Common Weakness Enumeration

CWE-787

Weakness 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.

Dimensions

  • Behavior-Type: Write
  • Resource-Type: Memory Buffer
  • Resource-Property: Out-of-bounds
Mapping guidance

This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities. However, closer examination is required.

While this CWE is allowed for mapping, it has more specific children that might be a better fit. Carefully read both the name and description to ensure that this mapping is appropriate. Consider the root cause errors that have led to the out-of-bounds write by examining "CanFollow" relationships for this entry.

Relationships and members
ChildOf: CWE-119 · View CWE-1000
ChildOf: CWE-119 · View CWE-1003
ChildOf: CWE-119 · View CWE-1305
ChildOf: CWE-119 · View CWE-1340
Modes of introduction
Implementation
Detection methods

Automated Static Analysis

This weakness can often be detected using automated static analysis tools. Many modern tools use data flow analysis or constraint-based techniques to minimize the number of false positives.

Automated static analysis generally does not account for environmental considerations when reporting out-of-bounds memory operations. This can make it difficult for users to determine which warnings should be investigated first. For example, an analysis tool might report buffer overflows that originate from command line arguments in a program that is not expected to run with setuid or other special privileges.

Effectiveness: High

Detection techniques for buffer-related errors are more mature than for most other weakness types.

Automated Dynamic Analysis

This weakness can be detected using dynamic tools and techniques that interact with the software using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The software's operation may slow down, but it should not become unstable, crash, or generate incorrect results.

Automated Dynamic Analysis

Use tools that are integrated during compilation to insert runtime error-checking mechanisms related to memory safety errors, such as AddressSanitizer (ASan) for C/C++ [REF-1518].

Effectiveness: Moderate

Crafted inputs are necessary to reach the code containing the error, such as generated by fuzzers. Also, these tools may reduce performance, and they only report the error condition - not the original mistake that led to the error.

Content history
Submission: CWE Content Team · MITRE · 2009-10-21 · CWE 1.6
Contribution: "Mapping CWE to 62443" Sub-Working Group · CWE-CAPEC ICS/OT SIG · 2023-04-25 · CWE 4.11

Suggested mappings to ISA/IEC 62443.

Contribution: Abhi Balakrishnan · 2024-02-29 · CWE 4.15

Provided diagram to improve CWE usability

Modification: CWE Content Team · MITRE · 2010-02-16 · CWE 1.8

updated Demonstrative_Examples

Modification: CWE Content Team · MITRE · 2010-09-27 · CWE 1.10

updated Relationships

Modification: CWE Content Team · MITRE · 2011-06-01 · CWE 1.13

updated Common_Consequences

Modification: CWE Content Team · MITRE · 2014-06-23 · CWE 2.7

updated Demonstrative_Examples

Modification: CWE Content Team · MITRE · 2015-12-07 · CWE 2.9

updated Relationships

Modification: CWE Content Team · MITRE · 2018-03-27 · CWE 3.1

updated Description

Modification: CWE Content Team · MITRE · 2019-09-19 · CWE 3.4

updated Applicable_Platforms, Demonstrative_Examples, Detection_Factors, Likelihood_of_Exploit, Observed_Examples, Potential_Mitigations, References, Relationships, Time_of_Introduction

Modification: CWE Content Team · MITRE · 2020-02-24 · CWE 4.0

updated Observed_Examples, Relationships

Modification: CWE Content Team · MITRE · 2020-06-25 · CWE 4.1

updated Observed_Examples

Modification: CWE Content Team · MITRE · 2020-08-20 · CWE 4.2

updated Alternate_Terms, Demonstrative_Examples, Observed_Examples, Relationships

