Vulnerability-Lookup

CNVD-2022-87257

Vulnerability from cnvd - Published: 2022-12-08

Title

Google TensorFlow tf.raw_ops.FusedResizeAndPadConv2D缓冲区溢出漏洞

Description

Google TensorFlow是美国谷歌（Google）公司的一套用于机器学习的端到端开源平台。 Google TensorFlow 2.7.4之前版本、2.8.0及其之后版本，2.8.1之前版本、2.9.0及其之后版本，2.9.1之前版本存在缓冲区溢出漏洞，该漏洞源于“tf.raw_ops.FusedResizeAndPadConv2D“对用户提供的数据缺乏适当的验证，攻击者可利用漏洞导致缓冲区溢出。

Severity

高

Patch Name

Google TensorFlow tf.raw_ops.FusedResizeAndPadConv2D缓冲区溢出漏洞的补丁

Patch Description

Formal description

目前厂商已发布升级补丁以修复漏洞，补丁获取链接： https://github.com/tensorflow/tensorflow/security/advisories/GHSA-762h-vpvw-3rcx

Reference

https://github.com/tensorflow/tensorflow/commit/d66e1d568275e6a2947de97dca7a102a211e01ce

Impacted products

Name
['Google TensorFlow <2.7.4', 'Google TensorFlow >=2.8.0，<2.8.1', 'Google TensorFlow >=2.9.0，<2.9.1']

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{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2022-41885",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2022-41885"
    }
  },
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  "discovererName": "Neophytos Christou",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8865\u4e01\u83b7\u53d6\u94fe\u63a5\uff1a\r\nhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-762h-vpvw-3rcx",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-87257",
  "openTime": "2022-12-08",
  "patchDescription": "Google TensorFlow\u662f\u7f8e\u56fd\u8c37\u6b4c\uff08Google\uff09\u516c\u53f8\u7684\u4e00\u5957\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u7684\u7aef\u5230\u7aef\u5f00\u6e90\u5e73\u53f0\u3002\r\n\r\nGoogle TensorFlow 2.7.4\u4e4b\u524d\u7248\u672c\u30012.8.0\u53ca\u5176\u4e4b\u540e\u7248\u672c\uff0c2.8.1\u4e4b\u524d\u7248\u672c\u30012.9.0\u53ca\u5176\u4e4b\u540e\u7248\u672c\uff0c2.9.1\u4e4b\u524d\u7248\u672c\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u201ctf.raw_ops.FusedResizeAndPadConv2D\u201c\u5bf9\u7528\u6237\u63d0\u4f9b\u7684\u6570\u636e\u7f3a\u4e4f\u9002\u5f53\u7684\u9a8c\u8bc1\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u6f0f\u6d1e\u5bfc\u81f4\u7f13\u51b2\u533a\u6ea2\u51fa\u3002\u76ee\u524d\uff0c\u4f9b\u5e94\u5546\u53d1\u5e03\u4e86\u5b89\u5168\u516c\u544a\u53ca\u76f8\u5173\u8865\u4e01\u4fe1\u606f\uff0c\u4fee\u590d\u4e86\u6b64\u6f0f\u6d1e\u3002",
  "patchName": "Google TensorFlow tf.raw_ops.FusedResizeAndPadConv2D\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
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  "serverity": "\u9ad8",
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  "title": "Google TensorFlow tf.raw_ops.FusedResizeAndPadConv2D\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e"
}

CVE-2022-41885 (GCVE-0-2022-41885)

Vulnerability from cvelistv5 – Published: 2022-11-18 00:00 – Updated: 2025-04-22 16:06

Title

Overflow in `FusedResizeAndPadConv2D` in Tensorflow

Summary

TensorFlow is an open source platform for machine learning. When `tf.raw_ops.FusedResizeAndPadConv2D` is given a large tensor shape, it overflows. We have patched the issue in GitHub commit d66e1d568275e6a2947de97dca7a102a211e01ce. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

Severity

4.8 (Medium)


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

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-04-22 15:42 UTC

CWE

CWE-131 - Incorrect Calculation of Buffer Size

Assigner

GitHub_M mitre root

References

3 references

URL	Tags
https://github.com/tensorflow/tensorflow/security…
https://github.com/tensorflow/tensorflow/commit/d…
https://github.com/tensorflow/tensorflow/blob/mas…

Impacted products

1 product

Vendor	Product	Version
tensorflow	tensorflow	Affected: >= 2.9.0, < 2.9.1 Affected: >= 2.8.0, < 2.8.1 Affected: < 2.7.4

Show details on NVD website

JSON

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            "url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/conv_ops_fused_image_transform.cc"
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        ],
        "title": "CVE Program Container"
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        "metrics": [
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      "metrics": [
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            "attackVector": "NETWORK",
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            "baseScore": 4.8,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
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            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

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