Common Weakness Enumeration

CWE-617

Allowed

Reachable Assertion

Abstraction: Base · Status: Draft

API response cwe.mitre.org

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.

1150 vulnerabilities reference this CWE, most recent first.

GHSA-H4HQ-CXXW-86JX

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 SIB1 with invalid Bandwidth in Snapdragon Mobile

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2022-25672"
  ],
  "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 SIB1 with invalid Bandwidth in Snapdragon Mobile",
  "id": "GHSA-h4hq-cxxw-86jx",
  "modified": "2022-12-15T18:30:24Z",
  "published": "2022-12-13T18:30:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-25672"
    },
    {
      "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-H5VQ-GW2C-PQ47

Vulnerability from github – Published: 2022-09-16 22:12 – Updated: 2022-09-19 19:42
VLAI
Summary
TensorFlow vulnerable to `CHECK` failures in `UnbatchGradOp`
Details

Impact

The UnbatchGradOp function takes an argument id that is assumed to be a scalar. A nonscalar id can trigger a CHECK failure and crash the program.

import numpy as np
import tensorflow as tf

# `id` is not scalar
tf.raw_ops.UnbatchGrad(original_input= tf.constant([1]),batch_index=tf.constant([[0,0,0 ], ], dtype=tf.int64),grad=tf.constant([1,]),id=tf.constant([1,1,], dtype=tf.int64))

It also requires its argument batch_index to contain three times the number of elements as indicated in its batch_index.dim_size(0). An incorrect batch_index can trigger a CHECK failure and crash the program.

import numpy as np
import tensorflow as tf

# batch_index's size is not 3
tf.raw_ops.UnbatchGrad(original_input= tf.constant([1]),batch_index=tf.constant([[0,0], ], dtype=tf.int64),grad=tf.constant([1,]),id=tf.constant([1,], dtype=tf.int64))

Patches

We have patched the issue in GitHub commit 5f945fc6409a3c1e90d6970c9292f805f6e6ddf2.

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 Kang Hong Jin from Singapore Management University and 刘力源 from the Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology

Severity
5.9 (Medium)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "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-2022-35952"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T22:12:59Z",
    "nvd_published_at": "2022-09-16T20:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nThe [`UnbatchGradOp`](https://github.com/tensorflow/tensorflow/blob/769eddaf479c8debead9a59a72617d6ed6f0fe10/tensorflow/core/kernels/batch_kernels.cc#L891) function takes an argument `id` that is assumed to be a scalar. A nonscalar `id` can trigger a `CHECK` failure and crash the program.\n```python\nimport numpy as np\nimport tensorflow as tf\n\n# `id` is not scalar\ntf.raw_ops.UnbatchGrad(original_input= tf.constant([1]),batch_index=tf.constant([[0,0,0 ], ], dtype=tf.int64),grad=tf.constant([1,]),id=tf.constant([1,1,], dtype=tf.int64))\n```\nIt also requires its argument `batch_index` to contain three times the number of elements as indicated in its `batch_index.dim_size(0)`. An incorrect `batch_index` can trigger a `CHECK` failure and crash the program.\n```python\nimport numpy as np\nimport tensorflow as tf\n\n# batch_index\u0027s size is not 3\ntf.raw_ops.UnbatchGrad(original_input= tf.constant([1]),batch_index=tf.constant([[0,0], ], dtype=tf.int64),grad=tf.constant([1,]),id=tf.constant([1,], dtype=tf.int64))\n```\n\n### Patches\nWe have patched the issue in GitHub commit [5f945fc6409a3c1e90d6970c9292f805f6e6ddf2](https://github.com/tensorflow/tensorflow/commit/5f945fc6409a3c1e90d6970c9292f805f6e6ddf2).\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 Kang Hong Jin from Singapore Management University and \u5218\u529b\u6e90 from the Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology\n",
  "id": "GHSA-h5vq-gw2c-pq47",
  "modified": "2022-09-19T19:42:48Z",
  "published": "2022-09-16T22:12:59Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h5vq-gw2c-pq47"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35952"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/5f945fc6409a3c1e90d6970c9292f805f6e6ddf2"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/769eddaf479c8debead9a59a72617d6ed6f0fe10/tensorflow/core/kernels/batch_kernels.cc#L891"
    },
    {
      "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` failures in `UnbatchGradOp`"
}

GHSA-H663-9FGH-W7XF

Vulnerability from github – Published: 2026-07-21 21:32 – Updated: 2026-07-21 21:32
VLAI
Details

Reachable Assertion (CWE-617) in Elasticsearch can lead to denial of service via Input Data Manipulation (CAPEC-153). A specially crafted search request containing a null value in a specific query clause causes an internal assertion to be raised during query parsing. Because Elasticsearch treats assertion failures as fatal errors, this terminates the affected node process. A low-privileged authenticated user with read access to at least one index can exploit this condition with a single request to cause a node to terminate, disrupting search availability. In a single-node deployment this fully stops Elasticsearch; in a multi-node cluster it reduces cluster capacity for each affected node.

