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-GH8H-7J2J-QV4F

Vulnerability from github – Published: 2021-11-10 19:31 – Updated: 2024-11-13 21:45
VLAI
Summary
Incomplete validation in `tf.summary.create_file_writer`
Details

Impact

If tf.summary.create_file_writer is called with non-scalar arguments code crashes due to a CHECK-fail.

import tensorflow as tf
import numpy as np
tf.summary.create_file_writer(logdir='', flush_millis=np.ones((1,2)))

Patches

We have patched the issue in GitHub commit 874bda09e6702cd50bac90b453b50bcc65b2769e (merging #51715).

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 externally via a GitHub issue.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41200"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-11-08T22:50:32Z",
    "nvd_published_at": "2021-11-05T20:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nIf `tf.summary.create_file_writer` is called with non-scalar arguments code crashes due to a `CHECK`-fail.\n\n```python\nimport tensorflow as tf\nimport numpy as np\ntf.summary.create_file_writer(logdir=\u0027\u0027, flush_millis=np.ones((1,2)))\n```\n\n### Patches\nWe have patched the issue in GitHub commit [874bda09e6702cd50bac90b453b50bcc65b2769e](https://github.com/tensorflow/tensorflow/commit/874bda09e6702cd50bac90b453b50bcc65b2769e) (merging [#51715](https://github.com/tensorflow/tensorflow/pull/51715)).\n\nThe fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 externally via a [GitHub issue](https://github.com/tensorflow/tensorflow/issues/46909).",
  "id": "GHSA-gh8h-7j2j-qv4f",
  "modified": "2024-11-13T21:45:00Z",
  "published": "2021-11-10T19:31:16Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gh8h-7j2j-qv4f"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41200"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/issues/46909"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/874bda09e6702cd50bac90b453b50bcc65b2769e"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-610.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-808.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-393.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    }
  ],
  "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:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Incomplete validation in `tf.summary.create_file_writer`"
}

GHSA-GHQC-WX9W-J5H4

Vulnerability from github – Published: 2023-09-05 09:30 – Updated: 2024-04-04 07:27
VLAI
Details

Transient DOS in Modem while processing RRC reconfiguration message.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-21653"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-09-05T07:15:12Z",
    "severity": "HIGH"
  },
  "details": "Transient DOS in Modem while processing RRC reconfiguration message.",
  "id": "GHSA-ghqc-wx9w-j5h4",
  "modified": "2024-04-04T07:27:01Z",
  "published": "2023-09-05T09:30:19Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-21653"
    },
    {
      "type": "WEB",
      "url": "https://www.qualcomm.com/company/product-security/bulletins/september-2023-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-GJQC-Q9G6-Q2J3

Vulnerability from github – Published: 2022-02-10 00:34 – Updated: 2024-11-07 22:28
VLAI
Summary
`CHECK`-failures in binary ops in Tensorflow
Details

Impact

A malicious user can cause a denial of service by altering a SavedModel such that any binary op would trigger CHECK failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the dtype no longer matches the dtype expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved:

functor::BinaryFunctor<Device, Functor, 1>()(
    eigen_device, out->template flat<Tout>(),
    input_0.template flat<Tin>(), input_1.template flat<Tin>(),
    error_ptr);

If Tin and Tout don't match the type of data in out and input_* tensors then flat<*> would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a CHECK crash, hence a denial of service.

Patches

We have patched the issue in GitHub commit a7c02f1a9bbc35473969618a09ee5f9f5d3e52d9. 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.

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-2022-23583"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617",
      "CWE-843"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-04T19:45:57Z",
    "nvd_published_at": "2022-02-04T23:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nA malicious user can cause a denial of service by altering a `SavedModel` such that [any binary op](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/cwise_ops_common.h#L88-L137) would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved:\n\n```cc\nfunctor::BinaryFunctor\u003cDevice, Functor, 1\u003e()(\n    eigen_device, out-\u003etemplate flat\u003cTout\u003e(),\n    input_0.template flat\u003cTin\u003e(), input_1.template flat\u003cTin\u003e(),\n    error_ptr);\n```\nIf `Tin` and `Tout` don\u0027t match the type of data in `out` and `input_*` tensors then `flat\u003c*\u003e` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service.\n\n### Patches\nWe have patched the issue in GitHub commit [a7c02f1a9bbc35473969618a09ee5f9f5d3e52d9](https://github.com/tensorflow/tensorflow/commit/a7c02f1a9bbc35473969618a09ee5f9f5d3e52d9).\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.",
  "id": "GHSA-gjqc-q9g6-q2j3",
  "modified": "2024-11-07T22:28:14Z",
  "published": "2022-02-10T00:34:13Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gjqc-q9g6-q2j3"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23583"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/a7c02f1a9bbc35473969618a09ee5f9f5d3e52d9"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-92.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-147.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/cwise_ops_common.h#L88-L137"
    }
  ],
  "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"
    }
  ],
  "summary": "`CHECK`-failures in binary ops in Tensorflow"
}

