Vulnerability-Lookup

GHSA-96V6-RMPC-R36J

Vulnerability from github – Published: 2022-05-24 16:51 – Updated: 2023-03-03 21:30

Details

J2B in libopenmpt before 0.4.2 allows an assertion failure during file parsing with debug STLs.

Severity

6.5 (Medium)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H

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{
  "affected": [],
  "aliases": [
    "CVE-2019-14383"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-07-30T19:15:00Z",
    "severity": "MODERATE"
  },
  "details": "J2B in libopenmpt before 0.4.2 allows an assertion failure during file parsing with debug STLs.",
  "id": "GHSA-96v6-rmpc-r36j",
  "modified": "2023-03-03T21:30:19Z",
  "published": "2022-05-24T16:51:44Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-14383"
    },
    {
      "type": "WEB",
      "url": "https://lib.openmpt.org/libopenmpt/2019/01/22/security-updates-0.4.2-0.3.15-0.2.11253-beta37-0.2.7561-beta20.5-p13-0.2.7386-beta20.3-p16"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00084.html"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00085.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-96VC-HJJ8-MP82

Vulnerability from github – Published: 2025-09-05 18:31 – Updated: 2026-05-12 15:31

Details

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

hfsplus: don't use BUG_ON() in hfsplus_create_attributes_file()

When the volume header contains erroneous values that do not reflect the actual state of the filesystem, hfsplus_fill_super() assumes that the attributes file is not yet created, which later results in hitting BUG_ON() when hfsplus_create_attributes_file() is called. Replace this BUG_ON() with -EIO error with a message to suggest running fsck tool.

Severity

5.5 (Medium)


                  
                    CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

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{
  "affected": [],
  "aliases": [
    "CVE-2025-38712"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-09-04T16:15:40Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nhfsplus: don\u0027t use BUG_ON() in hfsplus_create_attributes_file()\n\nWhen the volume header contains erroneous values that do not reflect\nthe actual state of the filesystem, hfsplus_fill_super() assumes that\nthe attributes file is not yet created, which later results in hitting\nBUG_ON() when hfsplus_create_attributes_file() is called. Replace this\nBUG_ON() with -EIO error with a message to suggest running fsck tool.",
  "id": "GHSA-96vc-hjj8-mp82",
  "modified": "2026-05-12T15:31:01Z",
  "published": "2025-09-05T18:31:17Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-38712"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/html/ssa-032379.html"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/03cd1db1494cf930e2fa042c9c13e32bffdb4eba"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1bb8da27ff15e346d4bc9e248e819c9a88ebf9d6"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/9046566fa692f88954dac8c510f37ee17a15fdb7"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/b3359392b75395a31af739a761f48f4041148226"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/bb0eea8e375677f586ad11c12e2525ed3fc698c2"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/c7c6363ca186747ebc2df10c8a1a51e66e0e32d9"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/ce5e387f396cbb5c061d9837abcac731e9e06f4d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d768e3ed430e89a699bf89d3214dcbbf4648c939"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/dee5c668ad71ddbcb4b48d95e8a4f371314ad41d"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2025/10/msg00007.html"
    },
    {
      "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-97P7-W86H-VCF9

Vulnerability from github – Published: 2022-09-16 20:51 – Updated: 2022-09-19 19:50

Summary

TensorFlow vulnerable to `CHECK` failure in `SobolSample` via missing validation

Details

Impact

The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by assuming input(0), input(1), and input(2) to be scalar.

import tensorflow as tf
tf.raw_ops.SobolSample(dim=tf.constant([1,0]), num_results=tf.constant([1]), skip=tf.constant([1]))

Patches

We have patched the issue in GitHub commit c65c67f88ad770662e8f191269a907bf2b94b1bf.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.