Severity
6.5 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2026-63140"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-07-21T21:16:53Z",
    "severity": "MODERATE"
  },
  "details": "Reachable Assertion (CWE-617) in Elasticsearch can lead to denial of service via Input Data Manipulation (CAPEC-153). A specially crafted search request containing a null value in a specific query clause causes an internal assertion to be raised during query parsing. Because Elasticsearch treats assertion failures as fatal errors, this terminates the affected node process. A low-privileged authenticated user with read access to at least one index can exploit this condition with a single request to cause a node to terminate, disrupting search availability. In a single-node deployment this fully stops Elasticsearch; in a multi-node cluster it reduces cluster capacity for each affected node.",
  "id": "GHSA-h663-9fgh-w7xf",
  "modified": "2026-07-21T21:32:42Z",
  "published": "2026-07-21T21:32:42Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-63140"
    },
    {
      "type": "WEB",
      "url": "https://discuss.elastic.co/t/elasticsearch-8-19-19-9-3-8-9-4-4-security-update-esa-2026-64/388565"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-H6FQ-F4XM-H8JQ

Vulnerability from github – Published: 2022-05-13 01:50 – Updated: 2022-05-13 01:50
VLAI
Details

The BPMDetect class in BPMDetect.cpp in libSoundTouch.a in Olli Parviainen SoundTouch 2.0 allows remote attackers to cause a denial of service (assertion failure and application exit), as demonstrated by SoundStretch.

Severity
6.5 (Medium)
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2018-17096"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-09-16T21:29:00Z",
    "severity": "MODERATE"
  },
  "details": "The BPMDetect class in BPMDetect.cpp in libSoundTouch.a in Olli Parviainen SoundTouch 2.0 allows remote attackers to cause a denial of service (assertion failure and application exit), as demonstrated by SoundStretch.",
  "id": "GHSA-h6fq-f4xm-h8jq",
  "modified": "2022-05-13T01:50:31Z",
  "published": "2022-05-13T01:50:31Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-17096"
    },
    {
      "type": "WEB",
      "url": "https://github.com/TeamSeri0us/pocs/tree/master/soundtouch/2018_09_03"
    },
    {
      "type": "WEB",
      "url": "https://gitlab.com/soundtouch/soundtouch/issues/14"
    }
  ],
  "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-H6P9-W9R4-7X73

Vulnerability from github – Published: 2022-05-24 19:09 – Updated: 2022-05-24 19:09
VLAI
Details

An issue was discovered in PJSIP in Asterisk before 16.19.1 and before 18.5.1. To exploit, a re-INVITE without SDP must be received after Asterisk has sent a BYE request.

Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2021-31878"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-07-30T14:15:00Z",
    "severity": "MODERATE"
  },
  "details": "An issue was discovered in PJSIP in Asterisk before 16.19.1 and before 18.5.1. To exploit, a re-INVITE without SDP must be received after Asterisk has sent a BYE request.",
  "id": "GHSA-h6p9-w9r4-7x73",
  "modified": "2022-05-24T19:09:23Z",
  "published": "2022-05-24T19:09:23Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-31878"
    },
    {
      "type": "WEB",
      "url": "https://downloads.digium.com/pub/security/AST-2021-007.html"
    },
    {
      "type": "WEB",
      "url": "https://issues.asterisk.org/jira/browse/ASTERISK-29381"
    },
    {
      "type": "WEB",
      "url": "http://downloads.asterisk.org/pub/security/AST-2021-007.html"
    },
    {
      "type": "WEB",
      "url": "http://packetstormsecurity.com/files/163638/Asterisk-Project-Security-Advisory-AST-2021-007.html"
    },
    {
      "type": "WEB",
      "url": "http://seclists.org/fulldisclosure/2021/Jul/48"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-H738-V27M-F6MW

Vulnerability from github – Published: 2023-12-13 15:30 – Updated: 2025-11-04 21:30
VLAI
Details