GHSA-GM3M-Q82F-958H

Vulnerability from github – Published: 2025-12-19 18:31 – Updated: 2026-02-24 06:31
VLAI
Details

A vulnerability has been found in Open5GS up to 2.7.5. Affected is the function ogs_pfcp_pdr_find_or_add/ogs_pfcp_far_find_or_add/ogs_pfcp_urr_find_or_add/ogs_pfcp_qer_find_or_add in the library lib/pfcp/context.c of the component QER/FAR/URR/PDR. The manipulation leads to reachable assertion. It is possible to initiate the attack remotely. The attack's complexity is rated as high. The exploitability is told to be difficult. The exploit has been disclosed to the public and may be used. The identifier of the patch is 442369dcd964f03d95429a6a01a57ed21f7779b7. Applying a patch is the recommended action to fix this issue.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-14954"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-12-19T16:15:55Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability has been found in Open5GS up to 2.7.5. Affected is the function ogs_pfcp_pdr_find_or_add/ogs_pfcp_far_find_or_add/ogs_pfcp_urr_find_or_add/ogs_pfcp_qer_find_or_add in the library lib/pfcp/context.c of the component QER/FAR/URR/PDR. The manipulation leads to reachable assertion. It is possible to initiate the attack remotely. The attack\u0027s complexity is rated as high. The exploitability is told to be difficult. The exploit has been disclosed to the public and may be used. The identifier of the patch is 442369dcd964f03d95429a6a01a57ed21f7779b7. Applying a patch is the recommended action to fix this issue.",
  "id": "GHSA-gm3m-q82f-958h",
  "modified": "2026-02-24T06:31:30Z",
  "published": "2025-12-19T18:31:17Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-14954"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open5gs/open5gs/issues/4181"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open5gs/open5gs/issues/4181#issue-3667069101"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open5gs/open5gs/issues/4181#issuecomment-3615646842"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open5gs/open5gs/commit/442369dcd964f03d95429a6a01a57ed21f7779b7"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open5gs/open5gs"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?ctiid.337590"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?id.337590"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?submit.716810"
    }
  ],
  "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:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:H/AT:N/PR:N/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-GMMJ-CHCC-2F2X

Vulnerability from github – Published: 2026-05-11 03:31 – Updated: 2026-05-11 03:31
VLAI
Details

A vulnerability was detected in WebAssembly Binaryen up to 117. This issue affects the function IRBuilder::makeBrOn of the file src/wasm/wasm-ir-builder.cpp of the component BrOn Parser. Performing a manipulation results in reachable assertion. The attack needs to be approached locally. The exploit is now public and may be used. The patch is named 1251efbc1ea471c1311d2726b2bbe061ff2a291c. It is suggested to install a patch to address this issue.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-8257"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-11T02:16:27Z",
    "severity": "LOW"
  },
  "details": "A vulnerability was detected in WebAssembly Binaryen up to 117. This issue affects the function IRBuilder::makeBrOn of the file src/wasm/wasm-ir-builder.cpp of the component BrOn Parser. Performing a manipulation results in reachable assertion. The attack needs to be approached locally. The exploit is now public and may be used. The patch is named 1251efbc1ea471c1311d2726b2bbe061ff2a291c. It is suggested to install a patch to address this issue.",
  "id": "GHSA-gmmj-chcc-2f2x",
  "modified": "2026-05-11T03:31:31Z",
  "published": "2026-05-11T03:31:31Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-8257"
    },
    {
      "type": "WEB",
      "url": "https://github.com/WebAssembly/binaryen/issues/8633"
    },
    {
      "type": "WEB",
      "url": "https://github.com/WebAssembly/binaryen/pull/8635"
    },
    {
      "type": "WEB",
      "url": "https://github.com/WebAssembly/binaryen/commit/1251efbc1ea471c1311d2726b2bbe061ff2a291c"
    },
    {
      "type": "WEB",
      "url": "https://github.com/HackC0der/CVE-Repos/blob/main/wasm-binaryen/Assertion_Failure_isRef_wasm_Type_getHeapType_commit_3ef8d19"
    },
    {
      "type": "WEB",
      "url": "https://github.com/WebAssembly/binaryen"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/submit/809552"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/vuln/362554"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/vuln/362554/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-GMQ5-QGC7-64GV

