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.

1249 vulnerabilities reference this CWE, most recent first.

GHSA-CV2P-32V3-VHWQ

Vulnerability from github – Published: 2022-09-16 21:39 – Updated: 2022-09-19 19:09
VLAI
Summary
TensorFlow vulnerable to `CHECK` fail in `RandomPoissonV2`
Details

Impact

When RandomPoissonV2 receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack.

import tensorflow as tf
arg_0=tf.random.uniform(shape=(4,), dtype=tf.int32, maxval=65536)
arg_1=tf.random.uniform(shape=(4, 4, 4, 4, 4), dtype=tf.float32, maxval=None)
arg_2=0
arg_3=0
arg_4=tf.int32
arg_5=None
tf.raw_ops.RandomPoissonV2(shape=arg_0, rate=arg_1, seed=arg_2,
                           seed2=arg_3, dtype=arg_4, name=arg_5)

Patches

We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3.

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.

Severity
5.9 (Medium)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
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{
  "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-2022-36003"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T21:39:10Z",
    "nvd_published_at": "2022-09-16T23:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nWhen `RandomPoissonV2` receives large input shape and rates, 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=(4,), dtype=tf.int32, maxval=65536)\narg_1=tf.random.uniform(shape=(4, 4, 4, 4, 4), dtype=tf.float32, maxval=None)\narg_2=0\narg_3=0\narg_4=tf.int32\narg_5=None\ntf.raw_ops.RandomPoissonV2(shape=arg_0, rate=arg_1, seed=arg_2,\n                           seed2=arg_3, dtype=arg_4, name=arg_5)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [552bfced6ce4809db5f3ca305f60ff80dd40c5a3](https://github.com/tensorflow/tensorflow/commit/552bfced6ce4809db5f3ca305f60ff80dd40c5a3).\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 \u5218\u529b\u6e90, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology.\n",
  "id": "GHSA-cv2p-32v3-vhwq",
  "modified": "2022-09-19T19:09:56Z",
  "published": "2022-09-16T21:39:10Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cv2p-32v3-vhwq"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-36003"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/552bfced6ce4809db5f3ca305f60ff80dd40c5a3"
    },
    {
      "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 `RandomPoissonV2`"
}

GHSA-CVCV-GHR7-J8GJ

Vulnerability from github – Published: 2026-10-14 18:32 – Updated: 2026-10-14 18:32
VLAI
Details

A Reachable Assertion vulnerability in the

l2ald

daemon of Juniper Networks Junos OS and Junos OS Evolved devices configured for MC-LAG/ICCP allows an adjacent attacker to cause a denial of service via an inconsistent ICCP peer message.

Severity
6.5 (Medium)
CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
7.1 (High)
CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:L
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2026-101996"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-10-14T17:17:52Z",
    "severity": "HIGH"
  },
  "details": "A Reachable Assertion vulnerability in the \n\nl2ald \n\ndaemon of Juniper Networks Junos OS and Junos OS Evolved devices configured for MC-LAG/ICCP allows an adjacent attacker to cause a denial of service via an inconsistent ICCP peer message.",
  "id": "GHSA-cvcv-ghr7-j8gj",
  "modified": "2026-10-14T18:32:22Z",
  "published": "2026-10-14T18:32:22Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-101996"
    },
    {
      "type": "WEB",
      "url": "https://supportportal.juniper.net/JSA112187"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:L/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-CVR3-87PR-9XFF

Vulnerability from github – Published: 2023-12-04 06:30 – Updated: 2023-12-07 18:30
VLAI
Details

In 5G Modem, there is a possible system crash due to improper error handling. This could lead to remote denial of service when receiving malformed RRC messages, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY01128524; Issue ID: MOLY01139296 (MSV-860).

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-2023-32845"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-12-04T04:15:07Z",
    "severity": "HIGH"
  },
  "details": "In 5G Modem, there is a possible system crash due to improper error handling. This could lead to remote denial of service when receiving malformed RRC messages, with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: MOLY01128524; Issue ID: MOLY01139296 (MSV-860).",
  "id": "GHSA-cvr3-87pr-9xff",
  "modified": "2023-12-07T18:30:29Z",
  "published": "2023-12-04T06:30:17Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-32845"
    },
    {
      "type": "WEB",
      "url": "https://corp.mediatek.com/product-security-bulletin/December-2023"
    }
  ],
  "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-CWF7-V3FR-VJH3

Vulnerability from github – Published: 2026-10-14 18:32 – Updated: 2026-10-14 18:32
VLAI
Details

A Reachable Assertion vulnerability in the srxpfe process of Juniper Networks Junos OS on SRX Series allows an adjacent network attacker to cause a denial of service of the data plane via malformed firewall-authentication synchronization traffic on chassis-cluster fabric interfaces.

