/imageRUNNER 1643iF II firmware v06.02 and earlier sold in Europe.",
  "id": "GHSA-wcv5-68f6-32pr",
  "modified": "2026-01-16T00:30:55Z",
  "published": "2026-01-16T00:30:55Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-14235"
    },
    {
      "type": "WEB",
      "url": "https://canon.jp/support/support-info/260115vulnerability-response"
    },
    {
      "type": "WEB",
      "url": "https://psirt.canon/advisory-information/cp2026-001"
    },
    {
      "type": "WEB",
      "url": "https://www.canon-europe.com/support/product-security"
    },
    {
      "type": "WEB",
      "url": "https://www.usa.canon.com/support/canon-product-advisories/Service-Notice-Regarding-Remediation-Measure-Against-Potential-Buffer-Overflow-Vulnerability-in-Laser-Printers-and-Small-Office-Multifunctional-Printers"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/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-WCV5-QRJ6-9PFM

Vulnerability from github – Published: 2021-05-21 14:21 – Updated: 2024-10-30 23:11
VLAI
Summary
Heap buffer overflow in `Conv3DBackprop*`
Details

Impact

Missing validation between arguments to tf.raw_ops.Conv3DBackprop* operations can result in heap buffer overflows:

import tensorflow as tf

input_sizes = tf.constant([1, 1, 1, 1, 2], shape=[5], dtype=tf.int32)
filter_tensor = tf.constant([734.6274508233133, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0,
                            -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0,
                            -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0], shape=[4, 1, 6, 1, 1], dtype=tf.float32)
out_backprop = tf.constant([-10.0], shape=[1, 1, 1, 1, 1], dtype=tf.float32)

tf.raw_ops.Conv3DBackpropInputV2(input_sizes=input_sizes, filter=filter_tensor, out_backprop=out_backprop, strides=[1, 89, 29, 89, 1], padding='SAME', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])
import tensorflow as tf

input_values = [-10.0] * (7 * 7 * 7 * 7 * 7)
input_values[0] = 429.6491056791816
input_sizes = tf.constant(input_values, shape=[7, 7, 7, 7, 7], dtype=tf.float32)
filter_tensor = tf.constant([7, 7, 7, 1, 1], shape=[5], dtype=tf.int32)
out_backprop = tf.constant([-10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0], shape=[7, 1, 1, 1, 1], dtype=tf.float32)

tf.raw_ops.Conv3DBackpropFilterV2(input=input_sizes, filter_sizes=filter_tensor, out_backprop=out_backprop, strides=[1, 37, 65, 93, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])

This is because the implementation assumes that the input, filter_sizes and out_backprop tensors have the same shape, as they are accessed in parallel.

Patches

We have patched the issue in GitHub commit 8f37b52e1320d8d72a9529b2468277791a261197.

