Common Weakness Enumeration

CWE-617

Allowed

Reachable Assertion

Abstraction: Base · Status: Draft

The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.

989 vulnerabilities reference this CWE, most recent first.

GHSA-35Q6-7298-9C8J

Vulnerability from github – Published: 2025-01-22 15:32 – Updated: 2025-01-29 00:31
VLAI
Details

A reachable assertion in the ogs_kdf_hash_mme function of Open5GS <= 2.6.4 allows attackers to cause a Denial of Service (DoS) via a crafted NAS packet.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-24432"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-01-22T15:15:12Z",
    "severity": "MODERATE"
  },
  "details": "A reachable assertion in the ogs_kdf_hash_mme function of Open5GS \u003c= 2.6.4 allows attackers to cause a Denial of Service (DoS) via a crafted NAS packet.",
  "id": "GHSA-35q6-7298-9c8j",
  "modified": "2025-01-29T00:31:53Z",
  "published": "2025-01-22T15:32:35Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-24432"
    },
    {
      "type": "WEB",
      "url": "https://cellularsecurity.org/ransacked"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-364J-9M4F-F6R2

Vulnerability from github – Published: 2022-05-13 01:48 – Updated: 2022-05-13 01:48
VLAI
Details

In ImageMagick 7.0.5-7 Q16, an assertion failure was found in the function SetPixelChannelAttributes, which allows attackers to cause a denial of service via a crafted file.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2017-9499"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-06-07T14:29:00Z",
    "severity": "MODERATE"
  },
  "details": "In ImageMagick 7.0.5-7 Q16, an assertion failure was found in the function SetPixelChannelAttributes, which allows attackers to cause a denial of service via a crafted file.",
  "id": "GHSA-364j-9m4f-f6r2",
  "modified": "2022-05-13T01:48:00Z",
  "published": "2022-05-13T01:48:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-9499"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ImageMagick/ImageMagick/issues/492"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ImageMagick/ImageMagick/commit/7fd419441bc7103398e313558171d342c6315f44"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/98944"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-36M4-MV4F-9C4Q

Vulnerability from github – Published: 2025-01-22 00:33 – Updated: 2025-01-23 21:31
VLAI
Details

Magma versions <= 1.8.0 (fixed in v1.9 commit 08472ba98b8321f802e95f5622fa90fec2dea486) are susceptible to an assertion-based crash when an oversized NAS packet is received. An attacker may leverage this behavior to repeatedly crash the MME via either a compromised base station or via an unauthenticated cellphone within range of a base station managed by the MME, causing a denial of service.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-37029"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-01-21T23:15:10Z",
    "severity": "HIGH"
  },
  "details": "Magma versions \u003c= 1.8.0 (fixed in v1.9 commit 08472ba98b8321f802e95f5622fa90fec2dea486) are susceptible to an assertion-based crash when an oversized NAS packet is received. An attacker may leverage this behavior to repeatedly crash the MME via either a compromised base station or via an unauthenticated cellphone within range of a base station managed by the MME, causing a denial of service.",
  "id": "GHSA-36m4-mv4f-9c4q",
  "modified": "2025-01-23T21:31:51Z",
  "published": "2025-01-22T00:33:37Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-37029"
    },
    {
      "type": "WEB",
      "url": "https://cellularsecurity.org/ransacked"
    }
  ],
  "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-36VM-XW34-X4PJ

Vulnerability from github – Published: 2021-05-21 14:25 – Updated: 2024-11-01 16:55
VLAI
Summary
CHECK-fail in `tf.raw_ops.IRFFT`
Details

Impact

An attacker can cause a denial of service by exploiting a CHECK-failure coming from the implementation of tf.raw_ops.IRFFT:

import tensorflow as tf

values = [-10.0] * 130
values[0] = -9.999999999999995
inputs = tf.constant(values, shape=[10, 13], dtype=tf.float32)
inputs = tf.cast(inputs, dtype=tf.complex64)
fft_length = tf.constant([0], shape=[1], dtype=tf.int32)

tf.raw_ops.IRFFT(input=inputs, fft_length=fft_length)

The above example causes Eigen code to operate on an empty matrix. This triggers on an assertion and causes program termination.

Patches

We have patched the issue in GitHub commit 1c56f53be0b722ca657cbc7df461ed676c8642a2.

