CWE-617

{
  "affected": [],
  "aliases": [
    "CVE-2016-9398"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-03-23T18:59:00Z",
    "severity": "HIGH"
  },
  "details": "The jpc_floorlog2 function in jpc_math.c in JasPer before 1.900.17 allows remote attackers to cause a denial of service (assertion failure) via unspecified vectors.",
  "id": "GHSA-98gc-chhf-m9gv",
  "modified": "2025-04-20T03:34:44Z",
  "published": "2022-05-13T01:11:42Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2016-9398"
    },
    {
      "type": "WEB",
      "url": "https://blogs.gentoo.org/ago/2016/11/16/jasper-multiple-assertion-failure"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=1396980"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/N4ALB4SXHURLVWKAOKYRNJXPABW3M22M"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/UPOVZTSIQPW2H4AFLMI3LHJEZGBVEQET"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/N4ALB4SXHURLVWKAOKYRNJXPABW3M22M"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/UPOVZTSIQPW2H4AFLMI3LHJEZGBVEQET"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2017-01/msg00008.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2017-01/msg00009.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-09/msg00082.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-09/msg00085.html"
    },
    {
      "type": "WEB",
      "url": "http://www.openwall.com/lists/oss-security/2016/11/17/1"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/94382"
    }
  ],
  "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"
    }
  ]
}

{
  "affected": [],
  "aliases": [
    "CVE-2022-48633"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-04-28T13:15:06Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\ndrm/gma500: Fix WARN_ON(lock-\u003emagic != lock) error\n\npsb_gem_unpin() calls dma_resv_lock() but the underlying ww_mutex\ngets destroyed by drm_gem_object_release() move the\ndrm_gem_object_release() call in psb_gem_free_object() to after\nthe unpin to fix the below warning:\n\n[   79.693962] ------------[ cut here ]------------\n[   79.693992] DEBUG_LOCKS_WARN_ON(lock-\u003emagic != lock)\n[   79.694015] WARNING: CPU: 0 PID: 240 at kernel/locking/mutex.c:582 __ww_mutex_lock.constprop.0+0x569/0xfb0\n[   79.694052] Modules linked in: rfcomm snd_seq_dummy snd_hrtimer qrtr bnep ath9k ath9k_common ath9k_hw snd_hda_codec_realtek snd_hda_codec_generic ledtrig_audio snd_hda_codec_hdmi snd_hda_intel ath3k snd_intel_dspcfg mac80211 snd_intel_sdw_acpi btusb snd_hda_codec btrtl btbcm btintel btmtk bluetooth at24 snd_hda_core snd_hwdep uvcvideo snd_seq libarc4 videobuf2_vmalloc ath videobuf2_memops videobuf2_v4l2 videobuf2_common snd_seq_device videodev acer_wmi intel_powerclamp coretemp mc snd_pcm joydev sparse_keymap ecdh_generic pcspkr wmi_bmof cfg80211 i2c_i801 i2c_smbus snd_timer snd r8169 rfkill lpc_ich soundcore acpi_cpufreq zram rtsx_pci_sdmmc mmc_core serio_raw rtsx_pci gma500_gfx(E) video wmi ip6_tables ip_tables i2c_dev fuse\n[   79.694436] CPU: 0 PID: 240 Comm: plymouthd Tainted: G        W   E      6.0.0-rc3+ #490\n[   79.694457] Hardware name: Packard Bell dot s/SJE01_CT, BIOS V1.10 07/23/2013\n[   79.694469] RIP: 0010:__ww_mutex_lock.constprop.0+0x569/0xfb0\n[   79.694496] Code: ff 85 c0 0f 84 15 fb ff ff 8b 05 ca 3c 11 01 85 c0 0f 85 07 fb ff ff 48 c7 c6 30 cb 84 aa 48 c7 c7 a3 e1 82 aa e8 ac 29 f8 ff \u003c0f\u003e 0b e9 ed fa ff ff e8 5b 83 8a ff 85 c0 74 10 44 8b 0d 98 3c 11\n[   79.694513] RSP: 0018:ffffad1dc048bbe0 EFLAGS: 00010282\n[   79.694623] RAX: 0000000000000028 RBX: 0000000000000000 RCX: 0000000000000000\n[   79.694636] RDX: 0000000000000001 RSI: ffffffffaa8b0ffc RDI: 00000000ffffffff\n[   79.694650] RBP: ffffad1dc048bc80 R08: 0000000000000000 R09: ffffad1dc048ba90\n[   79.694662] R10: 0000000000000003 R11: ffffffffaad62fe8 R12: ffff9ff302103138\n[   79.694675] R13: ffff9ff306ec8000 R14: ffff9ff307779078 R15: ffff9ff3014c0270\n[   79.694690] FS:  00007ff1cccf1740(0000) GS:ffff9ff3bc200000(0000) knlGS:0000000000000000\n[   79.694705] CS:  0010 DS: 0000 ES: 0000 CR0: 0000000080050033\n[   79.694719] CR2: 0000559ecbcb4420 CR3: 0000000013210000 CR4: 00000000000006f0\n[   79.694734] Call Trace:\n[   79.694749]  \u003cTASK\u003e\n[   79.694761]  ? __schedule+0x47f/0x1670\n[   79.694796]  ? psb_gem_unpin+0x27/0x1a0 [gma500_gfx]\n[   79.694830]  ? lock_is_held_type+0xe3/0x140\n[   79.694864]  ? ww_mutex_lock+0x38/0xa0\n[   79.694885]  ? __cond_resched+0x1c/0x30\n[   79.694902]  ww_mutex_lock+0x38/0xa0\n[   79.694925]  psb_gem_unpin+0x27/0x1a0 [gma500_gfx]\n[   79.694964]  psb_gem_unpin+0x199/0x1a0 [gma500_gfx]\n[   79.694996]  drm_gem_object_release_handle+0x50/0x60\n[   79.695020]  ? drm_gem_object_handle_put_unlocked+0xf0/0xf0\n[   79.695042]  idr_for_each+0x4b/0xb0\n[   79.695066]  ? _raw_spin_unlock_irqrestore+0x30/0x60\n[   79.695095]  drm_gem_release+0x1c/0x30\n[   79.695118]  drm_file_free.part.0+0x1ea/0x260\n[   79.695150]  drm_release+0x6a/0x120\n[   79.695175]  __fput+0x9f/0x260\n[   79.695203]  task_work_run+0x59/0xa0\n[   79.695227]  do_exit+0x387/0xbe0\n[   79.695250]  ? seqcount_lockdep_reader_access.constprop.0+0x82/0x90\n[   79.695275]  ? lockdep_hardirqs_on+0x7d/0x100\n[   79.695304]  do_group_exit+0x33/0xb0\n[   79.695331]  __x64_sys_exit_group+0x14/0x20\n[   79.695353]  do_syscall_64+0x58/0x80\n[   79.695376]  ? up_read+0x17/0x20\n[   79.695401]  ? lock_is_held_type+0xe3/0x140\n[   79.695429]  ? asm_exc_page_fault+0x22/0x30\n[   79.695450]  ? lockdep_hardirqs_on+0x7d/0x100\n[   79.695473]  entry_SYSCALL_64_after_hwframe+0x63/0xcd\n[   79.695493] RIP: 0033:0x7ff1ccefe3f1\n[   79.695516] Code: Unable to access opcode bytes at RIP 0x7ff1ccefe3c7.\n[   79.695607] RSP: 002b:00007ffed4413378 EFLAGS: \n---truncated---",
  "id": "GHSA-9939-379m-g97w",
  "modified": "2025-09-16T18:31:19Z",
  "published": "2024-04-28T15:30:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-48633"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/55c077d97fa67e9f19952bb24122a8316b089474"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/b6f25c3b94f2aadbf5cbef954db4073614943d74"
    }
  ],
  "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"
    }
  ]
}

