ghsa-c94w-c95p-phf8
Vulnerability from github
7.1 (High) - CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
Impact
The implementation of OpLevelCostEstimator::CalculateTensorSize
is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements:
cc
int64_t OpLevelCostEstimator::CalculateTensorSize(
const OpInfo::TensorProperties& tensor, bool* found_unknown_shapes) {
int64_t count = CalculateTensorElementCount(tensor, found_unknown_shapes);
int size = DataTypeSize(BaseType(tensor.dtype()));
VLOG(2) << "Count: " << count << " DataTypeSize: " << size;
return count * size;
}
Here, count
and size
can be large enough to cause count * size
to overflow.
Patches
We have patched the issue in GitHub commit fcd18ce3101f245b083b30655c27b239dc72221e.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
{ "affected": [ { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.5.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.6.0" }, { "fixed": "2.6.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.7.0" }, { "fixed": "2.7.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.7.0" ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.5.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.6.0" }, { "fixed": "2.6.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.7.0" }, { "fixed": "2.7.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.7.0" ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.5.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.6.0" }, { "fixed": "2.6.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.7.0" }, { "fixed": "2.7.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.7.0" ] } ], "aliases": [ "CVE-2022-23575" ], "database_specific": { "cwe_ids": [ "CWE-190" ], "github_reviewed": true, "github_reviewed_at": "2022-02-04T20:19:53Z", "nvd_published_at": "2022-02-04T23:15:00Z", "severity": "HIGH" }, "details": "### Impact\nThe [implementation of `OpLevelCostEstimator::CalculateTensorSize`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558) is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements:\n```cc\nint64_t OpLevelCostEstimator::CalculateTensorSize(\n const OpInfo::TensorProperties\u0026 tensor, bool* found_unknown_shapes) {\n int64_t count = CalculateTensorElementCount(tensor, found_unknown_shapes);\n int size = DataTypeSize(BaseType(tensor.dtype()));\n VLOG(2) \u003c\u003c \"Count: \" \u003c\u003c count \u003c\u003c \" DataTypeSize: \" \u003c\u003c size;\n return count * size;\n}\n```\nHere, `count` and `size` can be large enough to cause `count * size` to overflow.\n\n### Patches\nWe have patched the issue in GitHub commit [fcd18ce3101f245b083b30655c27b239dc72221e](https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.", "id": "GHSA-c94w-c95p-phf8", "modified": "2024-11-13T22:48:17Z", "published": "2022-02-10T00:32:59Z", "references": [ { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c94w-c95p-phf8" }, { "type": "ADVISORY", "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23575" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-84.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-139.yaml" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558" } ], "schema_version": "1.4.0", "severity": [ { "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H", "type": "CVSS_V3" }, { "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N", "type": "CVSS_V4" } ], "summary": "Integer overflow in Tensorflow" }
Sightings
Author | Source | Type | Date |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.