Modification: CWE Content Team · MITRE · 2020-12-10 · CWE 4.3

updated Relationships

Modification: CWE Content Team · MITRE · 2021-03-15 · CWE 4.4

updated Demonstrative_Examples

Modification: CWE Content Team · MITRE · 2021-07-20 · CWE 4.5

updated Demonstrative_Examples, Potential_Mitigations, Relationships

Modification: CWE Content Team · MITRE · 2022-06-28 · CWE 4.8

updated Observed_Examples, Relationships

Modification: CWE Content Team · MITRE · 2022-10-13 · CWE 4.9

updated Applicable_Platforms

Modification: CWE Content Team · MITRE · 2023-01-31 · CWE 4.10

updated Alternate_Terms, Demonstrative_Examples, Description

Modification: CWE Content Team · MITRE · 2023-04-27 · CWE 4.11

updated Potential_Mitigations, References, Relationships, Taxonomy_Mappings

Modification: CWE Content Team · MITRE · 2023-06-29 · CWE 4.12

updated Mapping_Notes, Relationships, Taxonomy_Mappings

Modification: CWE Content Team · MITRE · 2024-02-29 · CWE 4.14

updated Demonstrative_Examples

Modification: CWE Content Team · MITRE · 2024-07-16 · CWE 4.15

updated Alternate_Terms, Common_Consequences, Description, Diagram, Weakness_Ordinalities

Modification: CWE Content Team · MITRE · 2024-11-19 · CWE 4.16

updated Observed_Examples, Relationships

Modification: CWE Content Team · MITRE · 2025-04-03 · CWE 4.17

updated Observed_Examples, Relationships

Modification: CWE Content Team · MITRE · 2025-09-09 · CWE 4.18

updated Affected_Resources, Functional_Areas, References

Modification: CWE Content Team · MITRE · 2025-12-11 · CWE 4.19

updated Applicable_Platforms, Detection_Factors, References, Relationships

Modification: CWE Content Team · MITRE · 2026-04-30 · CWE 4.20

updated Mapping_Notes

Modification: CWE Content Team · MITRE · 2026-10-28 · CWE 5.0

updated Dimensions, Observed_Examples, References, Relationships, Taxonomy_Mappings

17048 vulnerabilities reference this CWE, most recent first.

GHSA-V6M6-XMWW-QH8J

Vulnerability from github – Published: 2022-05-24 17:25 – Updated: 2024-01-04 03:30
VLAI
Details

A memory corruption vulnerability exists when Windows Media Foundation improperly handles objects in memory, aka 'Media Foundation Memory Corruption Vulnerability'. This CVE ID is unique from CVE-2020-1379, CVE-2020-1477, CVE-2020-1478, CVE-2020-1525, CVE-2020-1554.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-1492"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-119",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-08-17T19:15:00Z",
    "severity": "MODERATE"
  },
  "details": "A memory corruption vulnerability exists when Windows Media Foundation improperly handles objects in memory, aka \u0027Media Foundation Memory Corruption Vulnerability\u0027. This CVE ID is unique from CVE-2020-1379, CVE-2020-1477, CVE-2020-1478, CVE-2020-1525, CVE-2020-1554.",
  "id": "GHSA-v6m6-xmww-qh8j",
  "modified": "2024-01-04T03:30:33Z",
  "published": "2022-05-24T17:25:49Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-1492"
    },
    {
      "type": "WEB",
      "url": "https://portal.msrc.microsoft.com/en-US/security-guidance/advisory/CVE-2020-1492"
    }
  ],
  "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-V6PH-6G9P-25RC

Vulnerability from github – Published: 2026-01-29 15:30 – Updated: 2026-01-29 15:30
VLAI
Details