{
  "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-2022-35985"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T22:29:52Z",
    "nvd_published_at": "2022-09-16T22:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nIf `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\ndepth_radius = 1\nbias = 1.59018219\nalpha = 0.117728651\nbeta = 0.404427052\ninput_grads = tf.random.uniform(shape=[4, 4, 4, 4], minval=-10000, maxval=10000, dtype=tf.float32, seed=-2033)\ninput_image = tf.random.uniform(shape=[4, 4, 4, 4], minval=-10000, maxval=10000, dtype=tf.float32, seed=-2033)\noutput_image = tf.random.uniform(shape=[4, 4, 4, 4, 4, 4], minval=-10000, maxval=10000, dtype=tf.float32, seed=-2033)\ntf.raw_ops.LRNGrad(input_grads=input_grads, input_image=input_image, output_image=output_image, depth_radius=depth_radius, bias=bias, alpha=alpha, beta=beta)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [bd90b3efab4ec958b228cd7cfe9125be1c0cf255](https://github.com/tensorflow/tensorflow/commit/bd90b3efab4ec958b228cd7cfe9125be1c0cf255).\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 Di Jin, Secure Systems Labs, Brown University\n",
  "id": "GHSA-9942-r22v-78cp",
  "modified": "2022-09-19T19:39:32Z",
  "published": "2022-09-16T22:29:52Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9942-r22v-78cp"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35985"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/bd90b3efab4ec958b228cd7cfe9125be1c0cf255"
    },
    {
      "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 `LRNGrad`"
}