Severity
6.5 (Medium)
CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
7.1 (High)
CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/AU:Y/R:A/V:C/RE:M
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2026-101936"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-10-14T17:17:45Z",
    "severity": "HIGH"
  },
  "details": "A Reachable Assertion vulnerability in the srxpfe process of Juniper Networks Junos OS on SRX Series allows an adjacent network attacker to cause a denial of service of the data plane via malformed firewall-authentication synchronization traffic on chassis-cluster fabric interfaces.",
  "id": "GHSA-cwf7-v3fr-vjh3",
  "modified": "2026-10-14T18:32:20Z",
  "published": "2026-10-14T18:32:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-101936"
    },
    {
      "type": "WEB",
      "url": "https://supportportal.juniper.net/JSA112186"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:Y/R:A/V:C/RE:M/U:X",
      "type": "CVSS_V4"
    }
  ]
}

GHSA-CWGJ-88JC-P385

Vulnerability from github – Published: 2025-01-22 15:32 – Updated: 2025-01-28 21:31
VLAI
Details

Open5GS MME versions <= 2.6.4 contain an assertion that can be remotely triggered via a malformed ASN.1 packet over the S1AP interface. An attacker may send an E-RAB Modification Indication message missing a required MME_UE_S1AP_ID field to repeatedly crash the MME, resulting in denial of service.

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

{
  "affected": [],
  "aliases": [
    "CVE-2023-37002"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-01-22T15:15:09Z",
    "severity": "MODERATE"
  },
  "details": "Open5GS MME versions \u003c= 2.6.4 contain an assertion that can be remotely triggered via a malformed ASN.1 packet over the S1AP interface. An attacker may send an `E-RAB Modification Indication` message missing a required `MME_UE_S1AP_ID` field to repeatedly crash the MME, resulting in denial of service.",
  "id": "GHSA-cwgj-88jc-p385",
  "modified": "2025-01-28T21:31:01Z",
  "published": "2025-01-22T15:32:34Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-37002"
    },
    {
      "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-CWJH-J5FP-PM2G

Vulnerability from github – Published: 2026-10-14 18:32 – Updated: 2026-10-14 18:32
VLAI
Details

A Reachable Assertion vulnerability in the routing protocol daemon (rpd) of Juniper Networks Junos OS and Junos OS Evolved allows an unauthenticated adjacent attacker to cause a denial of service via a specific RSVP packet.

Severity
6.5 (Medium)
CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
7.1 (High)
CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:L
Show details on source website
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{
  "affected": [],
  "aliases": [
    "CVE-2026-102071"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-10-14T17:18:03Z",
    "severity": "HIGH"
  },
  "details": "A Reachable Assertion vulnerability in the routing protocol daemon (rpd) of Juniper Networks Junos OS and Junos OS Evolved allows an unauthenticated adjacent attacker to cause a denial of service via a specific RSVP packet.",
  "id": "GHSA-cwjh-j5fp-pm2g",
  "modified": "2026-10-14T18:32:25Z",
  "published": "2026-10-14T18:32:25Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-102071"
    },
    {
      "type": "WEB",
      "url": "https://supportportal.juniper.net/JSA112187"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:L/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-F22P-QQ49-QCXH

Vulnerability from github – Published: 2026-10-21 15:42 – Updated: 2026-10-21 15:42
VLAI
Details

Enforceable assertion in the streaming feature of Apache bRPC (version < 1.18.0) on all platforms allows a remote attacker to crash the server process by sending a malformed stream feedback frame.

Root Cause: When handling FRAME_TYPE_FEEDBACK frames, bRPC calls Stream::SetRemoteConsumed() which contains CHECK(_cur_buf_size > 0) and unconditionally asserts CHECK(buf.IsEmpty()) on the frame payload. A feedback frame that carries an unexpected payload, or a feedback frame received on a stream where flow control is disabled (cur_buf_size == 0), reaches these assertions. On failure, CHECK failures abort the process, allowing an unauthenticated single client (once a stream is established) to terminate the server and cause a denial of service.

Affected Scenarios: Use bRPC server with the streaming control feature (Stream API) served from untrusted network.

