Hi ryuo, welcome to the openEuler Community.
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If you have any questions, please contact the SIG: sig-ai-bigdata, and any of the maintainers: @sinever , @unioah , @wuzeyi1 , @njlzk , @yangzhao_kl


@sinever ,@unioah ,@wuzeyi1 ,@njlzk ,@yangzhao_kl
issue处理注意事项:
1. 当前issue受影响的分支提交pr时, 须在pr描述中填写当前issue编号进行关联, 否则无法关闭当前issue;
2. 模板内容需要填写完整, 无论是受影响或者不受影响都需要填写完整内容,未引入的分支不需要填写, 否则无法关闭当前issue;
3. 以下为模板中需要填写完整的内容, 请复制到评论区回复, 注: 内容的标题名称(影响性分析说明, openEuler评分, 受影响版本排查(受影响/不受影响), 修复是否涉及abi变化(是/否))不能省略,省略后cve-manager将无法正常解析填写内容.
影响性分析说明:
openEuler评分: (评分和向量)
受影响版本排查(受影响/不受影响):
1.openEuler-20.03-LTS-SP1:
2.openEuler-20.03-LTS-SP2:
3.openEuler-20.03-LTS-SP3:
修复是否涉及abi变化(是/否):
1.openEuler-20.03-LTS-SP1:
2.openEuler-20.03-LTS-SP2:
3.openEuler-20.03-LTS-SP3:
issue处理具体操作请参考:
https://gitee.com/openeuler/cve-manager/blob/master/cve-vulner-manager/doc/md/manual.md
pr关联issue具体操作请参考:
https://gitee.com/help/articles/4142


@ryuo CVE信息从NVD同步成功, 稍后请重新加载页面.


影响性分析说明:
TensorFlow是一个开源的机器学习平台。在受影响的版本中,几个TensorFlow操作缺少对调用中涉及的Tensor参数形状的验证。根据API的不同,这可能会导致未定义的行为和segfault或“ check ”-fail相关的崩溃,但在某些情况下,从堆填充的数组进行写入和读取也是可能的。我们在内部通过工具发现了这些问题,同时致力于改进/测试GPU操作确定性。因此,我们没有复制器,将有多个修复这些问题。这些修复将包含在TensorFlow 2.7.0中。我们还将在TensorFlow 2.6.1、TensorFlow 2.5.2和TensorF low 2.4.4上挑选这些提交,因为它们也受到影响,并且仍在支持范围内。
openEuler评分:
7.8
Vector:CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
受影响版本排查(受影响/不受影响):
1.master(2.8.2):不受影响
2.openEuler-22.03-LTS(2.8.2):不受影响
3.openEuler-22.03-LTS-Next(2.8.2):不受影响
4.openEuler-20.03-LTS-SP1:不受影响
5.openEuler-20.03-LTS-SP3:不受影响
修复是否涉及abi变化(是/否):
1.master(2.8.2):否
2.openEuler-22.03-LTS(2.8.2):否
3.openEuler-22.03-LTS-Next(2.8.2):否
4.openEuler-20.03-LTS-SP1:否
5.openEuler-20.03-LTS-SP3:否


@small_leek 经过 cve-manager 解析, 已分析的内容如下表所示:
| 状态 | 需分析 | 内容 |
|---|---|---|
| 已分析 | 1.影响性分析说明 | TensorFlow是一个开源的机器学习平台。在受影响的版本中,几个TensorFlow操作缺少对调用中涉及的Tensor参数形状的验证。根据API的不同,这可能会导致未定义的行为和segfault或“ check ”-fail相关的崩溃,但在某些情况下,从堆填充的数组进行写入和读取也是可能的。我们在内部通过工具发现了这些问题,同时致力于改进/测试GPU操作确定性。因此,我们没有复制器,将有多个修复这些问题。这些修复将包含在TensorFlow 2.7.0中。我们还将在TensorFlow 2.6.1、TensorFlow 2.5.2和TensorF low 2.4.4上挑选这些提交,因为它们也受到影响,并且仍在支持范围内。 |
| 已分析 | 2.openEulerScore | 7.8 |
| 已分析 | 2.openEulerVector | AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H |
| 已分析 | 3.受影响版本排查 | master:不受影响,openEuler-22.03-LTS:不受影响,openEuler-22.03-LTS-Next:不受影响,openEuler-20.03-LTS-SP1:不受影响,openEuler-20.03-LTS-SP3:不受影响 |
| 已分析 | 4.修复是否涉及abi变化 | master:否,openEuler-22.03-LTS:否,openEuler-22.03-LTS-Next:否,openEuler-20.03-LTS-SP1:否,openEuler-20.03-LTS-SP3:否 |
请确认分析内容的准确性, 确认无误后, 您可以进行后续步骤, 否则您可以继续分析.


