Vulnerability-Lookup

CNVD-2022-09855

Vulnerability from cnvd - Published: 2022-02-12

Title

Google TensorFlow缓冲区溢出漏洞（CNVD-2022-09855）

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存在缓冲区溢出漏洞，该漏洞源于软件中的""tf.raw_ops.RaggedGather""参数无法确定有效的ragged tensor代码，会触发堆分配缓冲区边界外的数据读取操作。目前没有详细的漏洞细节提供。

Severity

低

Patch Name

Google TensorFlow缓冲区溢出漏洞（CNVD-2022-09855）的补丁

Patch Description

Formal description

厂商已发布了漏洞修复程序，请及时关注更新： https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-vvrj-w2p8

Reference

https://github.com/tensorflow/tensorflow/commit/a2b743f6017d7b97af1fe49087ae15f0ac634373

Impacted products

Name
['Google TensorFlow <2.6.0', 'Google TensorFlow <2.5.1', 'Google TensorFlow <2.4.3', 'Google TensorFlow <2.3.4']

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{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-37641",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-37641"
    }
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  "description": "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\n\nGoogle TensorFlow\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u8f6f\u4ef6\u4e2d\u7684\"\"tf.raw_ops.RaggedGather\"\"\u53c2\u6570\u65e0\u6cd5\u786e\u5b9a\u6709\u6548\u7684ragged tensor\u4ee3\u7801\uff0c\u4f1a\u89e6\u53d1\u5806\u5206\u914d\u7f13\u51b2\u533a\u8fb9\u754c\u5916\u7684\u6570\u636e\u8bfb\u53d6\u64cd\u4f5c\u3002\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u7684\u6f0f\u6d1e\u7ec6\u8282\u63d0\u4f9b\u3002",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-vvrj-w2p8",
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  "number": "CNVD-2022-09855",
  "openTime": "2022-02-12",
  "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\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u8f6f\u4ef6\u4e2d\u7684\"\"tf.raw_ops.RaggedGather\"\"\u53c2\u6570\u65e0\u6cd5\u786e\u5b9a\u6709\u6548\u7684ragged tensor\u4ee3\u7801\uff0c\u4f1a\u89e6\u53d1\u5806\u5206\u914d\u7f13\u51b2\u533a\u8fb9\u754c\u5916\u7684\u6570\u636e\u8bfb\u53d6\u64cd\u4f5c\u3002\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u7684\u6f0f\u6d1e\u7ec6\u8282\u63d0\u4f9b\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",
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  "products": {
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  "referenceLink": "https://github.com/tensorflow/tensorflow/commit/a2b743f6017d7b97af1fe49087ae15f0ac634373",
  "serverity": "\u4f4e",
  "submitTime": "2021-10-08",
  "title": "Google TensorFlow\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-09855\uff09"
}

CVE-2021-37641 (GCVE-0-2021-37641)

Vulnerability from cvelistv5 – Published: 2021-08-12 20:30 – Updated: 2024-08-04 01:23

Title

Heap OOB in `RaggedGather` in TensorFlow

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Severity

7.3 (High)


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

CWE

CWE-125 - Out-of-bounds Read

Assigner

GitHub_M mitre root

References

2 references

URL	Tags
https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/commit/a…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
tensorflow	tensorflow	Affected: >= 2.5.0, < 2.5.1 Affected: >= 2.4.0, < 2.4.3 Affected: < 2.3.4

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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.

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.
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CNVD-2022-09855

CVE-2021-37641 (GCVE-0-2021-37641)

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