Vulnerability from github – Published: 2026-01-13 18:31 – Updated: 2026-03-25 21:30
VLAI
Details

In the Linux kernel, the following vulnerability has been resolved:

ipv6: fix a BUG in rt6_get_pcpu_route() under PREEMPT_RT

On PREEMPT_RT kernels, after rt6_get_pcpu_route() returns NULL, the current task can be preempted. Another task running on the same CPU may then execute rt6_make_pcpu_route() and successfully install a pcpu_rt entry. When the first task resumes execution, its cmpxchg() in rt6_make_pcpu_route() will fail because rt6i_pcpu is no longer NULL, triggering the BUG_ON(prev). It's easy to reproduce it by adding mdelay() after rt6_get_pcpu_route().

Using preempt_disable/enable is not appropriate here because ip6_rt_pcpu_alloc() may sleep.

Fix this by handling the cmpxchg() failure gracefully on PREEMPT_RT: free our allocation and return the existing pcpu_rt installed by another task. The BUG_ON is replaced by WARN_ON_ONCE for non-PREEMPT_RT kernels where such races should not occur.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-71080"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-01-13T16:16:07Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nipv6: fix a BUG in rt6_get_pcpu_route() under PREEMPT_RT\n\nOn PREEMPT_RT kernels, after rt6_get_pcpu_route() returns NULL, the\ncurrent task can be preempted. Another task running on the same CPU\nmay then execute rt6_make_pcpu_route() and successfully install a\npcpu_rt entry. When the first task resumes execution, its cmpxchg()\nin rt6_make_pcpu_route() will fail because rt6i_pcpu is no longer\nNULL, triggering the BUG_ON(prev). It\u0027s easy to reproduce it by adding\nmdelay() after rt6_get_pcpu_route().\n\nUsing preempt_disable/enable is not appropriate here because\nip6_rt_pcpu_alloc() may sleep.\n\nFix this by handling the cmpxchg() failure gracefully on PREEMPT_RT:\nfree our allocation and return the existing pcpu_rt installed by\nanother task. The BUG_ON is replaced by WARN_ON_ONCE for non-PREEMPT_RT\nkernels where such races should not occur.",
  "id": "GHSA-gmq5-qgc7-64gv",
  "modified": "2026-03-25T21:30:21Z",
  "published": "2026-01-13T18:31:06Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-71080"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1adaea51c61b52e24e7ab38f7d3eba023b2d050d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1dc33ad0867325f8d2c6d7b2a6f542d4f3121f66"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/787515ccb2292f82eb0876993129154629a49651"
    }
  ],
  "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:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-GPW5-J8CP-9P59

Vulnerability from github – Published: 2022-01-28 00:01 – Updated: 2022-02-03 00:00
VLAI
Details

There is an Assertion 'ppos != NULL && mjs_is_number(*ppos)' failed at src/mjs_core.c in Cesanta MJS v2.20.0.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-46514"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-01-27T21:15:00Z",
    "severity": "MODERATE"
  },
  "details": "There is an Assertion \u0027ppos != NULL \u0026\u0026 mjs_is_number(*ppos)\u0027 failed at src/mjs_core.c in Cesanta MJS v2.20.0.",
  "id": "GHSA-gpw5-j8cp-9p59",
  "modified": "2022-02-03T00:00:31Z",
  "published": "2022-01-28T00:01:22Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-46514"
    },
    {
      "type": "WEB",
      "url": "https://github.com/cesanta/mjs/issues/187"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-GQHV-6FQP-J722

Vulnerability from github – Published: 2022-05-13 01:49 – Updated: 2022-05-13 01:49
VLAI
Details