For more information

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

Attribution

This vulnerability has been reported by: - Kang Hong Jin from Singapore Management University - Neophytos Christou, Secure Systems Labs, Brown University - 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-2022-35935"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T20:51:55Z",
    "nvd_published_at": "2022-09-16T20:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nThe implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by assuming `input(0)`, `input(1)`, and `input(2)` to be scalar.\n```python\nimport tensorflow as tf\ntf.raw_ops.SobolSample(dim=tf.constant([1,0]), num_results=tf.constant([1]), skip=tf.constant([1]))\n```\n\n### Patches\nWe have patched the issue in GitHub commit [c65c67f88ad770662e8f191269a907bf2b94b1bf](https://github.com/tensorflow/tensorflow/commit/c65c67f88ad770662e8f191269a907bf2b94b1bf).\n\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- Kang Hong Jin from Singapore Management University\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-97p7-w86h-vcf9",
  "modified": "2022-09-19T19:50:05Z",
  "published": "2022-09-16T20:51:55Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-97p7-w86h-vcf9"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35935"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/c65c67f88ad770662e8f191269a907bf2b94b1bf"
    },
    {
      "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` failure in `SobolSample` via missing validation"
}

GHSA-97X5-WJV7-8W72

Vulnerability from github – Published: 2025-06-18 12:30 – Updated: 2025-12-17 21:30

Details

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

dm cache: prevent BUG_ON by blocking retries on failed device resumes

A cache device failing to resume due to mapping errors should not be retried, as the failure leaves a partially initialized policy object. Repeating the resume operation risks triggering BUG_ON when reloading cache mappings into the incomplete policy object.

Reproduce steps:

create a cache metadata consisting of 512 or more cache blocks, with some mappings stored in the first array block of the mapping array. Here we use cache_restore v1.0 to build the metadata.

cat <> cmeta.xml EOF dmsetup create cmeta --table "0 8192 linear /dev/sdc 0" cache_restore -i cmeta.xml -o /dev/mapper/cmeta --metadata-version=2 dmsetup remove cmeta

wipe the second array block of the mapping array to simulate data degradations.

mapping_root=$(dd if=/dev/sdc bs=1c count=8 skip=192 \ 2>/dev/null | hexdump -e '1/8 "%u\n"') ablock=$(dd if=/dev/sdc bs=1c count=8 skip=$((4096*mapping_root+2056)) \ 2>/dev/null | hexdump -e '1/8 "%u\n"') dd if=/dev/zero of=/dev/sdc bs=4k count=1 seek=$ablock

try bringing up the cache device. The resume is expected to fail due to the broken array block.

dmsetup create cmeta --table "0 8192 linear /dev/sdc 0" dmsetup create cdata --table "0 65536 linear /dev/sdc 8192" dmsetup create corig --table "0 524288 linear /dev/sdc 262144" dmsetup create cache --notable dmsetup load cache --table "0 524288 cache /dev/mapper/cmeta \ /dev/mapper/cdata /dev/mapper/corig 128 2 metadata2 writethrough smq 0" dmsetup resume cache

try resuming the cache again. An unexpected BUG_ON is triggered while loading cache mappings.

dmsetup resume cache

Kernel logs:

(snip) ------------[ cut here ]------------ kernel BUG at drivers/md/dm-cache-policy-smq.c:752! Oops: invalid opcode: 0000 [#1] PREEMPT SMP KASAN NOPTI CPU: 0 UID: 0 PID: 332 Comm: dmsetup Not tainted 6.13.4 #3 RIP: 0010:smq_load_mapping+0x3e5/0x570

Fix by disallowing resume operations for devices that failed the initial attempt.

Severity

5.5 (Medium)