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 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": [
        {
          "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-2021-29562"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T19:48:31Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nAn attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.IRFFT`:\n    \n```python\nimport tensorflow as tf\n\nvalues = [-10.0] * 130\nvalues[0] = -9.999999999999995\ninputs = tf.constant(values, shape=[10, 13], dtype=tf.float32)\ninputs = tf.cast(inputs, dtype=tf.complex64)\nfft_length = tf.constant([0], shape=[1], dtype=tf.int32)\n\ntf.raw_ops.IRFFT(input=inputs, fft_length=fft_length)\n``` \n    \nThe above example causes Eigen code to operate on an empty matrix. This triggers on an assertion and causes program termination.\n\n### Patches\nWe have patched the issue in GitHub commit [1c56f53be0b722ca657cbc7df461ed676c8642a2](https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2).\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 Yakun Zhang and Ying Wang of Baidu X-Team. ",
  "id": "GHSA-36vm-xw34-x4pj",
  "modified": "2024-11-01T16:55:35Z",
  "published": "2021-05-21T14:25:02Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-36vm-xw34-x4pj"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29562"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-490.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-688.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-199.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": "CHECK-fail in `tf.raw_ops.IRFFT`"
}

GHSA-3775-FRGH-J3VC

Vulnerability from github – Published: 2022-05-24 16:55 – Updated: 2022-06-22 00:00
VLAI
Details

An issue was discovered in Varnish Cache before 6.0.4 LTS, and 6.1.x and 6.2.x before 6.2.1. An HTTP/1 parsing failure allows a remote attacker to trigger an assert by sending crafted HTTP/1 requests. The assert will cause an automatic restart with a clean cache, which makes it a Denial of Service attack.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2019-15892"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-09-03T21:15:00Z",
    "severity": "HIGH"
  },
  "details": "An issue was discovered in Varnish Cache before 6.0.4 LTS, and 6.1.x and 6.2.x before 6.2.1. An HTTP/1 parsing failure allows a remote attacker to trigger an assert by sending crafted HTTP/1 requests. The assert will cause an automatic restart with a clean cache, which makes it a Denial of Service attack.",
  "id": "GHSA-3775-frgh-j3vc",
  "modified": "2022-06-22T00:00:54Z",
  "published": "2022-05-24T16:55:23Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-15892"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3OEOCYRU43TWEU2C65F3D6GK64MSWNNK"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DBAQF6UDRSTURGINIMSMLJR4PTDYWA7C"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/KLSF54TDJWJLINIFEW5V5BKDNY5EQRR3"
    },
    {
      "type": "WEB",
      "url": "https://seclists.org/bugtraq/2019/Sep/5"
    },
    {
      "type": "WEB",
      "url": "https://varnish-cache.org/security/VSV00003.html"
    },
    {
      "type": "WEB",
      "url": "https://www.debian.org/security/2019/dsa-4514"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00069.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00089.html"
    }
  ],
  "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-3778-6QX9-FC4V

Vulnerability from github – Published: 2022-12-13 18:30 – Updated: 2022-12-15 18:30
VLAI
Details

Denial of service in MODEM due to reachable assertion while processing configuration from network in Snapdragon Mobile

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-25673"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-12-13T16:15:00Z",
    "severity": "HIGH"
  },
  "details": "Denial of service in MODEM due to reachable assertion while processing configuration from network in Snapdragon Mobile",
  "id": "GHSA-3778-6qx9-fc4v",
  "modified": "2022-12-15T18:30:23Z",
  "published": "2022-12-13T18:30:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-25673"
    },
    {
      "type": "WEB",
      "url": "https://www.qualcomm.com/company/product-security/bulletins/december-2022-bulletin"
    }
  ],
  "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-3784-9734-2V5F

Vulnerability from github – Published: 2025-06-03 15:31 – Updated: 2025-06-03 15:31
VLAI
Details

A vulnerability classified as problematic was found in Open5GS up to 2.7.3. Affected by this vulnerability is the function ngap_handle_path_switch_request_transfer of the file src/smf/ngap-handler.c of the component NGAP PathSwitchRequest Message Handler. The manipulation leads to reachable assertion. The attack can be launched remotely. The exploit has been disclosed to the public and may be used. The patch is named 2daa44adab762c47a8cef69cc984946973a845b3. It is recommended to apply a patch to fix this issue.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-5501"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-06-03T14:15:51Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability classified as problematic was found in Open5GS up to 2.7.3. Affected by this vulnerability is the function ngap_handle_path_switch_request_transfer of the file src/smf/ngap-handler.c of the component NGAP PathSwitchRequest Message Handler. The manipulation leads to reachable assertion. The attack can be launched remotely. The exploit has been disclosed to the public and may be used. The patch is named 2daa44adab762c47a8cef69cc984946973a845b3. It is recommended to apply a patch to fix this issue.",
  "id": "GHSA-3784-9734-2v5f",
  "modified": "2025-06-03T15:31:26Z",
  "published": "2025-06-03T15:31:26Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-5501"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open5gs/open5gs/issues/3909"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open5gs/open5gs/issues/3909#issuecomment-2926682623"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open5gs/open5gs/commit/2daa44adab762c47a8cef69cc984946973a845b3"
    },
    {
      "type": "WEB",
      "url": "https://github.com/user-attachments/files/20362183/AMF.crash.due.to.pathswitchrequest.zip"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?ctiid.310915"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?id.310915"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?submit.582265"
    }
  ],
  "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:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/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-37JF-MJV6-XFQW

Vulnerability from github – Published: 2022-09-16 19:24 – Updated: 2022-09-19 19:09
VLAI
Summary
TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
Details

