Vulnerability-Lookup

CNVD-2021-63071

Vulnerability from cnvd - Published: 2021-08-18

Title

Google TensorFlow "tf.raw_ops.UpperBound"信息泄露漏洞

Description

Google TensorFlow是一个端到端开源机器学习平台。 Google TensorFlow "tf.raw_ops.UpperBound"存在安全漏洞。攻击者可利用此漏洞从堆分配数据的边界之外读取数据，并使用此信息对受影响的系统发起进一步的攻击。

Severity

中

Patch Name

Google TensorFlow "tf.raw_ops.UpperBound"信息泄露漏洞的补丁

Patch Description

Google TensorFlow是一个端到端开源机器学习平台。 Google TensorFlow "tf.raw_ops.UpperBound"存在安全漏洞。攻击者可利用此漏洞从堆分配数据的边界之外读取数据，并使用此信息对受影响的系统发起进一步的攻击。目前，供应商发布了安全公告及相关补丁信息，修复了此漏洞。

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-9697-98pf-4rw7

Reference

https://nvd.nist.gov/vuln/detail/CVE-2021-37670

Impacted products

Name
Google TensorFlow <2.6.0

Show details on source website

JSON

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    "cve": {
      "cveNumber": "CVE-2021-37670",
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  "number": "CNVD-2021-63071",
  "openTime": "2021-08-18",
  "patchDescription": "Google TensorFlow\u662f\u4e00\u4e2a\u7aef\u5230\u7aef\u5f00\u6e90\u673a\u5668\u5b66\u4e60\u5e73\u53f0\u3002\r\n\r\nGoogle TensorFlow \"tf.raw_ops.UpperBound\"\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u6b64\u6f0f\u6d1e\u4ece\u5806\u5206\u914d\u6570\u636e\u7684\u8fb9\u754c\u4e4b\u5916\u8bfb\u53d6\u6570\u636e\uff0c\u5e76\u4f7f\u7528\u6b64\u4fe1\u606f\u5bf9\u53d7\u5f71\u54cd\u7684\u7cfb\u7edf\u53d1\u8d77\u8fdb\u4e00\u6b65\u7684\u653b\u51fb\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": {
    "product": "Google TensorFlow \u003c2.6.0"
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  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2021-37670",
  "serverity": "\u4e2d",
  "submitTime": "2021-08-13",
  "title": "Google TensorFlow \"tf.raw_ops.UpperBound\"\u4fe1\u606f\u6cc4\u9732\u6f0f\u6d1e"
}

CVE-2021-37670 (GCVE-0-2021-37670)

Vulnerability from cvelistv5 – Published: 2021-08-12 22:25 – Updated: 2024-08-04 01:23

Title

Heap OOB in `UpperBound` and `LowerBound` in TensorFlow

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument. A similar issue occurs in `tf.raw_ops.LowerBound`. We have patched the issue in GitHub commit 42459e4273c2e47a3232cc16c4f4fff3b3a35c38. 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

5.5 (Medium)


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

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/4…	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

Show details on NVD website

JSON

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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.
Browse all ATT&CK techniques and the vulnerabilities related to each.

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CNVD-2021-63071

CVE-2021-37670 (GCVE-0-2021-37670)

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