一、漏洞信息
漏洞编号:CVE-2021-41206
漏洞归属组件:tensorflow
漏洞归属的版本:1.15.2,2.3.1
CVSS V3.0分值:
BaseScore:7.8 High
Vector:CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
漏洞简述:
TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or
CHECK-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don t have reproducers and there will be multiple fixes for these issues. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.漏洞公开时间:2021-11-06 06:15
漏洞创建时间:2022-04-02 02:07:46
漏洞详情参考链接:
https://nvd.nist.gov/vuln/detail/CVE-2021-41206
更多参考(点击展开)
漏洞分析指导链接:
https://gitee.com/openeuler/cve-manager/blob/master/cve-vulner-manager/doc/md/manual.md
漏洞数据来源:
openBrain开源漏洞感知系统
漏洞补丁信息:
详情(点击展开)
无
二、漏洞分析结构反馈
影响性分析说明:
TensorFlow是一个开源的机器学习平台。在受影响的版本中,几个TensorFlow操作缺少对调用中涉及的Tensor参数形状的验证。根据API的不同,这可能会导致未定义的行为和segfault或“ check ”-fail相关的崩溃,但在某些情况下,从堆填充的数组进行写入和读取也是可能的。我们在内部通过工具发现了这些问题,同时致力于改进/测试GPU操作确定性。因此,我们没有复制器,将有多个修复这些问题。这些修复将包含在TensorFlow 2.7.0中。我们还将在TensorFlow 2.6.1、TensorFlow 2.5.2和TensorF low 2.4.4上挑选这些提交,因为它们也受到影响,并且仍在支持范围内。
openEuler评分:
7.8
Vector:CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
受影响版本排查(受影响/不受影响):
1.master(2.12.1):不受影响
2.openEuler-22.03-LTS(2.8.2):不受影响
3.openEuler-22.03-LTS-Next(2.10.0):不受影响
4.openEuler-20.03-LTS-SP1:不受影响
5.openEuler-20.03-LTS-SP3:不受影响
6.openEuler-24.03-LTS(2.12.1):
7.openEuler-24.03-LTS-Next(2.12.1):
8.openEuler-22.03-LTS-SP4(2.10.0):
修复是否涉及abi变化(是/否):
1.master(2.12.1):否
2.openEuler-22.03-LTS(2.8.2):否
3.openEuler-22.03-LTS-Next(2.10.0):否
4.openEuler-20.03-LTS-SP1:否
5.openEuler-20.03-LTS-SP3:否
6.openEuler-24.03-LTS(2.12.1):
7.openEuler-24.03-LTS-Next(2.12.1):
8.openEuler-22.03-LTS-SP4(2.10.0):
9.master(2.12.1):
10.openEuler-20.03-LTS-SP4:
11.openEuler-22.03-LTS-SP3(2.10.0):
12.openEuler-22.03-LTS-SP4(2.10.0):
13.openEuler-24.03-LTS(2.12.1):
14.openEuler-24.03-LTS-Next(2.12.1):
15.openEuler-24.03-LTS-SP1(2.12.1):
16.openEuler-24.03-LTS-SP2(2.12.1):
17.master(2.12.1):
18.openEuler-20.03-LTS-SP4:
19.openEuler-22.03-LTS-SP3(2.10.0):
20.openEuler-22.03-LTS-SP4(2.10.0):
21.openEuler-24.03-LTS(2.12.1):
22.openEuler-24.03-LTS-Next(2.12.1):
23.openEuler-24.03-LTS-SP1(2.12.1):
24.openEuler-24.03-LTS-SP2(2.12.1):
25.master(2.12.1):
26.openEuler-20.03-LTS-SP4:
27.openEuler-22.03-LTS-SP3(2.10.0):
28.openEuler-22.03-LTS-SP4(2.10.0):
29.openEuler-24.03-LTS(2.12.1):
