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.

15126 vulnerabilities reference this CWE, most recent first.

GHSA-Q4Q4-FWJ6-52R8

Vulnerability from github – Published: 2023-10-30 18:30 – Updated: 2023-11-03 21:30
VLAI
Details

In Bluetooth, there is a possible out of bounds write due to a heap buffer overflow. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-21380"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-10-30T18:15:09Z",
    "severity": "MODERATE"
  },
  "details": "In Bluetooth, there is a possible out of bounds write due to a heap buffer overflow. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.",
  "id": "GHSA-q4q4-fwj6-52r8",
  "modified": "2023-11-03T21:30:25Z",
  "published": "2023-10-30T18:30:25Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-21380"
    },
    {
      "type": "WEB",
      "url": "https://source.android.com/docs/security/bulletin/android-14"
    }
  ],
  "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-Q4QF-3FC6-8X34

Vulnerability from github – Published: 2020-09-25 18:28 – Updated: 2024-10-30 21:12
VLAI
Summary
Segfault and data corruption in tensorflow-lite
Details

Impact

To mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72

If the DCHECK does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption.

Patches

We have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a and will release patch releases for all versions between 1.15 and 2.3.

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-2020-15207"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-119",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-09-25T17:55:41Z",
    "nvd_published_at": "2020-09-25T19:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nTo mimic Python\u0027s indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72\n\nIf the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption.\n### Patches\nWe have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a and will release patch releases for all versions between 1.15 and 2.3.\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-q4qf-3fc6-8x34",
  "modified": "2024-10-30T21:12:25Z",
  "published": "2020-09-25T18:28:43Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q4qf-3fc6-8x34"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15207"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/2d88f470dea2671b430884260f3626b1fe99830a"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-287.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-322.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-130.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:N/UI:N/S:C/C:N/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:N/SC:N/SI:H/SA:H",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Segfault and data corruption in tensorflow-lite"
}

GHSA-Q4QF-R73J-H8WF

Vulnerability from github – Published: 2022-12-31 00:30 – Updated: 2023-01-11 21:30
VLAI
Details

NVIDIA GPU Display Driver for Windows contains a vulnerability in the user mode layer, where an unprivileged regular user can cause an out-of-bounds write, which may lead to code execution, denial of service, escalation of privileges, information disclosure, or data tampering.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-34671"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-12-30T23:15:00Z",
    "severity": "HIGH"
  },
  "details": "NVIDIA GPU Display Driver for Windows contains a vulnerability in the user mode layer, where an unprivileged regular user can cause an out-of-bounds write, which may lead to code execution, denial of service, escalation of privileges, information disclosure, or data tampering.",
  "id": "GHSA-q4qf-r73j-h8wf",
  "modified": "2023-01-11T21:30:41Z",
  "published": "2022-12-31T00:30:23Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-34671"
    },
    {
      "type": "WEB",
      "url": "https://nvidia.custhelp.com/app/answers/detail/a_id/5415"
    },
    {
      "type": "WEB",
      "url": "https://nvidia.custhelp.com/app/answers/detail/a_id/5468"
    },
    {
      "type": "WEB",
      "url": "https://www.talosintelligence.com/vulnerability_reports/TALOS-2023-1719"
    },
    {
      "type": "WEB",
      "url": "https://www.talosintelligence.com/vulnerability_reports/TALOS-2023-1720"
    },
    {
      "type": "WEB",
      "url": "https://www.talosintelligence.com/vulnerability_reports/TALOS-2023-1721"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-Q4QJ-2F5M-98GC

Vulnerability from github – Published: 2022-05-13 01:21 – Updated: 2023-07-21 19:24
VLAI
Summary
ChakraCore RCE Vulnerability
Details

