CWE-681

{
  "affected": [
    {
      "package": {
        "ecosystem": "Maven",
        "name": "org.hyperledger.besu:evm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "22.4.0-RC1"
            },
            {
              "fixed": "22.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-36025"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-196",
      "CWE-681"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-23T20:24:21Z",
    "nvd_published_at": "2022-09-24T02:15:00Z",
    "severity": "CRITICAL"
  },
  "details": "### Impact\nAn error in 32 bit signed and unsigned types in the calculation of available gas in the CALL operations (including DELEGATECALL) results in incorrect gas being passed into called contracts and incorrect gas being returned after call execution.  Where the amount of gas makes a difference in the success or failure, or if the gas is a negative 64 bit value, the execution will result in a different state root than expected, resulting in a consensus failure in networks with multiple EVM implementations. \n\nIn networks with a single EVM implementation this can be used to execute with significantly more gas than then transaction requested, possibly exceeding gas limitations. \n\n### Patches\nVersion 22.7.1 contains a fix, ensuring that excess gas will not be allocated to inner transaction calls and correcting the excess gas errors.\n\n### Workarounds\nReverting to version 22.1.3 or earlier will prevent incorrect execution. However many ethereum mainnet networks require changes in more recent versions of Besu and should not use older versions of besu and should instead use the patched version.  \n\nEthereum Classic and other networks not depending on a Proof of Stake transition should function fine with version 22.1.3 or earlier.\n\n### For more information\nIssue was found by [Martin Holst Swende](https://github.com/holiman) using [goevmlab](https://github.com/holiman/goevmlab), it is believed that no production networks have transactions that would trigger this failure.\n\n",
  "id": "GHSA-4456-w38r-m53x",
  "modified": "2022-09-23T20:24:21Z",
  "published": "2022-09-23T20:24:21Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/hyperledger/besu/security/advisories/GHSA-4456-w38r-m53x"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-36025"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/hyperledger/besu"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Besu VM vulnerable to gas allocation error in CALL operations"
}

{
  "affected": [],
  "aliases": [
    "CVE-2022-43663"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-195",
      "CWE-681",
      "CWE-704"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-03-20T21:15:00Z",
    "severity": "CRITICAL"
  },
  "details": "An integer conversion vulnerability exists in the SORBAx64.dll RecvPacket functionality of WellinTech KingHistorian 35.01.00.05. A specially crafted network packet can lead to a buffer overflow. An attacker can send a malicious packet to trigger this vulnerability.",
  "id": "GHSA-488p-w8x3-xh6m",
  "modified": "2023-03-23T21:30:20Z",
  "published": "2023-03-20T21:30:16Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-43663"
    },
    {
      "type": "WEB",
      "url": "https://talosintelligence.com/vulnerability_reports/TALOS-2022-1674"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

{
  "affected": [],
  "aliases": [
    "CVE-2021-21860"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-681",
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-08-16T20:15:00Z",
    "severity": "HIGH"
  },
  "details": "An exploitable integer truncation vulnerability exists within the MPEG-4 decoding functionality of the GPAC Project on Advanced Content library v1.0.1. A specially crafted MPEG-4 input can cause an improper memory allocation resulting in a heap-based buffer overflow that causes memory corruption. The FOURCC code, \u0027trik\u0027, is parsed by the function within the library. An attacker can convince a user to open a video to trigger this vulnerability.",
  "id": "GHSA-4q7h-5c9f-8xqg",
  "modified": "2022-05-24T19:11:11Z",
  "published": "2022-05-24T19:11:11Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-21860"
    },
    {
      "type": "WEB",
      "url": "https://talosintelligence.com/vulnerability_reports/TALOS-2021-1298"
    },
    {
      "type": "WEB",
      "url": "https://www.debian.org/security/2021/dsa-4966"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