                  
                    CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

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{
  "affected": [],
  "aliases": [
    "CVE-2025-38066"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-06-18T10:15:39Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\ndm cache: prevent BUG_ON by blocking retries on failed device resumes\n\nA cache device failing to resume due to mapping errors should not be\nretried, as the failure leaves a partially initialized policy object.\nRepeating the resume operation risks triggering BUG_ON when reloading\ncache mappings into the incomplete policy object.\n\nReproduce steps:\n\n1. create a cache metadata consisting of 512 or more cache blocks,\n   with some mappings stored in the first array block of the mapping\n   array. Here we use cache_restore v1.0 to build the metadata.\n\ncat \u003c\u003cEOF \u003e\u003e cmeta.xml\n\u003csuperblock uuid=\"\" block_size=\"128\" nr_cache_blocks=\"512\" \\\npolicy=\"smq\" hint_width=\"4\"\u003e\n  \u003cmappings\u003e\n    \u003cmapping cache_block=\"0\" origin_block=\"0\" dirty=\"false\"/\u003e\n  \u003c/mappings\u003e\n\u003c/superblock\u003e\nEOF\ndmsetup create cmeta --table \"0 8192 linear /dev/sdc 0\"\ncache_restore -i cmeta.xml -o /dev/mapper/cmeta --metadata-version=2\ndmsetup remove cmeta\n\n2. wipe the second array block of the mapping array to simulate\n   data degradations.\n\nmapping_root=$(dd if=/dev/sdc bs=1c count=8 skip=192 \\\n2\u003e/dev/null | hexdump -e \u00271/8 \"%u\\n\"\u0027)\nablock=$(dd if=/dev/sdc bs=1c count=8 skip=$((4096*mapping_root+2056)) \\\n2\u003e/dev/null | hexdump -e \u00271/8 \"%u\\n\"\u0027)\ndd if=/dev/zero of=/dev/sdc bs=4k count=1 seek=$ablock\n\n3. try bringing up the cache device. The resume is expected to fail\n   due to the broken array block.\n\ndmsetup create cmeta --table \"0 8192 linear /dev/sdc 0\"\ndmsetup create cdata --table \"0 65536 linear /dev/sdc 8192\"\ndmsetup create corig --table \"0 524288 linear /dev/sdc 262144\"\ndmsetup create cache --notable\ndmsetup load cache --table \"0 524288 cache /dev/mapper/cmeta \\\n/dev/mapper/cdata /dev/mapper/corig 128 2 metadata2 writethrough smq 0\"\ndmsetup resume cache\n\n4. try resuming the cache again. An unexpected BUG_ON is triggered\n   while loading cache mappings.\n\ndmsetup resume cache\n\nKernel logs:\n\n(snip)\n------------[ cut here ]------------\nkernel BUG at drivers/md/dm-cache-policy-smq.c:752!\nOops: invalid opcode: 0000 [#1] PREEMPT SMP KASAN NOPTI\nCPU: 0 UID: 0 PID: 332 Comm: dmsetup Not tainted 6.13.4 #3\nRIP: 0010:smq_load_mapping+0x3e5/0x570\n\nFix by disallowing resume operations for devices that failed the\ninitial attempt.",
  "id": "GHSA-97x5-wjv7-8w72",
  "modified": "2025-12-17T21:30:31Z",
  "published": "2025-06-18T12:30:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-38066"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/00586b78eeb7c626a14ca13453a1631f88a7cf36"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/025c8f477625eb39006ded650e7d027bcfb20e79"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/3986ef4a9b6a0d9c28bc325d8713beba5e67586f"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/5da692e2262b8f81993baa9592f57d12c2703dea"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/c5356a5e80442131e2714d0d26bb110590e4e568"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/c614584c2a66b538f469089ac089457a34590c14"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/cc80a5cc520939d0a7d071cc4ae4b3c55ef171d0"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/f3128e3074e8af565cc6a66fe3384a56df87f803"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2025/10/msg00007.html"
    },
    {
      "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-9879-VJ7M-R497

Vulnerability from github – Published: 2026-05-19 15:31 – Updated: 2026-05-19 18:32

Details

Any guest can cause xenstored to crash by issuing a XS_RESET_WATCHES command within a transaction due to an assert() triggering.

In case xenstored was built with NDEBUG #defined nothing bad will happen, as assert() is doing nothing in this case. Note that the default is not to define NDEBUG for xenstored builds even in release builds of Xen.

Severity

6.5 (Medium)


                  
                    CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:N/I:N/A:H

Show details on source website

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To clipboard

{
  "affected": [],
  "aliases": [
    "CVE-2026-23557"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-19T14:16:38Z",
    "severity": "MODERATE"
  },
  "details": "Any guest can cause xenstored to crash by issuing a XS_RESET_WATCHES\ncommand within a transaction due to an assert() triggering.\n\nIn case xenstored was built with NDEBUG #defined nothing bad will\nhappen, as assert() is doing nothing in this case. Note that the\ndefault is not to define NDEBUG for xenstored builds even in release\nbuilds of Xen.",
  "id": "GHSA-9879-vj7m-r497",
  "modified": "2026-05-19T18:32:08Z",
  "published": "2026-05-19T15:31:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-23557"
    },
    {
      "type": "WEB",
      "url": "https://xenbits.xenproject.org/xsa/advisory-484.html"
    },
    {
      "type": "WEB",
      "url": "http://www.openwall.com/lists/oss-security/2026/04/28/11"
    },
    {
      "type": "WEB",
      "url": "http://xenbits.xen.org/xsa/advisory-484.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-98GC-CHHF-M9GV

Vulnerability from github – Published: 2022-05-13 01:11 – Updated: 2025-04-20 03:34

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.