Impact

When Conv2DBackpropInput receives empty out_backprop inputs (e.g. [3, 1, 0, 1]), the current CPU/GPU kernels CHECK fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack.

import tensorflow as tf
import numpy as np
input_sizes = [3, 1, 1, 2]
filter = np.ones([1, 3, 2, 3])
out_backprop = np.ones([3, 1, 0, 3])
strides = [1, 1, 2, 1]
padding = 'VALID'

tf.raw_ops.Conv2DBackpropInput(
   input_sizes = input_sizes,
   filter = filter,
   out_backprop = out_backprop,
   strides = strides,
   padding = padding
)

Patches

We have patched the issue in GitHub commit 27a65a43cf763897fecfa5cdb5cc653fc5dd0346.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Jingyi Shi.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-35999"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T19:24:49Z",
    "nvd_published_at": "2022-09-16T23:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nWhen `Conv2DBackpropInput` receives empty `out_backprop` inputs (e.g. `[3, 1, 0, 1]`), the current CPU/GPU kernels `CHECK` fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\nimport numpy as np\ninput_sizes = [3, 1, 1, 2]\nfilter = np.ones([1, 3, 2, 3])\nout_backprop = np.ones([3, 1, 0, 3])\nstrides = [1, 1, 2, 1]\npadding = \u0027VALID\u0027\n\ntf.raw_ops.Conv2DBackpropInput(\n   input_sizes = input_sizes,\n   filter = filter,\n   out_backprop = out_backprop,\n   strides = strides,\n   padding = padding\n)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [27a65a43cf763897fecfa5cdb5cc653fc5dd0346](https://github.com/tensorflow/tensorflow/commit/27a65a43cf763897fecfa5cdb5cc653fc5dd0346).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\n\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\n### Attribution\nThis vulnerability has been reported by Jingyi Shi.\n",
  "id": "GHSA-37jf-mjv6-xfqw",
  "modified": "2022-09-19T19:09:33Z",
  "published": "2022-09-16T19:24:49Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-37jf-mjv6-xfqw"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35999"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/27a65a43cf763897fecfa5cdb5cc653fc5dd0346"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`"
}

GHSA-39WR-F4FF-XM6P

Vulnerability from github – Published: 2021-08-25 20:46 – Updated: 2023-06-13 21:56
VLAI
Summary
Incorrect implementation in streebog
Details

Internal update-sigma function was implemented incorrectly and depending on debug-assertions it could've caused an incorrect result or panic for certain inputs.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "crates.io",
        "name": "streebog"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.8.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2019-25007"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-08-19T21:19:50Z",
    "nvd_published_at": "2020-12-31T10:15:14Z",
    "severity": "HIGH"
  },
  "details": "Internal update-sigma function was implemented incorrectly and depending on debug-assertions it could\u0027ve caused an incorrect result or panic for certain inputs.",
  "id": "GHSA-39wr-f4ff-xm6p",
  "modified": "2023-06-13T21:56:16Z",
  "published": "2021-08-25T20:46:41Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-25007"
    },
    {
      "type": "WEB",
      "url": "https://github.com/RustCrypto/hashes/pull/91"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/RustCrypto/hashes/tree/master/streebog"
    },
    {
      "type": "WEB",
      "url": "https://rustsec.org/advisories/RUSTSEC-2019-0030.html"
    }
  ],
  "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"
    }
  ],
  "summary": "Incorrect implementation in streebog"
}

GHSA-3H5Q-GG6W-2G7P

Vulnerability from github – Published: 2022-05-24 19:02 – Updated: 2022-05-24 19:02
VLAI
Details

Mikrotik RouterOs 6.44.6 (long-term tree) suffers from an assertion failure vulnerability in the btest process. An authenticated remote attacker can cause a Denial of Service due to an assertion failure via a crafted packet.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-20214"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-05-18T19:15:00Z",
    "severity": "MODERATE"
  },
  "details": "Mikrotik RouterOs 6.44.6 (long-term tree) suffers from an assertion failure vulnerability in the btest process. An authenticated remote attacker can cause a Denial of Service due to an assertion failure via a crafted packet.",
  "id": "GHSA-3h5q-gg6w-2g7p",
  "modified": "2022-05-24T19:02:42Z",
  "published": "2022-05-24T19:02:42Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-20214"
    },
    {
      "type": "WEB",
      "url": "https://mikrotik.com"
    },
    {
      "type": "WEB",
      "url": "http://packetstormsecurity.com/files/162513/Mikrotik-RouterOS-6.46.5-Memory-Corruption-Assertion-Failure.html"
    },
    {
      "type": "WEB",
      "url": "http://seclists.org/fulldisclosure/2021/May/15"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

Mitigation
Implementation

Make sensitive open/close operation non reachable by directly user-controlled data (e.g. open/close resources)

Mitigation
Implementation

Strategy: Input Validation

Perform input validation on user data.

No CAPEC attack patterns related to this CWE.