A remote code execution vulnerability exists in the way that the Chakra scripting engine handles objects in memory in Microsoft Edge, aka "Chakra Scripting Engine Memory Corruption Vulnerability." This affects Microsoft Edge, ChakraCore. This CVE ID is unique from CVE-2018-8617, CVE-2018-8618, CVE-2018-8624, CVE-2018-8629.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "NuGet",
        "name": "Microsoft.ChakraCore"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.11.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2018-8583"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2023-07-21T19:24:19Z",
    "nvd_published_at": "2018-12-12T00:29:00Z",
    "severity": "HIGH"
  },
  "details": "A remote code execution vulnerability exists in the way that the Chakra scripting engine handles objects in memory in Microsoft Edge, aka \"Chakra Scripting Engine Memory Corruption Vulnerability.\" This affects Microsoft Edge, ChakraCore. This CVE ID is unique from CVE-2018-8617, CVE-2018-8618, CVE-2018-8624, CVE-2018-8629.",
  "id": "GHSA-q4qj-2f5m-98gc",
  "modified": "2023-07-21T19:24:19Z",
  "published": "2022-05-13T01:21:01Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-8583"
    },
    {
      "type": "WEB",
      "url": "https://github.com/chakra-core/ChakraCore/pull/5869"
    },
    {
      "type": "WEB",
      "url": "https://github.com/chakra-core/ChakraCore/commit/8d21cde342a4e826d96eb4ac85241f876b879aed"
    },
    {
      "type": "WEB",
      "url": "https://portal.msrc.microsoft.com/en-US/security-guidance/advisory/CVE-2018-8583"
    },
    {
      "type": "WEB",
      "url": "https://web.archive.org/web/20210124222840/http://www.securityfocus.com/bid/106111"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "ChakraCore RCE Vulnerability"
}

GHSA-Q4QR-2V9Q-C9MQ

Vulnerability from github – Published: 2022-05-24 17:20 – Updated: 2022-05-24 17:20
VLAI
Details

Multiple vulnerabilities in the web-based management interface of Cisco Small Business RV320 and RV325 Series Routers and Cisco Small Business RV016, RV042, and RV082 Routers could allow an authenticated, remote attacker with administrative privileges to execute arbitrary code on an affected device. The vulnerabilities are due to insufficient boundary restrictions on user-supplied input to scripts in the web-based management interface. An attacker with administrative privileges that are sufficient to log in to the web-based management interface could exploit each vulnerability by sending crafted requests that contain overly large values to an affected device, causing a stack overflow. A successful exploit could allow the attacker to cause the device to crash or allow the attacker to execute arbitrary code with root privileges on the underlying operating system.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-3289"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-06-18T03:15:00Z",
    "severity": "HIGH"
  },
  "details": "Multiple vulnerabilities in the web-based management interface of Cisco Small Business RV320 and RV325 Series Routers and Cisco Small Business RV016, RV042, and RV082 Routers could allow an authenticated, remote attacker with administrative privileges to execute arbitrary code on an affected device. The vulnerabilities are due to insufficient boundary restrictions on user-supplied input to scripts in the web-based management interface. An attacker with administrative privileges that are sufficient to log in to the web-based management interface could exploit each vulnerability by sending crafted requests that contain overly large values to an affected device, causing a stack overflow. A successful exploit could allow the attacker to cause the device to crash or allow the attacker to execute arbitrary code with root privileges on the underlying operating system.",
  "id": "GHSA-q4qr-2v9q-c9mq",
  "modified": "2022-05-24T17:20:57Z",
  "published": "2022-05-24T17:20:57Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-3289"
    },
    {
      "type": "WEB",
      "url": "https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-rv-routers-stack-vUxHmnNz"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-Q4QX-HMMJ-4GJ8

Vulnerability from github – Published: 2023-05-08 21:31 – Updated: 2024-04-04 03:52
VLAI
Details

A memory corruption issue was addressed with improved state management. This issue is fixed in macOS Ventura 13.3, Studio Display Firmware Update 16.4. An app may be able to execute arbitrary code with kernel privileges

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-27965"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-05-08T20:15:18Z",
    "severity": "HIGH"
  },
  "details": "A memory corruption issue was addressed with improved state management. This issue is fixed in macOS Ventura 13.3, Studio Display Firmware Update 16.4. An app may be able to execute arbitrary code with kernel privileges",
  "id": "GHSA-q4qx-hmmj-4gj8",
  "modified": "2024-04-04T03:52:15Z",
  "published": "2023-05-08T21:31:07Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-27965"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/en-us/HT213670"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/en-us/HT213672"
    }
  ],
  "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-Q4R3-M48V-FH5V

Vulnerability from github – Published: 2025-11-10 18:30 – Updated: 2025-11-17 21:31
VLAI
Details

Tenda AX-1803 v1.0.0.1 was discovered to contain a stack overflow via the wanMTU parameter in the sub_4F55C function. This vulnerability allows attackers to cause a Denial of Service (DoS) via a crafted request.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-63457"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-121",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-11-10T17:15:35Z",
    "severity": "HIGH"
  },
  "details": "Tenda AX-1803 v1.0.0.1 was discovered to contain a stack overflow via the wanMTU parameter in the sub_4F55C function. This vulnerability allows attackers to cause a Denial of Service (DoS) via a crafted request.",
  "id": "GHSA-q4r3-m48v-fh5v",
  "modified": "2025-11-17T21:31:19Z",
  "published": "2025-11-10T18:30:34Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-63457"
    },
    {
      "type": "WEB",
      "url": "https://github.com/0-fool/VulnbyCola/blob/main/Tenda/AX-1803/1/1.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"
    }
  ]
}

GHSA-Q4R3-MQQ6-78X5

Vulnerability from github – Published: 2022-05-24 16:50 – Updated: 2022-05-24 16:50
VLAI
Details

An Integer Underflow in MP4_EIA608_Convert() in modules/demux/mp4/mp4.c in VideoLAN VLC media player through 3.0.7.1 allows remote attackers to cause a denial of service (heap-based buffer overflow and crash) or possibly have unspecified other impact via a crafted .mp4 file.