Severity

7.5 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

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{
  "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"
    }
  ]
}

GHSA-9939-379M-G97W

Vulnerability from github – Published: 2024-04-28 15:30 – Updated: 2025-09-16 18:31

Details

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

drm/gma500: Fix WARN_ON(lock->magic != lock) error

psb_gem_unpin() calls dma_resv_lock() but the underlying ww_mutex gets destroyed by drm_gem_object_release() move the drm_gem_object_release() call in psb_gem_free_object() to after the unpin to fix the below warning:

[ 79.693962] ------------[ cut here ]------------ [ 79.693992] DEBUG_LOCKS_WARN_ON(lock->magic != lock) [ 79.694015] WARNING: CPU: 0 PID: 240 at kernel/locking/mutex.c:582 __ww_mutex_lock.constprop.0+0x569/0xfb0 [ 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 [ 79.694436] CPU: 0 PID: 240 Comm: plymouthd Tainted: G W E 6.0.0-rc3+ #490 [ 79.694457] Hardware name: Packard Bell dot s/SJE01_CT, BIOS V1.10 07/23/2013 [ 79.694469] RIP: 0010:__ww_mutex_lock.constprop.0+0x569/0xfb0 [ 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 <0f> 0b e9 ed fa ff ff e8 5b 83 8a ff 85 c0 74 10 44 8b 0d 98 3c 11 [ 79.694513] RSP: 0018:ffffad1dc048bbe0 EFLAGS: 00010282 [ 79.694623] RAX: 0000000000000028 RBX: 0000000000000000 RCX: 0000000000000000 [ 79.694636] RDX: 0000000000000001 RSI: ffffffffaa8b0ffc RDI: 00000000ffffffff [ 79.694650] RBP: ffffad1dc048bc80 R08: 0000000000000000 R09: ffffad1dc048ba90 [ 79.694662] R10: 0000000000000003 R11: ffffffffaad62fe8 R12: ffff9ff302103138 [ 79.694675] R13: ffff9ff306ec8000 R14: ffff9ff307779078 R15: ffff9ff3014c0270 [ 79.694690] FS: 00007ff1cccf1740(0000) GS:ffff9ff3bc200000(0000) knlGS:0000000000000000 [ 79.694705] CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 [ 79.694719] CR2: 0000559ecbcb4420 CR3: 0000000013210000 CR4: 00000000000006f0 [ 79.694734] Call Trace: [ 79.694749] [ 79.694761] ? __schedule+0x47f/0x1670 [ 79.694796] ? psb_gem_unpin+0x27/0x1a0 [gma500_gfx] [ 79.694830] ? lock_is_held_type+0xe3/0x140 [ 79.694864] ? ww_mutex_lock+0x38/0xa0 [ 79.694885] ? __cond_resched+0x1c/0x30 [ 79.694902] ww_mutex_lock+0x38/0xa0 [ 79.694925] psb_gem_unpin+0x27/0x1a0 [gma500_gfx] [ 79.694964] psb_gem_unpin+0x199/0x1a0 [gma500_gfx] [ 79.694996] drm_gem_object_release_handle+0x50/0x60 [ 79.695020] ? drm_gem_object_handle_put_unlocked+0xf0/0xf0 [ 79.695042] idr_for_each+0x4b/0xb0 [ 79.695066] ? _raw_spin_unlock_irqrestore+0x30/0x60 [ 79.695095] drm_gem_release+0x1c/0x30 [ 79.695118] drm_file_free.part.0+0x1ea/0x260 [ 79.695150] drm_release+0x6a/0x120 [ 79.695175] __fput+0x9f/0x260 [ 79.695203] task_work_run+0x59/0xa0 [ 79.695227] do_exit+0x387/0xbe0 [ 79.695250] ? seqcount_lockdep_reader_access.constprop.0+0x82/0x90 [ 79.695275] ? lockdep_hardirqs_on+0x7d/0x100 [ 79.695304] do_group_exit+0x33/0xb0 [ 79.695331] __x64_sys_exit_group+0x14/0x20 [ 79.695353] do_syscall_64+0x58/0x80 [ 79.695376] ? up_read+0x17/0x20 [ 79.695401] ? lock_is_held_type+0xe3/0x140 [ 79.695429] ? asm_exc_page_fault+0x22/0x30 [ 79.695450] ? lockdep_hardirqs_on+0x7d/0x100 [ 79.695473] entry_SYSCALL_64_after_hwframe+0x63/0xcd [ 79.695493] RIP: 0033:0x7ff1ccefe3f1 [ 79.695516] Code: Unable to access opcode bytes at RIP 0x7ff1ccefe3c7. [ 79.695607] RSP: 002b:00007ffed4413378 EFLAGS: ---truncated---