How to Fix: 1. Upgrade bRPC to version 1.18.0, which fixes this issue. 2. Apply this patch: https://github.com/apache/brpc/pull/3494

The fix rejects malformed feedback frames with EPROTO and closes only the affected stream instead of crashing the whole process, and it bounds buffer shrinking so cur_buf_size never drops to 0 while flow control is enabled.

Show details on source website
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{
  "affected": [],
  "aliases": [
    "CVE-2026-82210"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-10-21T13:20:02Z",
    "severity": null
  },
  "details": "Enforceable assertion in the streaming feature of Apache bRPC (version \u003c 1.18.0) on all platforms allows a remote attacker to crash the server process by sending a malformed stream feedback frame.\n\nRoot Cause:\nWhen handling FRAME_TYPE_FEEDBACK frames, bRPC calls Stream::SetRemoteConsumed() which contains CHECK(_cur_buf_size \u003e 0) and unconditionally asserts CHECK(buf.IsEmpty()) on the frame payload. A feedback frame that carries an unexpected payload, or a feedback frame received on a stream where flow control is disabled (cur_buf_size == 0), reaches these assertions. On failure, CHECK failures abort the process, allowing an unauthenticated single client (once a stream is established) to terminate the server and cause a denial of service.\n\nAffected Scenarios:\nUse bRPC server with the streaming control feature (Stream API) served from untrusted network.\n\nHow to Fix:\n1. Upgrade bRPC to version 1.18.0, which fixes this issue.\n2. Apply this patch:  https://github.com/apache/brpc/pull/3494 \n\nThe fix rejects malformed feedback frames with EPROTO and closes only the affected stream instead of crashing the whole process, and it bounds buffer shrinking so cur_buf_size never drops to 0 while flow control is enabled.",
  "id": "GHSA-f22p-qq49-qcxh",
  "modified": "2026-10-21T15:42:28Z",
  "published": "2026-10-21T15:42:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-82210"
    },
    {
      "type": "WEB",
      "url": "https://lists.apache.org/thread/2pf15ojj0vr7rtx95677kgtl1mx3gdgb"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

GHSA-F2VV-V9CG-QHH7

Vulnerability from github – Published: 2022-02-09 23:43 – Updated: 2024-11-13 22:32
VLAI
Summary
Assertion failure based denial of service in Tensorflow
Details

Impact

The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail:

import tensorflow as tf

tf.raw_ops.DenseBincount(
  input=[[0], [1], [2]],
  size=[1],
  weights=[3,2,1],
  binary_output=False)

There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated.

Patches

We have patched the issue in GitHub commit 7019ce4f68925fd01cdafde26f8d8c938f47e6f9.

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

For more information

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

Attribution

This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.

Severity
6.5 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
7.1 (High)
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
Show details on source website
To clipboard 

{
  "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-2022-21737"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617",
      "CWE-754"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-03T19:59:49Z",
    "nvd_published_at": "2022-02-03T14:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact \nThe [implementation of `*Bincount` operations](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/bincount_op.cc) allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.DenseBincount(\n  input=[[0], [1], [2]],\n  size=[1],\n  weights=[3,2,1],\n  binary_output=False)\n```\n\nThere are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated.\n\n### Patches\nWe have patched the issue in GitHub commit [7019ce4f68925fd01cdafde26f8d8c938f47e6f9](https://github.com/tensorflow/tensorflow/commit/7019ce4f68925fd01cdafde26f8d8c938f47e6f9).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.",
  "id": "GHSA-f2vv-v9cg-qhh7",
  "modified": "2024-11-13T22:32:39Z",
  "published": "2022-02-09T23:43:48Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f2vv-v9cg-qhh7"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-21737"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/7019ce4f68925fd01cdafde26f8d8c938f47e6f9"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-61.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-116.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/bincount_op.cc"
    }
  ],
  "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"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Assertion failure based denial of service in Tensorflow"
}

GHSA-F344-CFPJ-CVMX

Vulnerability from github – Published: 2025-01-19 12:31 – Updated: 2026-10-15 03:34
VLAI
Details

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

fs: relax assertions on failure to encode file handles

Encoding file handles is usually performed by a filesystem >encode_fh() method that may fail for various reasons.

The legacy users of exportfs_encode_fh(), namely, nfsd and name_to_handle_at(2) syscall are ready to cope with the possibility of failure to encode a file handle.

There are a few other users of exportfs_encode_{fh,fid}() that currently have a WARN_ON() assertion when ->encode_fh() fails. Relax those assertions because they are wrong.