Gnome Fonts Viewer 3.34.0 contains a heap corruption vulnerability that allows attackers to trigger an out-of-bounds write by crafting a malicious TTF font file. Attackers can generate a specially crafted TTF file with an oversized pattern to cause an infinite malloc() loop and potentially crash the gnome-font-viewer process.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-37011"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-01-29T15:16:08Z",
    "severity": "HIGH"
  },
  "details": "Gnome Fonts Viewer 3.34.0 contains a heap corruption vulnerability that allows attackers to trigger an out-of-bounds write by crafting a malicious TTF font file. Attackers can generate a specially crafted TTF file with an oversized pattern to cause an infinite malloc() loop and potentially crash the gnome-font-viewer process.",
  "id": "GHSA-v6ph-6g9p-25rc",
  "modified": "2026-01-29T15:30:28Z",
  "published": "2026-01-29T15:30:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-37011"
    },
    {
      "type": "WEB",
      "url": "https://apps.gnome.org/FontViewer"
    },
    {
      "type": "WEB",
      "url": "https://help.gnome.org"
    },
    {
      "type": "WEB",
      "url": "https://www.exploit-db.com/exploits/48803"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/gnome-fonts-viewer-heap-corruption"
    }
  ],
  "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"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/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-V6Q2-P897-R99X

Vulnerability from github – Published: 2022-05-13 01:40 – Updated: 2022-05-13 01:40
VLAI
Details

An elevation of privilege vulnerability in the Qualcomm Wi-Fi driver could enable a local malicious application to execute arbitrary code within the context of the kernel. This issue is rated as High because it first requires compromising a privileged process. Product: Android. Versions: Kernel-3.10. Android ID: A-33979145. References: QC-CR#1105085.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2017-0453"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-03-08T01:59:00Z",
    "severity": "HIGH"
  },
  "details": "An elevation of privilege vulnerability in the Qualcomm Wi-Fi driver could enable a local malicious application to execute arbitrary code within the context of the kernel. This issue is rated as High because it first requires compromising a privileged process. Product: Android. Versions: Kernel-3.10. Android ID: A-33979145. References: QC-CR#1105085.",
  "id": "GHSA-v6q2-p897-r99x",
  "modified": "2022-05-13T01:40:06Z",
  "published": "2022-05-13T01:40:06Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-0453"
    },
    {
      "type": "WEB",
      "url": "https://source.android.com/security/bulletin/2017-03-01"
    },
    {
      "type": "WEB",
      "url": "https://source.android.com/security/bulletin/2017-03-01.html"
    },
    {
      "type": "WEB",
      "url": "https://source.codeaurora.org/quic/la/platform/vendor/qcom-opensource/wlan/qcacld-2.0/commit/?id=05af1f34723939f477cb7d25adb320d016d68513"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/96735"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id/1037968"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-V6QV-5WC9-PQ33

Vulnerability from github – Published: 2023-01-20 00:30 – Updated: 2023-01-26 15:30
VLAI
Details

Buffer overflow in function Notepad_plus::addHotSpot in Notepad++ v8.4.3 and earlier allows attackers to crash the application via two crafted files.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-31901"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-01-19T23:15:00Z",
    "severity": "MODERATE"
  },
  "details": "Buffer overflow in function Notepad_plus::addHotSpot in Notepad++ v8.4.3 and earlier allows attackers to crash the application via two crafted files.",
  "id": "GHSA-v6qv-5wc9-pq33",
  "modified": "2023-01-26T15:30:31Z",
  "published": "2023-01-20T00:30:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-31901"
    },
    {
      "type": "WEB",
      "url": "https://github.com/CDACesec/CVE-2022-31901"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-V6R6-84GR-92RM

Vulnerability from github – Published: 2021-05-21 14:26 – Updated: 2024-11-01 17:11
VLAI
Summary
Heap buffer overflow in `AvgPool3DGrad`
Details

Impact

The implementation of tf.raw_ops.AvgPool3DGrad is vulnerable to a heap buffer overflow:

import tensorflow as tf

orig_input_shape = tf.constant([10, 6, 3, 7, 7], shape=[5], dtype=tf.int32)
grad = tf.constant([0.01, 0, 0], shape=[3, 1, 1, 1, 1], dtype=tf.float32)
ksize = [1, 1, 1, 1, 1]
strides = [1, 1, 1, 1, 1]
padding = "SAME"

tf.raw_ops.AvgPool3DGrad(
  orig_input_shape=orig_input_shape, grad=grad, ksize=ksize, strides=strides,
  padding=padding)

The implementation assumes that the orig_input_shape and grad tensors have similar first and last dimensions but does not check that this assumption is validated.