30.openEuler-24.03-LTS-Next(2.12.1):
31.openEuler-24.03-LTS-SP1(2.12.1):
32.openEuler-24.03-LTS-SP2(2.12.1):
33.master(2.12.1):
34.openEuler-20.03-LTS-SP4:
35.openEuler-22.03-LTS-SP3(2.10.0):
36.openEuler-22.03-LTS-SP4(2.10.0):
37.openEuler-24.03-LTS(2.12.1):
38.openEuler-24.03-LTS-Next(2.12.1):
39.openEuler-24.03-LTS-SP1(2.12.1):
40.openEuler-24.03-LTS-SP2(2.12.1):
41.master(2.12.1):
42.openEuler-20.03-LTS-SP4:
43.openEuler-22.03-LTS-SP3(2.10.0):
44.openEuler-22.03-LTS-SP4(2.10.0):
45.openEuler-24.03-LTS(2.12.1):
46.openEuler-24.03-LTS-Next(2.12.1):
47.openEuler-24.03-LTS-SP1(2.12.1):
48.openEuler-24.03-LTS-SP2(2.12.1):
49.master(2.12.1):
50.openEuler-20.03-LTS-SP4:
51.openEuler-22.03-LTS-SP3(2.10.0):
52.openEuler-22.03-LTS-SP4(2.10.0):
53.openEuler-24.03-LTS(2.12.1):
54.openEuler-24.03-LTS-Next(2.12.1):
55.openEuler-24.03-LTS-SP1(2.12.1):
56.openEuler-24.03-LTS-SP2(2.12.1):
57.master(2.12.1):
58.openEuler-20.03-LTS-SP4:
59.openEuler-22.03-LTS-SP3(2.10.0):
60.openEuler-22.03-LTS-SP4(2.10.0):
61.openEuler-24.03-LTS(2.12.1):
62.openEuler-24.03-LTS-Next(2.12.1):
63.openEuler-24.03-LTS-SP1(2.12.1):
64.openEuler-24.03-LTS-SP2(2.12.1):
65.master(2.12.1):
66.openEuler-20.03-LTS-SP4:
67.openEuler-22.03-LTS-SP3(2.10.0):
68.openEuler-22.03-LTS-SP4(2.10.0):
69.openEuler-24.03-LTS(2.12.1):
70.openEuler-24.03-LTS-Next(2.12.1):
71.openEuler-24.03-LTS-SP1(2.12.1):
72.openEuler-24.03-LTS-SP2(2.12.1):
73.master(2.12.1):
74.openEuler-20.03-LTS-SP4:
75.openEuler-22.03-LTS-SP3(2.10.0):
76.openEuler-22.03-LTS-SP4(2.10.0):
77.openEuler-24.03-LTS(2.12.1):
78.openEuler-24.03-LTS-Next(2.12.1):
79.openEuler-24.03-LTS-SP1(2.12.1):
80.openEuler-24.03-LTS-SP2(2.12.1):
81.master(2.12.1):
82.openEuler-20.03-LTS-SP4:
83.openEuler-22.03-LTS-SP3(2.10.0):
84.openEuler-22.03-LTS-SP4(2.10.0):
85.openEuler-24.03-LTS(2.12.1):
86.openEuler-24.03-LTS-Next(2.12.1):
87.openEuler-24.03-LTS-SP1(2.12.1):
88.openEuler-24.03-LTS-SP2(2.12.1):
89.master(2.12.1):
90.openEuler-20.03-LTS-SP4:
91.openEuler-22.03-LTS-SP3(2.10.0):
92.master(2.12.1):
原因说明:
1.master(2.12.1):
2.openEuler-20.03-LTS-SP4:
3.openEuler-22.03-LTS-SP3(2.10.0):
4.openEuler-22.03-LTS-SP4(2.10.0):
5.openEuler-24.03-LTS(2.12.1):
6.openEuler-24.03-LTS-Next(2.12.1):
7.openEuler-24.03-LTS-SP1(2.12.1):
8.openEuler-24.03-LTS-SP2(2.12.1):