StringEqual in TiXmlDeclaration::Parse in tinyxmlparser.cpp in TinyXML through 2.6.2 has a reachable assertion (and application exit) via a crafted XML document with a '\0' located after whitespace.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2023-34194"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-12-13T14:15:43Z",
    "severity": "HIGH"
  },
  "details": "StringEqual in TiXmlDeclaration::Parse in tinyxmlparser.cpp in TinyXML through 2.6.2 has a reachable assertion (and application exit) via a crafted XML document with a \u0027\\0\u0027 located after whitespace.",
  "id": "GHSA-h738-v27m-f6mw",
  "modified": "2025-11-04T21:30:52Z",
  "published": "2023-12-13T15:30:57Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-34194"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2023/12/msg00024.html"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/4QCR5PIOBGDIDS6SYRESTMDJSEDFSCOE"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/HOMBSHRIW5Q34SQSXYURYAOYDZD2NQF6"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/4QCR5PIOBGDIDS6SYRESTMDJSEDFSCOE"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HOMBSHRIW5Q34SQSXYURYAOYDZD2NQF6"
    },
    {
      "type": "WEB",
      "url": "https://sourceforge.net/p/tinyxml/git/ci/master/tree/tinyxmlparser.cpp"
    },
    {
      "type": "WEB",
      "url": "https://www.forescout.com/resources/sierra21-vulnerabilities"
    }
  ],
  "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-H73X-845J-84Q5

Vulnerability from github – Published: 2025-08-06 09:30 – Updated: 2025-08-06 09:30
VLAI
Details

Transient DOS while creating NDP instance.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2025-27073"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-08-06T08:15:30Z",
    "severity": "HIGH"
  },
  "details": "Transient DOS while creating NDP instance.",
  "id": "GHSA-h73x-845j-84q5",
  "modified": "2025-08-06T09:30:36Z",
  "published": "2025-08-06T09:30:36Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-27073"
    },
    {
      "type": "WEB",
      "url": "https://docs.qualcomm.com/product/publicresources/securitybulletin/august-2025-bulletin.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"
    }
  ]
}

GHSA-H747-3Q39-R5RP

Vulnerability from github – Published: 2026-09-14 03:30 – Updated: 2026-09-14 03:30
VLAI
Details

A vulnerability was determined in GPAC up to f1219cde. This impacts the function xmt_parse_element of the file scene_manager/loader_xmt.c of the component MP4Box. Executing a manipulation can lead to reachable assertion. The attack is restricted to local execution. The exploit has been publicly disclosed and may be utilized. Upgrading to version abi-16.23 will fix this issue. This patch is called afca1f1181668d85941d51ed1adf647807d5d975. It is recommended to upgrade the affected component.

Severity
3.3 (Low)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
1.9 (Low)
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:P
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2026-90611"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-14T02:17:15Z",
    "severity": "LOW"
  },
  "details": "A vulnerability was determined in GPAC up to f1219cde. This impacts the function xmt_parse_element of the file scene_manager/loader_xmt.c of the component MP4Box. Executing a manipulation can lead to reachable assertion. The attack is restricted to local execution. The exploit has been publicly disclosed and may be utilized. Upgrading to version abi-16.23 will fix this issue. This patch is called afca1f1181668d85941d51ed1adf647807d5d975. It is recommended to upgrade the affected component.",
  "id": "GHSA-h747-3q39-r5rp",
  "modified": "2026-09-14T03:30:22Z",
  "published": "2026-09-14T03:30:22Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-90611"
    },
    {
      "type": "WEB",
      "url": "https://github.com/gpac/gpac/issues/3820"
    },
    {
      "type": "WEB",
      "url": "https://github.com/gpac/gpac/commit/afca1f1181668d85941d51ed1adf647807d5d975"
    },
    {
      "type": "WEB",
      "url": "https://github.com/gpac/gpac"
    },
    {
      "type": "WEB",
      "url": "https://github.com/gpac/gpac/releases/tag/abi-16.23"
    },
    {
      "type": "WEB",
      "url": "https://github.com/r1ck9-2q/cve_summit/blob/main/Vuln-GPAC-MP4Box-Assertion-Failure-in-xmt_parse_element.md"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/cve/CVE-2026-90611"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/submit/913517"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/vuln/403193"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/vuln/403193/cti"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:P/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-H7FF-CFC9-WMMH

Vulnerability from github – Published: 2022-09-16 22:15 – Updated: 2022-09-19 19:51
VLAI
Summary
TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`
Details

Impact

When tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack.

import tensorflow as tf
arg_0=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)
arg_1=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)
arg_2=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)
arg_3=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)
arg_4=8
arg_5=False
arg_6=None
tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient(gradients=arg_0, 
            inputs=arg_1, min=arg_2,  max=arg_3, num_bits=arg_4, 
            narrow_range=arg_5, name=arg_6)

Patches

We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed.

