Vulnerability CVE-2021-29591

Vulnerability Name:

CVE-2021-29591 (CCN-201901)

Assigned:

2021-05-12

Published:

2021-05-12

Updated:

2022-04-25

Summary:

TensorFlow is an end-to-end open source platform for machine learning. TFlite graphs must not have loops between nodes. However, this condition was not checked and an attacker could craft models that would result in infinite loop during evaluation. In certain cases, the infinite loop would be replaced by stack overflow due to too many recursive calls. For example, the `While` implementation(https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc) could be tricked into a scneario where both the body and the loop subgraphs are the same. Evaluating one of the subgraphs means calling the `Eval` function for the other and this quickly exhaust all stack space. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. Please consult our security guide(https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

CVSS v3 Severity:

7.8 High (CVSS v3.1 Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H)
6.8 Medium (Temporal CVSS v3.1 Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H/E:U/RL:O/RC:C)

Exploitability Metrics:	Attack Vector (AV): Local Attack Complexity (AC): Low Privileges Required (PR): Low User Interaction (UI): None
Scope:	Scope (S): Unchanged
Impact Metrics:	Confidentiality (C): High Integrity (I): High Availibility (A): High

7.3 High (CCN CVSS v3.1 Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H)
6.4 Medium (CCN Temporal CVSS v3.1 Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H/E:U/RL:O/RC:C)

Exploitability Metrics:	Attack Vector (AV): Local Attack Complexity (AC): Low Privileges Required (PR): Low User Interaction (UI): None
Scope:	Scope (S): Unchanged
Impact Metrics:	Confidentiality (C): High Integrity (I): Low Availibility (A): High

CVSS v2 Severity:

4.6 Medium (CVSS v2 Vector: AV:L/AC:L/Au:N/C:P/I:P/A:P)

Exploitability Metrics:	Access Vector (AV): Local Access Complexity (AC): Low Authentication (Au): None
Impact Metrics:	Confidentiality (C): Partial Integrity (I): Partial Availibility (A): Partial

6.4 Medium (CCN CVSS v2 Vector: AV:L/AC:L/Au:S/C:C/I:P/A:C)

Exploitability Metrics:	Access Vector (AV): Local Access Complexity (AC): Low Athentication (Au): Single_Instance
Impact Metrics:	Confidentiality (C): Complete Integrity (I): Partial Availibility (A): Complete

Vulnerability Type:

CWE-674
CWE-835

Vulnerability Consequences:

Gain Access

References:

Source: MITRE
Type: CNA
CVE-2021-29591

Source: XF
Type: UNKNOWN
tensorflow-cve202129591-bo(201901)

Source: MISC
Type: Patch, Third Party Advisory
https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743

Source: MISC
Type: Patch, Third Party Advisory
https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4

Source: CCN
Type: TensorFlow GIT Repository
Stack overflow due to looping TFLite subgraph

Source: CONFIRM
Type: Exploit, Patch, Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cwv3-863g-39vx

Source: CCN
Type: IBM Security Bulletin 6486007 (Watson Machine Learning on CP4D)
Multiple TensorFlow Vulnerabilities Affect IBM Watson Machine Learning on CP4D

Vulnerable Configuration:

Configuration 1:

cpe:/a:google:tensorflow:*:*:*:*:*:*:*:* (Version < 2.1.4)

OR cpe:/a:google:tensorflow:*:*:*:*:*:*:*:* (Version >= 2.2.0 and < 2.2.3)

OR cpe:/a:google:tensorflow:*:*:*:*:*:*:*:* (Version >= 2.3.0 and < 2.3.3)

OR cpe:/a:google:tensorflow:*:*:*:*:*:*:*:* (Version >= 2.4.0 and < 2.4.2)

Configuration CCN 1:

cpe:/a:google:tensorflow:2.4.2:*:*:*:*:*:*:*

Denotes that component is vulnerable

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