What is the CVSS score of CVE-2021-37690?

CVE-2021-37690 has a CVSS 3.1 base score of 6.6 (Medium). CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H. EPSS exploitation probability: 0.2%.

Is there a patch available for CVE-2021-37690?

Yes, a patch is available for CVE-2021-37690. Update the affected software to the latest version immediately.

Tensorflow CVE-2021-37690

MEDIUM

Use After Free (CWE-416)

2021-08-13 security-advisories@github.com

Information Disclosure Google Use After Free Memory Corruption Tensorflow

6.6

CVSS 3.1 · NVD

View

Vulnerability Assessment

Weakness	CWE CWE-416 ASVS 5.0 V15 - Secure Coding and Architecture Memory lifecycle management MITRE ATT&CK 2 techniques across 2 tactics: Execution, Privilege Escalation The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. Sign in to read
Impact	CVSS score of 6.6 (MEDIUM). Attack characteristics: local attack vector, low complexity, low privileges required, no user interaction not required.
Exploit ScenarioDerived	A local attacker with access to the system could access freed memory to execute arbitrary code or crash the application.

This Month Plan within 30 days. Why: MEDIUM severity (CVSS 4.0-6.9).

Patch available 0.2% exploitation probability (EPSS)

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AnalysisAI

TensorFlow is an end-to-end open source platform for machine learning. Rated medium severity (CVSS 6.6), this vulnerability is low attack complexity. This Use After Free vulnerability could allow attackers to access freed memory to execute arbitrary code or crash the application.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Use smart pointers or garbage-collected languages. Set pointers to NULL after freeing. Enable memory sanitizers.

Affected Packages

pypi tensorflow fix: 2.3.4, 2.4.3, 2.5.1

pypi tensorflow-cpu fix: 2.3.4, 2.4.3, 2.5.1

pypi tensorflow-gpu fix: 2.3.4, 2.4.3, 2.5.1

Source: OSV (Open Source Vulnerabilities)

Affects your stack

Affects 3 packages in pypi

Checking this CVE against your own stacks and servers is part of the Basic plan and up.

Technical ContextAI · show details

This vulnerability is classified as Use After Free (CWE-416), which allows attackers to access freed memory to execute arbitrary code or crash the application. TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as MutableHashTableShape) produce extra output information in the form of a ShapeAndType struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. ShapeRefiner is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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. Affected products include: Google Tensorflow.

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Severity by source

NVD PRIMARY 6.6 MEDIUM

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

Attack Vector

Local

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

Low

Integrity

Low

Availability

High

DescriptionNVD

TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as MutableHashTableShape) produce extra output information in the form of a ShapeAndType struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. ShapeRefiner is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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.

Blast Radius

ecosystem impact

† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth

43 pypi packages depend on tensorflow (41 direct, 2 indirect)
4 pypi packages depend on tensorflow-gpu (4 direct, 0 indirect)

Ecosystem-wide dependent count for version 2.4.0 and other introduced versions.

Threat Intelligence Overview

EPSS Score

0.2%

Top 94% exploitable

Data Quality

3 sources

Confidence: Low

NVD

CVE.org

EPSS

GitHub

How this decision was reached

The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.

SignalValue

Severity MEDIUM

CISA KEV No

Public POC No

EPSS 0.2%

Patch available Yes

Active threat No

Deciding rule

MEDIUM severity (CVSS 4.0-6.9)

What every action level means

Emergency Immediate action required. Criteria: CRITICAL + in CISA KEV (actively exploited) without patch, OR CRITICAL + EPSS > 30% without patch, OR CRITICAL + active threat signals without patch.

Act Now Prioritize within 24-48h. Criteria: in KEV with patch available, OR CRITICAL + public POC, OR HIGH + EPSS > 10%, OR CRITICAL + active threat, OR any CRITICAL severity.

This Week Schedule remediation this week. Criteria: HIGH severity (CVSS 7.0-8.9). Patch within normal change window.

This Month Plan within 30 days. Criteria: MEDIUM severity (CVSS 4.0-6.9), lower exploitation probability. Include in regular patch cycle.

Monitor Track and reassess. Criteria: LOW severity (CVSS 0.1-3.9), minimal exploitation risk. No immediate action needed.

SSVC AssessmentENISA

SSVC Decision· derived

Defer

Exploitation· derived

None

System Exposure· derived

Small

Automatable· derived

Human Impact· derived

Medium

Priority Score

Low Medium High Critical

KEV: 0

EPSS: 0

CVSS: +33

PoC: 0

Weaponized: 0

Threat intel: 0

Gov advisory: 0

Attack Technique

Use After Free HIGH

Use-after-free vulnerabilities occur when a program continues to access memory through a pointer after that memory has been deallocated.

Memory Corruption HIGH

Memory corruption occurs when a program writes data beyond the boundaries of allocated memory regions or accesses memory in unintended ways, violating the integrity of the process's address space.

Information Disclosure MEDIUM

Information disclosure occurs when an application unintentionally exposes sensitive data that aids attackers in reconnaissance or directly compromises security.