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CVE-2021-29544
已完成
#I3SCB5
CVE和安全问题
openeuler-ci-bot
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创建于
2021-05-21 11:44
一、漏洞信息 漏洞编号:[CVE-2021-29544](https://nvd.nist.gov/vuln/detail/CVE-2021-29544) 漏洞归属组件:tensorflow 漏洞归属的版本:2.3.1 CVSS V3.0分值: BaseScore:5.5 Medium Vector:CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H 漏洞简述: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306). However, the `vec<T>` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version. 漏洞公开时间:2021-05-14 漏洞创建时间:2021-05-21 11:44:39 漏洞详情参考链接: https://nvd.nist.gov/vuln/detail/CVE-2021-29544 漏洞分析指导链接: https://gitee.com/openeuler/cve-manager/blob/master/doc/md/manual.md 二、漏洞分析结构反馈 影响性分析说明: TensorFlow 是一个端到端的机器学习开源平台。攻击者可以通过 `tf.raw_ops.QuantizeAndDequantizeV4Grad` 中的 `CHECK`-fail 触发拒绝服务。这是因为实现(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163. 反过来,这会导致张量按原样传递给 `QuantizeAndDequantizePerChannelGradientImpl`(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/quantize_kerand.0L3/quantize_2L3_6Lh/quantize_kernelsh/。但是,`vec<T>` 方法要求等级为 1,否则会触发 `CHECK` 失败。该修复将包含在 TensorFlow 2.5.0 中。 openEuler评分: 5.5 Vector:CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H 受影响版本排查(受影响/不受影响): 1.master(2.3.1):受影响 2.openEuler-21.03(2.3.1):受影响 3.openEuler-21.09(2.3.1):受影响 修复是否涉及abi变化(是/否): 1.master(2.3.1):否 2.openEuler-21.03(2.3.1):否 3.openEuler-21.09(2.3.1):否
一、漏洞信息 漏洞编号:[CVE-2021-29544](https://nvd.nist.gov/vuln/detail/CVE-2021-29544) 漏洞归属组件:tensorflow 漏洞归属的版本:2.3.1 CVSS V3.0分值: BaseScore:5.5 Medium Vector:CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H 漏洞简述: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306). However, the `vec<T>` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version. 漏洞公开时间:2021-05-14 漏洞创建时间:2021-05-21 11:44:39 漏洞详情参考链接: https://nvd.nist.gov/vuln/detail/CVE-2021-29544 漏洞分析指导链接: https://gitee.com/openeuler/cve-manager/blob/master/doc/md/manual.md 二、漏洞分析结构反馈 影响性分析说明: TensorFlow 是一个端到端的机器学习开源平台。攻击者可以通过 `tf.raw_ops.QuantizeAndDequantizeV4Grad` 中的 `CHECK`-fail 触发拒绝服务。这是因为实现(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163. 反过来,这会导致张量按原样传递给 `QuantizeAndDequantizePerChannelGradientImpl`(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/quantize_kerand.0L3/quantize_2L3_6Lh/quantize_kernelsh/。但是,`vec<T>` 方法要求等级为 1,否则会触发 `CHECK` 失败。该修复将包含在 TensorFlow 2.5.0 中。 openEuler评分: 5.5 Vector:CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H 受影响版本排查(受影响/不受影响): 1.master(2.3.1):受影响 2.openEuler-21.03(2.3.1):受影响 3.openEuler-21.09(2.3.1):受影响 修复是否涉及abi变化(是/否): 1.master(2.3.1):否 2.openEuler-21.03(2.3.1):否 3.openEuler-21.09(2.3.1):否
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