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 securityguide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
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          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
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          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
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        }
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      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
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        {
          "events": [
            {
              "introduced": "2.4.0"
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            {
              "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-2021-29520"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-120",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T23:25:06Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nMissing validation between arguments to `tf.raw_ops.Conv3DBackprop*` operations can result in heap buffer overflows:\n\n```python\nimport tensorflow as tf\n\ninput_sizes = tf.constant([1, 1, 1, 1, 2], shape=[5], dtype=tf.int32)\nfilter_tensor = tf.constant([734.6274508233133, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0,\n                            -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0,\n                            -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0], shape=[4, 1, 6, 1, 1], dtype=tf.float32)\nout_backprop = tf.constant([-10.0], shape=[1, 1, 1, 1, 1], dtype=tf.float32)\n\ntf.raw_ops.Conv3DBackpropInputV2(input_sizes=input_sizes, filter=filter_tensor, out_backprop=out_backprop, strides=[1, 89, 29, 89, 1], padding=\u0027SAME\u0027, data_format=\u0027NDHWC\u0027, dilations=[1, 1, 1, 1, 1])\n```\n```python\nimport tensorflow as tf\n\ninput_values = [-10.0] * (7 * 7 * 7 * 7 * 7)\ninput_values[0] = 429.6491056791816\ninput_sizes = tf.constant(input_values, shape=[7, 7, 7, 7, 7], dtype=tf.float32)\nfilter_tensor = tf.constant([7, 7, 7, 1, 1], shape=[5], dtype=tf.int32)\nout_backprop = tf.constant([-10.0, -10.0, -10.0, -10.0, -10.0, -10.0, -10.0], shape=[7, 1, 1, 1, 1], dtype=tf.float32)\n  \ntf.raw_ops.Conv3DBackpropFilterV2(input=input_sizes, filter_sizes=filter_tensor, out_backprop=out_backprop, strides=[1, 37, 65, 93, 1], padding=\u0027VALID\u0027, data_format=\u0027NDHWC\u0027, dilations=[1, 1, 1, 1, 1])\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/4814fafb0ca6b5ab58a09411523b2193fed23fed/tensorflow/core/kernels/conv_grad_shape_utils.cc#L94-L153) assumes that the `input`, `filter_sizes` and `out_backprop` tensors have the same shape, as they are accessed in parallel.\n\n### Patches\nWe have patched the issue in GitHub commit [8f37b52e1320d8d72a9529b2468277791a261197](https://github.com/tensorflow/tensorflow/commit/8f37b52e1320d8d72a9529b2468277791a261197).\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 securityguide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.",
  "id": "GHSA-wcv5-qrj6-9pfm",
  "modified": "2024-10-30T23:11:45Z",
  "published": "2021-05-21T14:21:12Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wcv5-qrj6-9pfm"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29520"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/8f37b52e1320d8d72a9529b2468277791a261197"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-448.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-646.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-157.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 `Conv3DBackprop*`"
}

GHSA-WCV6-X2HG-7WQJ

Vulnerability from github – Published: 2022-05-24 17:03 – Updated: 2022-05-24 17:03
VLAI
Details

A vulnerability has been identified in SPPA-T3000 MS3000 Migration Server (All versions). An attacker with network access to the MS3000 Server could trigger a Denial-of-Service condition by sending specifically crafted packets to port 5010/tcp. This vulnerability is independent from CVE-2019-18290, CVE-2019-18291, CVE-2019-18294, CVE-2019-18298, CVE-2019-18299, CVE-2019-18300, CVE-2019-18301, CVE-2019-18302, CVE-2019-18303, CVE-2019-18304, CVE-2019-18305, CVE-2019-18306, and CVE-2019-18307. Please note that an attacker needs to have network access to the MS3000 in order to exploit this vulnerability. At the time of advisory publication no public exploitation of this security vulnerability was known.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2019-18292"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-12-12T19:15:00Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability has been identified in SPPA-T3000 MS3000 Migration Server (All versions). An attacker with network access to the MS3000 Server could trigger a Denial-of-Service condition by sending specifically crafted packets to port 5010/tcp. This vulnerability is independent from CVE-2019-18290, CVE-2019-18291, CVE-2019-18294, CVE-2019-18298, CVE-2019-18299, CVE-2019-18300, CVE-2019-18301, CVE-2019-18302, CVE-2019-18303, CVE-2019-18304, CVE-2019-18305, CVE-2019-18306, and CVE-2019-18307. Please note that an attacker needs to have network access to the MS3000 in order to exploit this vulnerability. At the time of advisory publication no public exploitation of this security vulnerability was known.",
  "id": "GHSA-wcv6-x2hg-7wqj",
  "modified": "2022-05-24T17:03:23Z",
  "published": "2022-05-24T17:03:23Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-18292"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/pdf/ssa-451445.pdf"
    },
    {
      "type": "WEB",
      "url": "http://packetstormsecurity.com/files/155665/Siemens-Security-Advisory-SPPA-T3000-Code-Execution.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-WCVH-Q8PM-3Q7Q

