Common Weakness Enumeration

CWE-125

Allowed

Out-of-bounds Read

Abstraction: Base · Status: Draft

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

11352 vulnerabilities reference this CWE, most recent first.

GHSA-VJ4W-GFGG-XVGV

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

A CWE-125: Out-of-bounds read vulnerability exists inIGSS Definition (Def.exe) V15.0.0.21140 and prior that could result in disclosure of information or remote code execution due to lack of user-supplied data validation, when a malicious CGF file is imported to IGSS Definition.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-22756"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-06-11T16:15:00Z",
    "severity": "HIGH"
  },
  "details": "A CWE-125: Out-of-bounds read vulnerability exists inIGSS Definition (Def.exe) V15.0.0.21140 and prior that could result in disclosure of information or remote code execution due to lack of user-supplied data validation, when a malicious CGF file is imported to IGSS Definition.",
  "id": "GHSA-vj4w-gfgg-xvgv",
  "modified": "2022-05-24T19:05:04Z",
  "published": "2022-05-24T19:05:04Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-22756"
    },
    {
      "type": "WEB",
      "url": "http://download.schneider-electric.com/files?p_Doc_Ref=SEVD-2021-159-01"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-VJ54-GX3V-3434

Vulnerability from github – Published: 2024-04-11 12:30 – Updated: 2024-04-11 12:30
VLAI
Details

Animate versions 23.0.4, 24.0.1 and earlier are affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. An attacker could leverage this vulnerability to bypass mitigations such as ASLR. Exploitation of this issue requires user interaction in that a victim must open a malicious file.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-20796"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-04-11T11:15:47Z",
    "severity": "MODERATE"
  },
  "details": "Animate versions 23.0.4, 24.0.1 and earlier are affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. An attacker could leverage this vulnerability to bypass mitigations such as ASLR. Exploitation of this issue requires user interaction in that a victim must open a malicious file.",
  "id": "GHSA-vj54-gx3v-3434",
  "modified": "2024-04-11T12:30:28Z",
  "published": "2024-04-11T12:30:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-20796"
    },
    {
      "type": "WEB",
      "url": "https://helpx.adobe.com/security/products/animate/apsb24-26.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-VJ59-CX37-65JX

Vulnerability from github – Published: 2022-05-24 17:45 – Updated: 2022-05-24 17:45
VLAI
Details

This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit PhantomPDF 10.1.0.37527. 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 JPEG2000 images. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated structure. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-12230.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-27270"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-03-30T15:15:00Z",
    "severity": "HIGH"
  },
  "details": "This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit PhantomPDF 10.1.0.37527. 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 JPEG2000 images. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated structure. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-12230.",
  "id": "GHSA-vj59-cx37-65jx",
  "modified": "2022-05-24T17:45:52Z",
  "published": "2022-05-24T17:45:52Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-27270"
    },
    {
      "type": "WEB",
      "url": "https://www.foxitsoftware.com/support/security-bulletins.php"
    },
    {
      "type": "WEB",
      "url": "https://www.zerodayinitiative.com/advisories/ZDI-21-352"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-VJ5C-95P9-JF9J

Vulnerability from github – Published: 2022-05-17 03:02 – Updated: 2025-04-20 03:31
VLAI
Details

The ConvertToPDF plugin in Foxit Reader before 8.2 and PhantomPDF before 8.2 on Windows, when the gflags app is enabled, allows remote attackers to cause a denial of service (out-of-bounds read and application crash) via a crafted JPEG image. The vulnerability could lead to information disclosure; an attacker can leverage this in conjunction with other vulnerabilities to execute code in the context of the current process.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2017-5556"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-01-23T07:59:00Z",
    "severity": "HIGH"
  },
  "details": "The ConvertToPDF plugin in Foxit Reader before 8.2 and PhantomPDF before 8.2 on Windows, when the gflags app is enabled, allows remote attackers to cause a denial of service (out-of-bounds read and application crash) via a crafted JPEG image. The vulnerability could lead to information disclosure; an attacker can leverage this in conjunction with other vulnerabilities to execute code in the context of the current process.",
  "id": "GHSA-vj5c-95p9-jf9j",
  "modified": "2025-04-20T03:31:24Z",
  "published": "2022-05-17T03:02:43Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-5556"
    },
    {
      "type": "WEB",
      "url": "https://www.foxitsoftware.com/support/security-bulletins.php"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/95353"
    },
    {
      "type": "WEB",
      "url": "http://www.zerodayinitiative.com/advisories/ZDI-17-039"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-VJ6G-QRFV-Q27W