Severity

5.5 (Medium)


                  
                    CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

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JSON

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{
  "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"
    }
  ]
}

GHSA-9942-R22V-78CP

Vulnerability from github – Published: 2022-09-16 22:29 – Updated: 2022-09-19 19:39

Summary

TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

Details

Impact

If 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.

import tensorflow as tf
depth_radius = 1
bias = 1.59018219
alpha = 0.117728651
beta = 0.404427052
input_grads = tf.random.uniform(shape=[4, 4, 4, 4], minval=-10000, maxval=10000, dtype=tf.float32, seed=-2033)
input_image = tf.random.uniform(shape=[4, 4, 4, 4], minval=-10000, maxval=10000, dtype=tf.float32, seed=-2033)
output_image = tf.random.uniform(shape=[4, 4, 4, 4, 4, 4], minval=-10000, maxval=10000, dtype=tf.float32, seed=-2033)
tf.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)

Patches

We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255.

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 Di Jin, Secure Systems Labs, Brown University

Severity

5.9 (Medium)


                  
                    CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-35985"
  ],
  "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`"
}

GHSA-9CG9-6HP2-VF6P

Vulnerability from github – Published: 2022-05-13 01:12 – Updated: 2022-05-13 01:12

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.

Severity

7.5 (High)


                  
                    CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

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{
  "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"
    }
  ]
}

GHSA-9CR2-8PWR-FHFQ

Vulnerability from github – Published: 2022-09-16 21:15 – Updated: 2022-09-19 19:51

Summary

TensorFlow vulnerable to `CHECK` fail in `QuantizeAndDequantizeV3`

Details

Impact

If 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.

import tensorflow as tf

signed_input = True
range_given = False
narrow_range = False
axis = -1
input = tf.constant(-3.5, shape=[1], dtype=tf.float32)
input_min = tf.constant(-3.5, shape=[1], dtype=tf.float32)
input_max = tf.constant(-3.5, shape=[1], dtype=tf.float32)
num_bits = tf.constant([], shape=[0], dtype=tf.int32)
tf.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)

Patches

We have patched the issue in GitHub commit f3f9cb38ecfe5a8a703f2c4a8fead434ef291713.

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 Neophytos Christou, Secure Systems Labs, Brown University.

Severity

5.9 (Medium)


                  
                    CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

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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-2022-36026"
  ],
  "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`"
}

CWE-617

Reachable Assertion

GHSA-96V6-RMPC-R36J

GHSA-96VC-HJJ8-MP82

GHSA-97P7-W86H-VCF9

Impact

Patches

For more information

Attribution

GHSA-97X5-WJV7-8W72

GHSA-9879-VJ7M-R497

GHSA-98GC-CHHF-M9GV

GHSA-9939-379M-G97W

GHSA-9942-R22V-78CP

Impact

Patches

For more information

Attribution

GHSA-9CG9-6HP2-VF6P

GHSA-9CR2-8PWR-FHFQ

Impact

Patches

For more information

Attribution

Mitigation

Mitigation