{
  "affected": [],
  "aliases": [
    "CVE-2018-15822"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-08-23T23:29:00Z",
    "severity": "HIGH"
  },
  "details": "The flv_write_packet function in libavformat/flvenc.c in FFmpeg through 2.8 does not check for an empty audio packet, leading to an assertion failure.",
  "id": "GHSA-9cg9-6hp2-vf6p",
  "modified": "2022-05-13T01:12:13Z",
  "published": "2022-05-13T01:12:13Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-15822"
    },
    {
      "type": "WEB",
      "url": "https://github.com/FFmpeg/FFmpeg/commit/6b67d7f05918f7a1ee8fc6ff21355d7e8736aa10"
    },
    {
      "type": "WEB",
      "url": "https://github.com/FFmpeg/FFmpeg/commit/d8ecb335fe4852bbc172c7b79e66944d158b4d92"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2019/05/msg00043.html"
    },
    {
      "type": "WEB",
      "url": "https://seclists.org/bugtraq/2019/May/60"
    },
    {
      "type": "WEB",
      "url": "https://usn.ubuntu.com/3967-1"
    },
    {
      "type": "WEB",
      "url": "https://usn.ubuntu.com/4431-1"
    },
    {
      "type": "WEB",
      "url": "https://www.debian.org/security/2019/dsa-4449"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

{
  "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-2022-36026"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T21:15:36Z",
    "nvd_published_at": "2022-09-16T22:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nIf `QuantizeAndDequantizeV3` is given a nonscalar `num_bits` input tensor, it results in a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\n\nsigned_input = True\nrange_given = False\nnarrow_range = False\naxis = -1\ninput = tf.constant(-3.5, shape=[1], dtype=tf.float32)\ninput_min = tf.constant(-3.5, shape=[1], dtype=tf.float32)\ninput_max = tf.constant(-3.5, shape=[1], dtype=tf.float32)\nnum_bits = tf.constant([], shape=[0], dtype=tf.int32)\ntf.raw_ops.QuantizeAndDequantizeV3(input=input, input_min=input_min, input_max=input_max, num_bits=num_bits, signed_input=signed_input, range_given=range_given, narrow_range=narrow_range, axis=axis)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f3f9cb38ecfe5a8a703f2c4a8fead434ef291713](https://github.com/tensorflow/tensorflow/commit/f3f9cb38ecfe5a8a703f2c4a8fead434ef291713).\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 Neophytos Christou, Secure Systems Labs, Brown University.",
  "id": "GHSA-9cr2-8pwr-fhfq",
  "modified": "2022-09-19T19:51:14Z",
  "published": "2022-09-16T21:15:36Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9cr2-8pwr-fhfq"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-36026"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/f3f9cb38ecfe5a8a703f2c4a8fead434ef291713"
    },
    {
      "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 `QuantizeAndDequantizeV3`"
}

{
  "affected": [],
  "aliases": [
    "CVE-2018-5737"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-01-16T20:29:00Z",
    "severity": "HIGH"
  },
  "details": "A problem with the implementation of the new serve-stale feature in BIND 9.12 can lead to an assertion failure in rbtdb.c, even when stale-answer-enable is off. Additionally, problematic interaction between the serve-stale feature and NSEC aggressive negative caching can in some cases cause undesirable behavior from named, such as a recursion loop or excessive logging. Deliberate exploitation of this condition could cause operational problems depending on the particular manifestation -- either degradation or denial of service. Affects BIND 9.12.0 and 9.12.1.",
  "id": "GHSA-9cxr-pmg7-9w5v",
  "modified": "2022-05-13T01:32:04Z",
  "published": "2022-05-13T01:32:04Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-5737"
    },
    {
      "type": "WEB",
      "url": "https://kb.isc.org/docs/aa-01606"
    },
    {
      "type": "WEB",
      "url": "https://security.netapp.com/advisory/ntap-20180926-0004"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/104236"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id/1040942"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

{
  "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": "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"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-35971"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T22:20:09Z",
    "nvd_published_at": "2022-09-16T21:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nIf `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\n\nnum_bits = 8\nnarrow_range = False\ninputs = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmin = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmax = tf.constant(0, shape=[2,3], dtype=tf.float32)\ntf.raw_ops.FakeQuantWithMinMaxVars(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [785d67a78a1d533759fcd2f5e8d6ef778de849e0](https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0).\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 - Neophytos Christou, Secure Systems Labs, Brown University.\n - \u5218\u529b\u6e90, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology\n",
  "id": "GHSA-9fpg-838v-wpv7",
  "modified": "2022-09-19T19:36:24Z",
  "published": "2022-09-16T22:20:09Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9fpg-838v-wpv7"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35971"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0"
    },
    {
      "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 `FakeQuantWithMinMaxVars`"
}

