Tensorflow
CVE-2020-15202
CRITICAL
Vulnerability Assessment
| Weakness |
CWE
ASVS 5.0
V15 - Secure Coding and Architecture Numeric truncation prevention
|
| Impact | CVSS score of 9.0 (CRITICAL). Attack characteristics: network attack vector, high complexity, no privileges required, no user interaction not required. Public proof-of-concept exploit code is available. |
| Exploit ScenarioDerived | This vulnerability can be exploited remotely over the network. Successful exploitation could compromise the critical-severity affected system. |
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Alert meAnalysisAI
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the Shard API in TensorFlow expects the last argument to be a function taking two int64 (i.e., long long) arguments. Rated critical severity (CVSS 9.0), this vulnerability is remotely exploitable, no authentication required. Public exploit code available.
RemediationAI
A vendor patch is available. Apply the latest security update as soon as possible. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 3 packages in pypi
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Technical ContextAI · show details
This vulnerability is classified under CWE-197. In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the Shard API in TensorFlow expects the last argument to be a function taking two int64 (i.e., long long) arguments. However, there are several places in TensorFlow where a lambda taking int or int32 arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. Affected products include: Google Tensorflow, Opensuse Leap.
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Severity by source
AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
DescriptionNVD
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the Shard API in TensorFlow expects the last argument to be a function taking two int64 (i.e., long long) arguments. However, there are several places in TensorFlow where a lambda taking int or int32 arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Blast Radius
ecosystem impact- 40 pypi packages depend on tensorflow (38 direct, 2 indirect)
- 11 pypi packages depend on tensorflow-gpu (11 direct, 0 indirect)
Ecosystem-wide dependent count for version 2.0.0 and other introduced versions.
Threat Intelligence Overview
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.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
A buffer overflow occurs when a program writes more data to a memory buffer than it was allocated to hold, causing the excess data to spill into adjacent memory regions.
Affected Products (CPE)NVD
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