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 - 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology - Neophytos Christou, Secure Systems Labs, Brown University

Severity
5.9 (Medium)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "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-2022-35990"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T22:15:21Z",
    "nvd_published_at": "2022-09-16T22:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nWhen `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient` receives input `min` or `max` of rank other than 1, it gives a `CHECK` fail that can trigger a denial of service attack.\n```python\nimport tensorflow as tf\narg_0=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)\narg_1=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)\narg_2=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)\narg_3=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)\narg_4=8\narg_5=False\narg_6=None\ntf.quantization.fake_quant_with_min_max_vars_per_channel_gradient(gradients=arg_0, \n            inputs=arg_1, min=arg_2,  max=arg_3, num_bits=arg_4, \n            narrow_range=arg_5, name=arg_6)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f3cf67ac5705f4f04721d15e485e192bb319feed](https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed).\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 \n - \u5218\u529b\u6e90, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology\n - Neophytos Christou, Secure Systems Labs, Brown University\n",
  "id": "GHSA-h7ff-cfc9-wmmh",
  "modified": "2022-09-19T19:51:34Z",
  "published": "2022-09-16T22:15:21Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h7ff-cfc9-wmmh"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35990"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed"
    },
    {
      "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 `FakeQuantWithMinMaxVarsPerChannelGradient`"
}

GHSA-H9CC-W26M-J342

Vulnerability from github – Published: 2026-05-21 19:45 – Updated: 2026-06-10 13:41
VLAI
Summary
nimiq-keys: Denial of service in Ed25519 multisig delinearization via invalid curve points
Details

Impact

A denial-of-service vulnerability exists in the Ed25519 multisig delinearization code path. Ed25519PublicKey::delinearize() in keys/src/multisig/mod.rs called .unwrap() on curve point decompression, which panics when a public key is constructed from 32 bytes that do not represent a valid point on the Ed25519 curve. Ed25519PublicKey construction only validates byte length, not curve membership, so invalid keys can reach the delinearization path and crash the hosting process.

A secondary panic existed in Commitment::From<[u8; 32]>, which similarly called .unwrap() on a failing curve point decompression.

Who is affected: Browser and desktop wallet users of the web-client WASM library and the nimiq-wallet crate, when initiating a multisig operation with an attacker-supplied public key. An attacker must convince the user to include a crafted public key in a multisig setup — this is not a remotely triggerable node/validator crash.

Who is NOT affected: Validator nodes, consensus, blockchain, mempool, and networking code. There is no on-chain multisig account type; multisig is a purely client-side construct, and no validator/consensus code calls the multisig delinearization path.

Patches

See PR.

Workarounds

No code-level workaround exists short of the patch. Users of wallet applications can mitigate exposure by only performing multisig operations with public keys received from trusted sources.

Resources

  • Affected code: keys/src/multisig/mod.rs, keys/src/multisig/commitment.rs
Severity
4.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "crates.io",
        "name": "nimiq-keys"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.4.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-46542"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-05-21T19:45:08Z",
    "nvd_published_at": "2026-06-10T00:16:54Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\n\nA denial-of-service vulnerability exists in the Ed25519 multisig delinearization code path. `Ed25519PublicKey::delinearize()` in `keys/src/multisig/mod.rs` called `.unwrap()` on curve point decompression, which panics when a public key is\nconstructed from 32 bytes that do not represent a valid point on the Ed25519 curve. `Ed25519PublicKey` construction only validates byte length, not curve membership, so invalid keys can reach the delinearization path and crash the\nhosting process.\n\nA secondary panic existed in `Commitment::From\u003c[u8; 32]\u003e`, which similarly called `.unwrap()` on a failing curve point decompression.\n\n**Who is affected:** Browser and desktop wallet users of the web-client WASM library and the `nimiq-wallet` crate, when initiating a multisig operation with an attacker-supplied public key. An attacker must convince the user to include\na crafted public key in a multisig setup \u2014 this is not a remotely triggerable node/validator crash.\n\n**Who is NOT affected:** Validator nodes, consensus, blockchain, mempool, and networking code. There is no on-chain multisig account type; multisig is a purely client-side construct, and no validator/consensus code calls the multisig  delinearization path.\n\n### Patches\n\nSee [PR](https://github.com/nimiq/core-rs-albatross/pull/3713).\n\n### Workarounds\n\nNo code-level workaround exists short of the patch. Users of wallet applications can mitigate exposure by only performing multisig operations with public keys received from trusted sources.\n\n### Resources\n- Affected code: `keys/src/multisig/mod.rs`, `keys/src/multisig/commitment.rs`",
  "id": "GHSA-h9cc-w26m-j342",
  "modified": "2026-06-10T13:41:32Z",
  "published": "2026-05-21T19:45:08Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/nimiq/core-rs-albatross/security/advisories/GHSA-h9cc-w26m-j342"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-46542"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nimiq/core-rs-albatross/pull/3713"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nimiq/core-rs-albatross/commit/3bc449a8138960c4de6bfd506bad1730c621d4de"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/nimiq/core-rs-albatross"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nimiq/core-rs-albatross/releases/tag/v1.4.0"
    }
  ],
  "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:L",
      "type": "CVSS_V3"
    }
  ],
  "summary": "nimiq-keys: Denial of service in Ed25519 multisig delinearization via invalid curve points"
}
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.

← Back to the CWE list