{
  "affected": [],
  "aliases": [
    "CVE-2026-23375"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-03-25T11:16:37Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nmm: thp: deny THP for files on anonymous inodes\n\nfile_thp_enabled() incorrectly allows THP for files on anonymous inodes\n(e.g. guest_memfd and secretmem). These files are created via\nalloc_file_pseudo(), which does not call get_write_access() and leaves\ninode-\u003ei_writecount at 0. Combined with S_ISREG(inode-\u003ei_mode) being\ntrue, they appear as read-only regular files when\nCONFIG_READ_ONLY_THP_FOR_FS is enabled, making them eligible for THP\ncollapse.\n\nAnonymous inodes can never pass the inode_is_open_for_write() check\nsince their i_writecount is never incremented through the normal VFS\nopen path. The right thing to do is to exclude them from THP eligibility\naltogether, since CONFIG_READ_ONLY_THP_FOR_FS was designed for real\nfilesystem files (e.g. shared libraries), not for pseudo-filesystem\ninodes.\n\nFor guest_memfd, this allows khugepaged and MADV_COLLAPSE to create\nlarge folios in the page cache via the collapse path, but the\nguest_memfd fault handler does not support large folios. This triggers\nWARN_ON_ONCE(folio_test_large(folio)) in kvm_gmem_fault_user_mapping().\n\nFor secretmem, collapse_file() tries to copy page contents through the\ndirect map, but secretmem pages are removed from the direct map. This\ncan result in a kernel crash:\n\n    BUG: unable to handle page fault for address: ffff88810284d000\n    RIP: 0010:memcpy_orig+0x16/0x130\n    Call Trace:\n     collapse_file\n     hpage_collapse_scan_file\n     madvise_collapse\n\nSecretmem is not affected by the crash on upstream as the memory failure\nrecovery handles the failed copy gracefully, but it still triggers\nconfusing false memory failure reports:\n\n    Memory failure: 0x106d96f: recovery action for clean unevictable\n    LRU page: Recovered\n\nCheck IS_ANON_FILE(inode) in file_thp_enabled() to deny THP for all\nanonymous inode files.",
  "id": "GHSA-9ghh-p583-m6m8",
  "modified": "2026-04-24T18:30:41Z",
  "published": "2026-03-25T12:30:24Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-23375"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/0524ee56af2c9bfbad152a810f1ca95de8ca00d7"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/08de46a75f91a6661bc1ce0a93614f4bc313c581"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/dd085fe9a8ebfc5d10314c60452db38d2b75e609"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/f6fa05f0dddd387417d0c28281ddb951582514d6"
    }
  ],
  "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"
    }
  ]
}

{
  "affected": [],
  "aliases": [
    "CVE-2025-38637"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-04-18T07:15:43Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nnet_sched: skbprio: Remove overly strict queue assertions\n\nIn the current implementation, skbprio enqueue/dequeue contains an assertion\nthat fails under certain conditions when SKBPRIO is used as a child qdisc under\nTBF with specific parameters. The failure occurs because TBF sometimes peeks at\npackets in the child qdisc without actually dequeuing them when tokens are\nunavailable.\n\nThis peek operation creates a discrepancy between the parent and child qdisc\nqueue length counters. When TBF later receives a high-priority packet,\nSKBPRIO\u0027s queue length may show a different value than what\u0027s reflected in its\ninternal priority queue tracking, triggering the assertion.\n\nThe fix removes this overly strict assertions in SKBPRIO, they are not\nnecessary at all.",
  "id": "GHSA-9ghj-mrhr-8wxx",
  "modified": "2025-11-07T00:30:26Z",
  "published": "2025-04-18T15:31:38Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-38637"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/034b293bf17c124fec0f0e663f81203b00aa7a50"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1284733bab736e598341f1d3f3b94e2a322864a8"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1dcc144c322a8d526b791135604c0663f1af9d85"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2286770b07cb5268c03d11274b8efd43dff0d380"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2f35b7673a3aa3d09b3eb05811669622ebaa98ca"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/32ee79682315e6d3c99947b3f38b078a09a66919"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/7abc8318ce0712182bf0783dcfdd9a6a8331160e"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/864ca690ff135078d374bd565b9872f161c614bc"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/ce8fe975fd99b49c29c42e50f2441ba53112b2e8"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2025/05/msg00030.html"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2025/05/msg00045.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"
    }
  ]
}

{
  "affected": [],
  "aliases": [
    "CVE-2021-30328"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-04-01T05:15:00Z",
    "severity": "HIGH"
  },
  "details": "Possible assertion due to improper validation of invalid NR CSI-IM resource configuration in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Industrial IOT, Snapdragon Mobile",
  "id": "GHSA-9h5h-27f6-m48g",
  "modified": "2022-04-09T00:00:48Z",
  "published": "2022-04-02T00:00:17Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-30328"
    },
    {
      "type": "WEB",
      "url": "https://www.qualcomm.com/company/product-security/bulletins/march-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"
    }
  ]
}