{
  "affected": [],
  "aliases": [
    "CVE-2009-0231"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-119",
      "CWE-681"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2009-07-15T15:30:00Z",
    "severity": "HIGH"
  },
  "details": "The Embedded OpenType (EOT) Font Engine (T2EMBED.DLL) in Microsoft Windows 2000 SP4, XP SP2 and SP3, Server 2003 SP2, Vista Gold, SP1, and SP2, and Server 2008 Gold and SP2 allows remote attackers to execute arbitrary code via a crafted name table in a data record that triggers an integer truncation and a heap-based buffer overflow, aka \"Embedded OpenType Font Heap Overflow Vulnerability.\"",
  "id": "GHSA-56xw-8wf9-j3x9",
  "modified": "2024-02-08T03:32:44Z",
  "published": "2022-05-02T03:13:43Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2009-0231"
    },
    {
      "type": "WEB",
      "url": "https://docs.microsoft.com/en-us/security-updates/securitybulletins/2009/ms09-029"
    },
    {
      "type": "WEB",
      "url": "https://oval.cisecurity.org/repository/search/definition/oval%3Aorg.mitre.oval%3Adef%3A5457"
    },
    {
      "type": "WEB",
      "url": "http://labs.idefense.com/intelligence/vulnerabilities/display.php?id=811"
    },
    {
      "type": "WEB",
      "url": "http://osvdb.org/55842"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id?1022543"
    },
    {
      "type": "WEB",
      "url": "http://www.us-cert.gov/cas/techalerts/TA09-195A.html"
    },
    {
      "type": "WEB",
      "url": "http://www.vupen.com/english/advisories/2009/1887"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "vllm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.5.5"
            },
            {
              "last_affected": "0.23.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-53923"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-200",
      "CWE-681"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-06-17T14:03:11Z",
    "nvd_published_at": null,
    "severity": "MODERATE"
  },
  "details": "## Summary\n\nInteger truncation of tensor dimensions in vLLM\u0027s GGUF dequantize kernels (`csrc/quantization/gguf/gguf_kernel.cu`) causes partial tensor processing. The output tensor is allocated at full size via `torch::empty` (uninitialized memory), but the dequantize CUDA kernel processes only a truncated number of elements. The unfilled portion of the output tensor retains whatever was previously in GPU memory. In multi-tenant inference deployments, this residual GPU memory may contain tensor data from other users\u0027 inference requests, constituting information disclosure.\n\n## Root Cause\n\nThe `to_cuda_ggml_t` function pointer type at `ggml-common.h:1067` declares its element count parameter as `int` (32-bit):\n\n```cpp\nusing to_cuda_ggml_t = void (*)(const void * __restrict__ x,\n                                dst_t * __restrict__ y,\n                                int k,              // 32-bit\n                                cudaStream_t stream);\n```\n\nAll dequantize kernel functions (`dequantize_block_cuda`, `dequantize_row_q2_K_cuda`, etc. in `dequantize.cuh`) inherit this `int k` parameter and use it as the kernel launch grid size:\n\n```cpp\nstatic void dequantize_block_cuda(..., const int k, cudaStream_t stream) {\n    const int num_blocks = (k + 2*CUDA_DEQUANTIZE_BLOCK_SIZE - 1) / (2*CUDA_DEQUANTIZE_BLOCK_SIZE);\n    dequantize_block\u003c\u003c\u003cnum_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, 0, stream\u003e\u003e\u003e(vx, y, k);\n}\n```\n\nIn `ggml_dequantize()` at `gguf_kernel.cu:85`, the caller passes `m * n` (an `int64_t` product) to this `int k` parameter:\n\n```cpp\nat::Tensor DW = torch::empty({m, n}, options);    // line 80: full-size, UNINITIALIZED\n// ...