Attacker Value
Unknown
(0 users assessed)
Exploitability
Unknown
(0 users assessed)
User Interaction
None
Privileges Required
None
Attack Vector
Network
0

CVE-2020-15202

Disclosure Date: September 25, 2020
Add MITRE ATT&CK tactics and techniques that apply to this CVE.

Description

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.

Add Assessment

No one has assessed this topic. Be the first to add your voice to the community.

CVSS V3 Severity and Metrics
Base Score:
9.0 Critical
Impact Score:
6
Exploitability Score:
2.2
Vector:
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
Attack Vector (AV):
Network
Attack Complexity (AC):
High
Privileges Required (PR):
None
User Interaction (UI):
None
Scope (S):
Changed
Confidentiality (C):
High
Integrity (I):
High
Availability (A):
High

General Information

Technical Analysis