Vulnerability from github – Published: 2022-05-24 19:07 – Updated: 2022-10-08 00:00
VLAI
Details

A vulnerability has been identified in JT2Go (All versions < V13.2), Teamcenter Visualization (All versions < V13.2). The Tiff_loader.dll library in affected applications lacks proper validation of user-supplied data when parsing TIFF files. This could result in an out of bounds read past the end of an allocated buffer. An attacker could leverage this vulnerability to leak information in the context of the current process. (ZDI-CAN-13192)

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-34299"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125",
      "CWE-126",
      "CWE-20"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-07-13T11:15:00Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability has been identified in JT2Go (All versions \u003c V13.2), Teamcenter Visualization (All versions \u003c V13.2). The Tiff_loader.dll library in affected applications lacks proper validation of user-supplied data when parsing TIFF files. This could result in an out of bounds read past the end of an allocated buffer. An attacker could leverage this vulnerability to leak information in the context of the current process. (ZDI-CAN-13192)",
  "id": "GHSA-vj6g-qrfv-q27w",
  "modified": "2022-10-08T00:00:17Z",
  "published": "2022-05-24T19:07:42Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-34299"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/pdf/ssa-483182.pdf"
    },
    {
      "type": "WEB",
      "url": "https://www.zerodayinitiative.com/advisories/ZDI-21-845"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-VJ6M-GG8Q-FVH6

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

In ih264d_decode_slice_thread of ih264d_thread_parse_decode.c, there is a possible out of bounds read due to improper input validation. This could lead to remote information disclosure with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-10Android ID: A-144687080

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-0192"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-06-11T15:15:00Z",
    "severity": "MODERATE"
  },
  "details": "In ih264d_decode_slice_thread of ih264d_thread_parse_decode.c, there is a possible out of bounds read due to improper input validation. This could lead to remote information disclosure with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-10Android ID: A-144687080",
  "id": "GHSA-vj6m-gg8q-fvh6",
  "modified": "2022-05-24T17:20:16Z",
  "published": "2022-05-24T17:20:16Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-0192"
    },
    {
      "type": "WEB",
      "url": "https://source.android.com/security/bulletin/pixel/2020-06-01"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-VJ76-XPGC-CHXJ

Vulnerability from github – Published: 2024-11-19 21:31 – Updated: 2024-12-18 15:32
VLAI
Details

In smp_data_received of smp_l2c.cc, there is a possible out of bounds read followed by code execution due to a missing bounds check. This could lead to remote code execution with no additional execution privileges needed. User interaction is needed for exploitation.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2018-9365"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-11-19T21:15:05Z",
    "severity": "HIGH"
  },
  "details": "In smp_data_received of smp_l2c.cc, there is a possible out of bounds read followed by code execution due to a missing bounds check. This could lead to remote code execution with no additional execution privileges needed. User interaction is needed for exploitation.",
  "id": "GHSA-vj76-xpgc-chxj",
  "modified": "2024-12-18T15:32:59Z",
  "published": "2024-11-19T21:31:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-9365"
    },
    {
      "type": "WEB",
      "url": "https://source.android.com/security/bulletin/2018-07-01"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-VJ94-JW3J-CJ94

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

Kofax Power PDF U3D File Parsing Out-Of-Bounds Read Information Disclosure Vulnerability. This vulnerability allows remote attackers to disclose sensitive information on affected installations of Kofax Power PDF. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.