\nto_cuda((void*)W.data_ptr(), (scalar_t*)DW.data_ptr(), m * n, stream);  // line 85: m*n truncated to int\n```\n\nWhen `m * n \u003e INT_MAX`, the truncated `k` is smaller than the actual tensor size. The kernel processes `k` elements. The remaining `(m * n) - k` elements in `DW` are never written and contain stale GPU memory.\n\nThis is a single root cause -- the `int` type on the `k` parameter in `to_cuda_ggml_t` -- with a single fix: change `int k` to `int64_t k`. All dequantize functions inherit this type through the same typedef.\n\n## Affected Functions\n\nAll in `csrc/quantization/gguf/gguf_kernel.cu`:\n\n| Function | Line | Allocation | Info Disclosure? |\n|----------|------|-----------|-----------------|\n| `ggml_dequantize` | 74 | `torch::empty({m, n})` at line 80 | Yes -- `m*n` truncated to `int k` at line 85 |\n| `ggml_mul_mat_vec_a8` | 91 | `torch::empty({vecs, row})` at line 99 | Yes -- `int col = X.sizes()[1]` at line 94 |\n| `ggml_mul_mat_a8` | 207 | `torch::empty({batch, row})` at line 215 | Yes -- `int col = X.sizes()[1]` at line 210 |\n| `ggml_moe_a8` | 279 | `torch::empty({tokens*top_k, row})` at line 289 | Yes -- `int col = X.sizes()[1]` at line 285 |\n\nAll four functions allocate output tensors with `torch::empty` (uninitialized) and then run CUDA kernels that use truncated dimension values as loop bounds. The unfilled portion of each output tensor retains stale GPU memory.\n\n`ggml_moe_a8_vec` (line 382) uses `torch::zeros` instead of `torch::empty`, so it is not affected by the info disclosure variant.\n\n## Impact: Information Disclosure in Multi-Tenant Serving\n\nvLLM is designed for multi-tenant inference serving. GPU memory is reused across requests from different users. When the dequantize kernel partially fills an output tensor:\n\n1. The output tensor `DW` is allocated with `torch::empty` -- the buffer contains whatever was previously in that GPU memory region\n2. The dequantize kernel fills only a truncated portion of the buffer\n3. The unfilled portion retains residual data from prior GPU operations, which may include tensor data from other users\u0027 inference requests\n4. The contaminated tensor proceeds through the model computation\n5. No error or warning is generated -- the partial fill is silent\n\nThis is a confidentiality violation. In shared inference deployments (the primary vLLM use case), one user\u0027s inference data can leak into another user\u0027s model computation through residual GPU memory.\n\n## Attacker Control\n\nThe attacker crafts a GGUF model file with weight tensor dimensions whose product exceeds `INT_MAX` (e.g., a matrix with shape `[65536, 65536]` gives `m * n = 4,294,967,296`). The model is hosted on HuggingFace or any model hub. The victim loads the model with vLLM for inference serving. The truncation happens automatically during model weight dequantization.\n\n## Fix\n\nA fix for this vulnerability was added here: https://github.com/vllm-project/vllm/pull/44971",
  "id": "GHSA-5jv2-g5wq-cmr4",
  "modified": "2026-06-17T14:03:11Z",
  "published": "2026-06-17T14:03:11Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-5jv2-g5wq-cmr4"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/pull/44971"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/commit/f219788f91952827132fa4fdf916427cd20d225e"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/vllm-project/vllm"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "vLLM: GGUF dequantize kernel int truncation exposes uninitialized GPU memory in multi-tenant serving"
}