In libavcodec in FFmpeg 4.0.1, improper maintenance of the consistency between the context profile field and studio_profile in libavcodec may trigger an assertion failure while converting a crafted AVI file to MPEG4, leading to a denial of service, related to error_resilience.c, h263dec.c, and mpeg4videodec.c.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2018-13304"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-07-05T17:29:00Z",
    "severity": "MODERATE"
  },
  "details": "In libavcodec in FFmpeg 4.0.1, improper maintenance of the consistency between the context profile field and studio_profile in libavcodec may trigger an assertion failure while converting a crafted AVI file to MPEG4, leading to a denial of service, related to error_resilience.c, h263dec.c, and mpeg4videodec.c.",
  "id": "GHSA-gqhv-6fqp-j722",
  "modified": "2022-05-13T01:49:43Z",
  "published": "2022-05-13T01:49:43Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-13304"
    },
    {
      "type": "WEB",
      "url": "https://github.com/FFmpeg/FFmpeg/commit/bd27a9364ca274ca97f1df6d984e88a0700fb235"
    }
  ],
  "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-GVM4-H8J3-RJRQ

Vulnerability from github – Published: 2021-05-21 14:24 – Updated: 2024-11-01 16:56
VLAI
Summary
CHECK-fail in `LoadAndRemapMatrix`
Details

Impact

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

import tensorflow as tf

ckpt_path = tf.constant([], shape=[0], dtype=tf.string)
old_tensor_name = tf.constant("")
row_remapping = tf.constant([], shape=[0], dtype=tf.int64)
col_remapping = tf.constant([1], shape=[1], dtype=tf.int64)
initializing_values = tf.constant(1.0)

tf.raw_ops.LoadAndRemapMatrix(
    ckpt_path=ckpt_path, old_tensor_name=old_tensor_name,
    row_remapping=row_remapping, col_remapping=col_remapping,
    initializing_values=initializing_values, num_rows=0, num_cols=1)

This is because the implementation assumes that the ckpt_path is always a valid scalar.

const string& ckpt_path = ckpt_path_t->scalar<tstring>()();

However, an attacker can send any other tensor as the first argument of LoadAndRemapMatrix. This would cause the rank CHECK in scalar<T>()() to trigger and terminate the process.

Patches

We have patched the issue in GitHub commit 77dd114513d7796e1e2b8aece214a380af26fbf4.

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": [
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          "events": [
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              "introduced": "2.2.0"
            },
            {
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            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
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            {
              "introduced": "2.3.0"
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            }
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      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
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      ]
    },
    {
      "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-2021-29561"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T20:18:41Z",
    "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 `tf.raw_ops.LoadAndRemapMatrix`:\n    \n```python\nimport tensorflow as tf\n\nckpt_path = tf.constant([], shape=[0], dtype=tf.string)\nold_tensor_name = tf.constant(\"\")\nrow_remapping = tf.constant([], shape=[0], dtype=tf.int64)\ncol_remapping = tf.constant([1], shape=[1], dtype=tf.int64)\ninitializing_values = tf.constant(1.0)\n\ntf.raw_ops.LoadAndRemapMatrix(\n    ckpt_path=ckpt_path, old_tensor_name=old_tensor_name,\n    row_remapping=row_remapping, col_remapping=col_remapping,\n    initializing_values=initializing_values, num_rows=0, num_cols=1)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar.\n  \n```cc\nconst string\u0026 ckpt_path = ckpt_path_t-\u003escalar\u003ctstring\u003e()();\n```\n\nHowever, an attacker can send any other tensor as the first argument of `LoadAndRemapMatrix`. This would cause the rank `CHECK` in `scalar\u003cT\u003e()()` to trigger and terminate the process.\n\n### Patches\nWe have patched the issue in GitHub commit [77dd114513d7796e1e2b8aece214a380af26fbf4](https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4).\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-gvm4-h8j3-rjrq",
  "modified": "2024-11-01T16:56:08Z",
  "published": "2021-05-21T14:24:59Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gvm4-h8j3-rjrq"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29561"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-489.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-687.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-198.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 `LoadAndRemapMatrix`"
}

GHSA-H3X3-J454-4PHV

Vulnerability from github – Published: 2023-11-02 15:30 – Updated: 2025-11-04 00:30
VLAI
Details

A vulnerability was found in Avahi. A reachable assertion exists in the dbus_set_host_name function.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-38471"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-11-02T15:15:08Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability was found in Avahi. A reachable assertion exists in the dbus_set_host_name function.",
  "id": "GHSA-h3x3-j454-4phv",
  "modified": "2025-11-04T00:30:41Z",
  "published": "2023-11-02T15:30:27Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-38471"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/security/cve/CVE-2023-38471"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2191691"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2024/12/msg00011.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

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.