Patches

We have patched the issue in GitHub commit 6fc9141f42f6a72180ecd24021c3e6b36165fe0d.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

For more information

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

Attribution

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

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29577"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-119",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T18:12:31Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nThe implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow:\n\n```python\nimport tensorflow as tf\n\norig_input_shape = tf.constant([10, 6, 3, 7, 7], shape=[5], dtype=tf.int32)\ngrad = tf.constant([0.01, 0, 0], shape=[3, 1, 1, 1, 1], dtype=tf.float32)\nksize = [1, 1, 1, 1, 1]\nstrides = [1, 1, 1, 1, 1]\npadding = \"SAME\"\n\ntf.raw_ops.AvgPool3DGrad(\n  orig_input_shape=orig_input_shape, grad=grad, ksize=ksize, strides=strides,\n  padding=padding)\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/d80ffba9702dc19d1fac74fc4b766b3fa1ee976b/tensorflow/core/kernels/pooling_ops_3d.cc#L376-L450) assumes that the `orig_input_shape` and `grad` tensors have similar first and last dimensions but does not check that this assumption is validated.\n\n### Patches\nWe have patched the issue in GitHub commit [6fc9141f42f6a72180ecd24021c3e6b36165fe0d](https://github.com/tensorflow/tensorflow/commit/6fc9141f42f6a72180ecd24021c3e6b36165fe0d).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.",
  "id": "GHSA-v6r6-84gr-92rm",
  "modified": "2024-11-01T17:11:43Z",
  "published": "2021-05-21T14:26:18Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6r6-84gr-92rm"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29577"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/6fc9141f42f6a72180ecd24021c3e6b36165fe0d"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-505.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-703.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-214.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 `AvgPool3DGrad`"
}

GHSA-V6RF-GWHG-99G6

Vulnerability from github – Published: 2024-11-22 21:32 – Updated: 2024-11-22 21:32
VLAI
Details

IrfanView DWG File Parsing Out-Of-Bounds Write Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of IrfanView. 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 DWG files. The issue results from the lack of proper validation of user-supplied data, which can result in a write 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-24754.

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{
  "affected": [],
  "aliases": [
    "CVE-2024-11554"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-11-22T21:15:14Z",
    "severity": "HIGH"
  },
  "details": "IrfanView DWG File Parsing Out-Of-Bounds Write Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of IrfanView. 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 DWG files. The issue results from the lack of proper validation of user-supplied data, which can result in a write 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-24754.",
  "id": "GHSA-v6rf-gwhg-99g6",
  "modified": "2024-11-22T21:32:18Z",
  "published": "2024-11-22T21:32:18Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-11554"
    },
    {
      "type": "WEB",
      "url": "https://www.zerodayinitiative.com/advisories/ZDI-24-1581"
    }
  ],
  "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-V6RV-MPPR-VW2J

Vulnerability from github – Published: 2022-05-24 16:49 – Updated: 2024-04-04 01:12
VLAI
Details

A vulnerability in the Session Initiation Protocol (SIP) protocol implementation of Cisco Unified Communications Manager could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition. The vulnerability is due to insufficient validation of input SIP traffic. An attacker could exploit this vulnerability by sending a malformed SIP packet to an affected Cisco Unified Communications Manager. A successful exploit could allow the attacker to trigger a new registration process on all connected phones, temporarily disrupting service.