{
  "affected": [],
  "aliases": [
    "CVE-2026-53133"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-681"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-25T09:16:30Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nRDMA/umem: Fix truncation for block sizes \u003e= 4G\n\nWhen the iommu is used the linearization of the mapping can give a single\nblock that is very large split across multiple SG entries.\n\nWhen __rdma_block_iter_next() reassembles the split SG entries it is\noverflowing the 32 bit stack values and computed the wrong DMA addresses\nfor blocks after the truncation.\n\nUse the right types to hold DMA addresses.",
  "id": "GHSA-5rwx-cqg3-893x",
  "modified": "2026-06-28T09:31:42Z",
  "published": "2026-06-25T09:31:18Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-53133"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/15fe76e23615f502d051ef0768f86babaf08746c"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2ff4b7817e5b78070c30f5fb5e678e452a2628b3"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/8fe0231adebe086c8a459c790944ac026cd99c6e"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/ac1aad8e1281534ce936c250f68084fc79c5469e"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/afd35fec9297195b759078745549c2671223f24f"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/baf8685bcf56dc1efb44b8f6a57c42516e549068"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/cc644d5608e3b0dadc970bd6e6aa26b91ea07d0f"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/dee2a49adeeb2a5e16a3fc858fa21b841c519802"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

{
  "affected": [],
  "aliases": [
    "CVE-2026-24174"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-681"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-04-07T18:16:39Z",
    "severity": "HIGH"
  },
  "details": "NVIDIA Triton Inference Server contains a vulnerability where an attacker could cause a server crash by sending a malformed request to the server. A successful exploit of this vulnerability might lead to denial of service.",
  "id": "GHSA-5vp6-8mmj-74fg",
  "modified": "2026-04-07T18:31:38Z",
  "published": "2026-04-07T18:31:38Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-24174"
    },
    {
      "type": "WEB",
      "url": "https://nvidia.custhelp.com/app/answers/detail/a_id/5816"
    },
    {
      "type": "WEB",
      "url": "https://www.cve.org/CVERecord?id=CVE-2026-24174"
    }
  ],
  "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-2019-19317"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-681"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2019-12-05T14:15:00Z",
    "severity": "HIGH"
  },
  "details": "lookupName in resolve.c in SQLite 3.30.1 omits bits from the colUsed bitmask in the case of a generated column, which allows attackers to cause a denial of service or possibly have unspecified other impact.",
  "id": "GHSA-6283-q875-5qpp",
  "modified": "2022-05-24T17:02:43Z",
  "published": "2022-05-24T17:02:43Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-19317"
    },
    {
      "type": "WEB",
      "url": "https://github.com/sqlite/sqlite/commit/522ebfa7cee96fb325a22ea3a2464a63485886a8"
    },
    {
      "type": "WEB",
      "url": "https://github.com/sqlite/sqlite/commit/73bacb7f93eab9f4bd5a65cbc4ae242acf63c9e3"
    },
    {
      "type": "WEB",
      "url": "https://cert-portal.siemens.com/productcert/pdf/ssa-389290.pdf"
    },
    {
      "type": "WEB",
      "url": "https://security.netapp.com/advisory/ntap-20191223-0001"
    },
    {
      "type": "WEB",
      "url": "https://www.oracle.com/security-alerts/cpuapr2020.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

{
  "affected": [],
  "aliases": [
    "CVE-2021-36357"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-681"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-10-22T12:15:00Z",
    "severity": "CRITICAL"
  },
  "details": "An issue was discovered in OpenPOWER 2.6 firmware. unpack_timestamp() calls le32_to_cpu() for endian conversion of a uint16_t \"year\" value, resulting in a type mismatch that can truncate a higher integer value to a smaller one, and bypass a timestamp check. The fix is to use the right endian conversion function.",
  "id": "GHSA-6552-8jmj-f95c",
  "modified": "2022-05-24T19:18:40Z",
  "published": "2022-05-24T19:18:40Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-36357"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open-power/skiboot/commit/5be38b672c1410e2f10acd3ad2eecfdc81d5daf7"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

{
  "affected": [],
  "aliases": [
    "CVE-2021-32996"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-192",
      "CWE-681"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-01-10T14:10:00Z",
    "severity": "HIGH"
  },
  "details": "The FANUC R-30iA and R-30iB series controllers are vulnerable to integer coercion errors, which cause the device to crash. A restart is required.",
  "id": "GHSA-6hf5-gqpw-h5ww",
  "modified": "2025-04-17T21:30:37Z",
  "published": "2022-01-11T00:01:35Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-32996"
    },
    {
      "type": "WEB",
      "url": "https://www.cisa.gov/uscert/ics/advisories/icsa-21-243-02"
    }
  ],
  "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"
    }
  ]
}