The specific flaw exists within the parsing of U3D files. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-20469.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-37358"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-05-03T02:15:48Z",
    "severity": "LOW"
  },
  "details": "Kofax Power PDF U3D File Parsing Out-Of-Bounds Read Information Disclosure Vulnerability. This vulnerability allows remote attackers to disclose sensitive information on affected installations of Kofax Power PDF. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the parsing of U3D files. The issue results from the lack of proper validation of user-supplied data, which can result in a read past the end of an allocated object. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-20469.",
  "id": "GHSA-vj94-jw3j-cj94",
  "modified": "2024-05-03T03:30:54Z",
  "published": "2024-05-03T03:30:54Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-37358"
    },
    {
      "type": "WEB",
      "url": "https://www.zerodayinitiative.com/advisories/ZDI-23-953"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-VJF4-HW94-9Q25

Vulnerability from github – Published: 2024-02-02 09:30 – Updated: 2024-02-02 09:30
VLAI
Details

in OpenHarmony v3.2.4 and prior versions allow a local attacker causes information leak through out-of-bounds Read.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-43756"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-02-02T07:15:08Z",
    "severity": "LOW"
  },
  "details": "\nin OpenHarmony v3.2.4 and prior versions allow a local attacker causes information leak through out-of-bounds Read.\n\n",
  "id": "GHSA-vjf4-hw94-9q25",
  "modified": "2024-02-02T09:30:20Z",
  "published": "2024-02-02T09:30:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-43756"
    },
    {
      "type": "WEB",
      "url": "https://gitee.com/openharmony/security/blob/master/zh/security-disclosure/2024/2024-02.md"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-VJG4-V33C-GGC4

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

Impact

The implementation of FractionalAvgPoolGrad does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap:

import tensorflow as tf

@tf.function
def test():
  y = tf.raw_ops.FractionalAvgPoolGrad(
    orig_input_tensor_shape=[2,2,2,2],
    out_backprop=[[[[1,2], [3, 4], [5, 6]], [[7, 8], [9,10], [11,12]]]],
    row_pooling_sequence=[-10,1,2,3],
    col_pooling_sequence=[1,2,3,4],
    overlapping=True)
  return y

test()

Patches

We have patched the issue in GitHub commit 002408c3696b173863228223d535f9de72a101a9.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

For more information

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

Attribution

This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-21730"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-03T18:36:19Z",
    "nvd_published_at": "2022-02-03T11:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact \nThe [implementation of `FractionalAvgPoolGrad`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_avg_pool_op.cc#L209-L360) does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap:\n\n```python\nimport tensorflow as tf\n\n@tf.function\ndef test():\n  y = tf.raw_ops.FractionalAvgPoolGrad(\n    orig_input_tensor_shape=[2,2,2,2],\n    out_backprop=[[[[1,2], [3, 4], [5, 6]], [[7, 8], [9,10], [11,12]]]],\n    row_pooling_sequence=[-10,1,2,3],\n    col_pooling_sequence=[1,2,3,4],\n    overlapping=True)\n  return y\n    \ntest()\n```\n\n### Patches\nWe have patched the issue in GitHub commit [002408c3696b173863228223d535f9de72a101a9](https://github.com/tensorflow/tensorflow/commit/002408c3696b173863228223d535f9de72a101a9).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n  \n### Attribution\nThis vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.",
  "id": "GHSA-vjg4-v33c-ggc4",
  "modified": "2024-11-13T22:11:42Z",
  "published": "2022-02-09T18:29:45Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vjg4-v33c-ggc4"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-21730"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/002408c3696b173863228223d535f9de72a101a9"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-54.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-109.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_avg_pool_op.cc#L209-L360"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Out of bounds read in Tensorflow"
}

Mitigation MIT-5
Implementation

Strategy: Input Validation

  • Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
  • When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue."
  • Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
  • To reduce the likelihood of introducing an out-of-bounds read, ensure that you validate and ensure correct calculations for any length argument, buffer size calculation, or offset. Be especially careful of relying on a sentinel (i.e. special character such as NUL) in untrusted inputs.
Mitigation
Architecture and Design

Strategy: Language Selection

Use a language that provides appropriate memory abstractions.

CAPEC-540: Overread Buffers

An adversary attacks a target by providing input that causes an application to read beyond the boundary of a defined buffer. This typically occurs when a value influencing where to start or stop reading is set to reflect positions outside of the valid memory location of the buffer. This type of attack may result in exposure of sensitive information, a system crash, or arbitrary code execution.