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{
  "affected": [],
  "aliases": [
    "CVE-2019-1887"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-07-06T02:15:00Z",
    "severity": "HIGH"
  },
  "details": "A vulnerability in the Session Initiation Protocol (SIP) protocol implementation of Cisco Unified Communications Manager could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition. The vulnerability is due to insufficient validation of input SIP traffic. An attacker could exploit this vulnerability by sending a malformed SIP packet to an affected Cisco Unified Communications Manager. A successful exploit could allow the attacker to trigger a new registration process on all connected phones, temporarily disrupting service.",
  "id": "GHSA-v6rv-mppr-vw2j",
  "modified": "2024-04-04T01:12:25Z",
  "published": "2022-05-24T16:49:41Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-1887"
    },
    {
      "type": "WEB",
      "url": "https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-20190703-cucm-dos"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-V6RX-85H6-26MF

Vulnerability from github – Published: 2022-05-24 19:04 – Updated: 2022-05-24 19:04
VLAI
Details

Out of bounds write in Tab Strip in Google Chrome prior to 90.0.4430.212 allowed an attacker who convinced a user to install a malicious extension to perform an out of bounds memory write via a crafted HTML page and a crafted Chrome extension.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-30509"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-06-04T18:15:00Z",
    "severity": "HIGH"
  },
  "details": "Out of bounds write in Tab Strip in Google Chrome prior to 90.0.4430.212 allowed an attacker who convinced a user to install a malicious extension to perform an out of bounds memory write via a crafted HTML page and a crafted Chrome extension.",
  "id": "GHSA-v6rx-85h6-26mf",
  "modified": "2022-05-24T19:04:03Z",
  "published": "2022-05-24T19:04:03Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-30509"
    },
    {
      "type": "WEB",
      "url": "https://chromereleases.googleblog.com/2021/05/stable-channel-update-for-desktop.html"
    },
    {
      "type": "WEB",
      "url": "https://crbug.com/1196309"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ETMZL6IHCTCTREEL434BQ4THQ7EOHJ43"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PAT6EOXVQFE6JFMFQF4IKAOUQSHMHL54"
    },
    {
      "type": "WEB",
      "url": "https://security.gentoo.org/glsa/202107-06"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-V6RX-F8VJ-JQGJ

Vulnerability from github – Published: 2022-05-24 17:32 – Updated: 2022-05-24 17:32
VLAI
Details

A memory consumption issue was addressed with improved memory handling. This issue is fixed in macOS Catalina 10.15.1, Security Update 2019-001, and Security Update 2019-006, macOS Catalina 10.15. Processing a maliciously crafted string may lead to heap corruption.

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{
  "affected": [],
  "aliases": [
    "CVE-2019-8767"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-10-27T20:15:00Z",
    "severity": "CRITICAL"
  },
  "details": "A memory consumption issue was addressed with improved memory handling. This issue is fixed in macOS Catalina 10.15.1, Security Update 2019-001, and Security Update 2019-006, macOS Catalina 10.15. Processing a maliciously crafted string may lead to heap corruption.",
  "id": "GHSA-v6rx-f8vj-jqgj",
  "modified": "2022-05-24T17:32:22Z",
  "published": "2022-05-24T17:32:22Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-8767"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/en-us/HT210634"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/en-us/HT210722"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-V6VG-VX8Q-9JC8

Vulnerability from github – Published: 2022-05-24 16:46 – Updated: 2022-05-24 16:46
VLAI
Details

Adobe Acrobat and Reader versions 2019.010.20069 and earlier, 2019.010.20069 and earlier, 2017.011.30113 and earlier version, and 2015.006.30464 and earlier have an out-of-bounds write vulnerability. Successful exploitation could lead to arbitrary code execution .

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2019-7039"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-05-24T19:29:00Z",
    "severity": "CRITICAL"
  },
  "details": "Adobe Acrobat and Reader versions 2019.010.20069 and earlier, 2019.010.20069 and earlier, 2017.011.30113 and earlier version, and 2015.006.30464 and earlier have an out-of-bounds write vulnerability. Successful exploitation could lead to arbitrary code execution .",
  "id": "GHSA-v6vg-vx8q-9jc8",
  "modified": "2022-05-24T16:46:39Z",
  "published": "2022-05-24T16:46:39Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-7039"
    },
    {
      "type": "WEB",
      "url": "https://helpx.adobe.com/security/products/acrobat/apsb19-07.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

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.