The second linked bug report states commit 16aac5ad1fa9 ("ovl: support encoding non-decodable file handles") in v6.6 as the regressing commit, but this is not accurate.

The aforementioned commit only increases the chances of the assertion and allows triggering the assertion with the reproducer using overlayfs, inotify and drop_caches.

Triggering this assertion was always possible with other filesystems and other reasons of ->encode_fh() failures and more particularly, it was also possible with the exact same reproducer using overlayfs that is mounted with options index=on,nfs_export=on also on kernels < v6.6. Therefore, I am not listing the aforementioned commit as a Fixes commit.

Backport hint: this patch will have a trivial conflict applying to v6.6.y, and other trivial conflicts applying to stable kernels < v6.6.

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

{
  "affected": [],
  "aliases": [
    "CVE-2024-57924"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-01-19T12:15:26Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nfs: relax assertions on failure to encode file handles\n\nEncoding file handles is usually performed by a filesystem \u003eencode_fh()\nmethod that may fail for various reasons.\n\nThe legacy users of exportfs_encode_fh(), namely, nfsd and\nname_to_handle_at(2) syscall are ready to cope with the possibility\nof failure to encode a file handle.\n\nThere are a few other users of exportfs_encode_{fh,fid}() that\ncurrently have a WARN_ON() assertion when -\u003eencode_fh() fails.\nRelax those assertions because they are wrong.\n\nThe second linked bug report states commit 16aac5ad1fa9 (\"ovl: support\nencoding non-decodable file handles\") in v6.6 as the regressing commit,\nbut this is not accurate.\n\nThe aforementioned commit only increases the chances of the assertion\nand allows triggering the assertion with the reproducer using overlayfs,\ninotify and drop_caches.\n\nTriggering this assertion was always possible with other filesystems and\nother reasons of -\u003eencode_fh() failures and more particularly, it was\nalso possible with the exact same reproducer using overlayfs that is\nmounted with options index=on,nfs_export=on also on kernels \u003c v6.6.\nTherefore, I am not listing the aforementioned commit as a Fixes commit.\n\nBackport hint: this patch will have a trivial conflict applying to\nv6.6.y, and other trivial conflicts applying to stable kernels \u003c v6.6.",
  "id": "GHSA-f344-cfpj-cvmx",
  "modified": "2026-10-15T03:34:26Z",
  "published": "2025-01-19T12:31:26Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-57924"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/html/ssa-019113.html"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/html/ssa-032379.html"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/html/ssa-082556.html"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/html/ssa-457936.html"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/73697928c806fe4689939722184a86fc1c1957b4"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/974e3fe0ac61de85015bbe5a4990cf4127b304b2"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/adcde2872f8fc399b249758ae1990dcd53b694ea"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/f47c834a9131ae64bee3c462f4e610c67b0a000f"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2025/10/msg00008.html"
    }
  ],
  "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-F395-X2GF-VH84

Vulnerability from github – Published: 2026-05-01 15:30 – Updated: 2026-05-03 09:33
VLAI
Details

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

crypto: tegra - Add missing CRYPTO_ALG_ASYNC

The tegra crypto driver failed to set the CRYPTO_ALG_ASYNC on its asynchronous algorithms, causing the crypto API to select them for users that request only synchronous algorithms. This causes crashes (at least). Fix this by adding the flag like what the other drivers do. Also remove the unnecessary CRYPTO_ALG_TYPE_* flags, since those just get ignored and overridden by the registration function anyway.

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

{
  "affected": [],
  "aliases": [
    "CVE-2026-31739"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-20",
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-01T15:16:36Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\ncrypto: tegra - Add missing CRYPTO_ALG_ASYNC\n\nThe tegra crypto driver failed to set the CRYPTO_ALG_ASYNC on its\nasynchronous algorithms, causing the crypto API to select them for users\nthat request only synchronous algorithms.  This causes crashes (at\nleast).  Fix this by adding the flag like what the other drivers do.\nAlso remove the unnecessary CRYPTO_ALG_TYPE_* flags, since those just\nget ignored and overridden by the registration function anyway.",
  "id": "GHSA-f395-x2gf-vh84",
  "modified": "2026-05-03T09:33:10Z",
  "published": "2026-05-01T15:30:34Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-31739"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/3aea268b6d5cde3b087df9eeecc3bc620aa09513"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/429d05565eb19ee545d8a8395991372adbe4daf3"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/4b56770d345524fc2acc143a2b85539cf7d74bc1"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/bdbf027a4504b4a86740de6beb6d18a957331839"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/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.

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