Vulnerability from github – Published: 2022-05-13 01:18 – Updated: 2022-05-13 01:18
VLAI
Details

The vlc_demux_chained_Delete function in input/demux_chained.c in VideoLAN VLC media player 3.0.1 allows remote attackers to cause a denial of service (heap corruption and application crash) or possibly have unspecified other impact via a crafted .swf file.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2018-11516"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-416",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-05-28T16:29:00Z",
    "severity": "HIGH"
  },
  "details": "The vlc_demux_chained_Delete function in input/demux_chained.c in VideoLAN VLC media player 3.0.1 allows remote attackers to cause a denial of service (heap corruption and application crash) or possibly have unspecified other impact via a crafted .swf file.",
  "id": "GHSA-wcvh-q8pm-3q7q",
  "modified": "2022-05-13T01:18:56Z",
  "published": "2022-05-13T01:18:56Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-11516"
    },
    {
      "type": "WEB",
      "url": "http://code610.blogspot.com/2018/05/make-free-vlc.html"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/104293"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id/1041312"
    },
    {
      "type": "WEB",
      "url": "http://www.videolan.org/security/sa1801.html"
    }
  ],
  "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-WCWJ-33H6-VXQV

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

An exploitable denial of service vulnerability exists in the freeDiameter functionality of freeDiameter 1.3.2. A specially crafted Diameter request can trigger a memory corruption resulting in denial-of-service. An attacker can send a malicious packet to trigger this vulnerability.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-6098"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-191",
      "CWE-20",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-07-28T22:15:00Z",
    "severity": "MODERATE"
  },
  "details": "An exploitable denial of service vulnerability exists in the freeDiameter functionality of freeDiameter 1.3.2. A specially crafted Diameter request can trigger a memory corruption resulting in denial-of-service. An attacker can send a malicious packet to trigger this vulnerability.",
  "id": "GHSA-wcwj-33h6-vxqv",
  "modified": "2022-05-24T17:24:40Z",
  "published": "2022-05-24T17:24:40Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-6098"
    },
    {
      "type": "WEB",
      "url": "https://talosintelligence.com/vulnerability_reports/TALOS-2020-1030"
    }
  ],
  "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-3
Requirements

Strategy: Language Selection

  • Use a language that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
  • For example, many languages that perform their own memory management, such as Java and Perl, are not subject to buffer overflows. Other languages, such as Ada and C#, typically provide overflow protection, but the protection can be disabled by the programmer.
  • Be wary that a language's interface to native code may still be subject to overflows, even if the language itself is theoretically safe.
Mitigation MIT-4.1
Architecture and Design

Strategy: Libraries or Frameworks

  • Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
  • Examples include the Safe C String Library (SafeStr) by Messier and Viega [REF-57], and the Strsafe.h library from Microsoft [REF-56]. These libraries provide safer versions of overflow-prone string-handling functions.
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-9
Implementation
  • Consider adhering to the following rules when allocating and managing an application's memory:
  • Double check that the buffer is as large as specified.
  • When using functions that accept a number of bytes to copy, such as strncpy(), be aware that if the destination buffer size is equal to the source buffer size, it may not NULL-terminate the string.
  • Check buffer boundaries if accessing the buffer in a loop and make sure there is no danger of writing past the allocated space.
  • If necessary, truncate all input strings to a reasonable length before passing them to the copy and concatenation functions.
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 MIT-12
Operation

Strategy: Environment Hardening

  • Use a CPU and operating system that offers Data Execution Protection (using hardware NX or XD bits) or the equivalent techniques that simulate this feature in software, such as PaX [REF-60] [REF-61]. These techniques ensure that any instruction executed is exclusively at a memory address that is part of the code segment.
  • For more information on these techniques see D3-PSEP (Process Segment Execution Prevention) from D3FEND [REF-1336].
Mitigation MIT-13
Implementation

Replace unbounded copy functions with analogous functions that support length arguments, such as strcpy with strncpy. Create these if they are not available.

No CAPEC attack patterns related to this CWE.