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{
  "affected": [],
  "aliases": [
    "CVE-2019-13602"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-191",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-07-14T21:15:00Z",
    "severity": "HIGH"
  },
  "details": "An Integer Underflow in MP4_EIA608_Convert() in modules/demux/mp4/mp4.c in VideoLAN VLC media player through 3.0.7.1 allows remote attackers to cause a denial of service (heap-based buffer overflow and crash) or possibly have unspecified other impact via a crafted .mp4 file.",
  "id": "GHSA-q4r3-mqq6-78x5",
  "modified": "2022-05-24T16:50:13Z",
  "published": "2022-05-24T16:50:13Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-13602"
    },
    {
      "type": "WEB",
      "url": "https://git.videolan.org/?p=vlc.git;a=commit;h=8e8e0d72447f8378244f5b4a3dcde036dbeb1491"
    },
    {
      "type": "WEB",
      "url": "https://git.videolan.org/?p=vlc.git;a=commit;h=b2b157076d9e94df34502dd8df0787deb940e938"
    },
    {
      "type": "WEB",
      "url": "https://seclists.org/bugtraq/2019/Aug/36"
    },
    {
      "type": "WEB",
      "url": "https://security.gentoo.org/glsa/201909-02"
    },
    {
      "type": "WEB",
      "url": "https://usn.ubuntu.com/4074-1"
    },
    {
      "type": "WEB",
      "url": "https://www.debian.org/security/2019/dsa-4504"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00005.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00037.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00040.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00081.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00036.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00046.html"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/109158"
    }
  ],
  "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-Q4R3-RJ3J-6C93

Vulnerability from github – Published: 2022-11-08 12:00 – Updated: 2022-11-08 19:00
VLAI
Details

A vulnerability has been identified in JT2Go (All versions < V14.1.0.4), Teamcenter Visualization V13.3 (All versions < V13.3.0.7), Teamcenter Visualization V14.0 (All versions < V14.0.0.3), Teamcenter Visualization V14.1 (All versions < V14.1.0.4). The affected products contain an out of bounds write vulnerability when parsing a CGM file. An attacker can leverage this vulnerability to execute code in the context of the current process.

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{
  "affected": [],
  "aliases": [
    "CVE-2022-41660"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-11-08T11:15:00Z",
    "severity": "HIGH"
  },
  "details": "A vulnerability has been identified in JT2Go (All versions \u003c V14.1.0.4), Teamcenter Visualization V13.3 (All versions \u003c V13.3.0.7), Teamcenter Visualization V14.0 (All versions \u003c V14.0.0.3), Teamcenter Visualization V14.1 (All versions \u003c V14.1.0.4). The affected products contain an out of bounds write vulnerability when parsing a CGM file. An attacker can leverage this vulnerability to execute code in the context of the current process.",
  "id": "GHSA-q4r3-rj3j-6c93",
  "modified": "2022-11-08T19:00:22Z",
  "published": "2022-11-08T12:00:18Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-41660"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/pdf/ssa-120378.pdf"
    }
  ],
  "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-Q4R7-VVV3-CGV4

Vulnerability from github – Published: 2024-01-02 03:30 – Updated: 2024-01-05 12:30
VLAI
Details

In battery, there is a possible memory corruption due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08308070; Issue ID: ALPS08308616.

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{
  "affected": [],
  "aliases": [
    "CVE-2023-32882"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-01-02T03:15:08Z",
    "severity": "MODERATE"
  },
  "details": "In battery, there is a possible memory corruption due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08308070; Issue ID: ALPS08308616.",
  "id": "GHSA-q4r7-vvv3-cgv4",
  "modified": "2024-01-05T12:30:19Z",
  "published": "2024-01-02T03:30:30Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-32882"
    },
    {
      "type": "WEB",
      "url": "https://corp.mediatek.com/product-security-bulletin/January-2024"
    }
  ],
  "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"
    }
  ]
}

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.