Detail CWE-197

CWE-197

Numeric Truncation Error
2006-07-19
00h00 +00:00
Rendah
Incomplete
2026-10-28
00h00 +00:00
Notifikasi untuk CWE tertentu
Tetap terinformasi tentang perubahan untuk CWE tertentu.
Kelola notifikasi

Nama: Numeric Truncation Error

Truncation errors occur when a primitive is cast to a primitive of a smaller size and data is lost in the conversion.

Informasi Umum

Mode Pengenalan

Implementation : While truncation may be employed viably to isolate the low bits of a value, this usage is rare, and truncation usually implies that an implementation error has occurred.

Platform yang Berlaku

Bahasa

Nama: C (Undetermined)
Nama: C++ (Undetermined)
Nama: Java (Undetermined)
Nama: C# (Undetermined)
Nama: Python (Undetermined)

Konsekuensi Umum

Cakupan Dampak Kemungkinan
IntegrityModify Memory, Varies by Context

Catatan: When a primitive is cast to a smaller primitive, the high order bits of the large value are lost in the conversion, potentially resulting in an unexpected value that is not equal to the original value. This value may be required as an index into a buffer, a loop iterator, or simply necessary state data. In any case, the value cannot be trusted and the system will be in an undefined state.

Contoh yang Diamati

Referensi Deskripsi

CVE-2020-17087

Chain: integer truncation (CWE-197) causes small buffer allocation (CWE-131) leading to out-of-bounds write (CWE-787) in kernel pool, as exploited in the wild per CISA KEV.

CVE-2009-0231

Integer truncation of length value leads to heap-based buffer overflow.

CVE-2008-3282

Size of a particular type changes for 64-bit platforms, leading to an integer truncation in document processor causes incorrect index to be generated.

Mitigasi yang Memungkinkan

Phases : Implementation
Ensure that no casts, implicit or explicit, take place that move from a larger size primitive or a smaller size primitive.

Metode Deteksi

Fuzzing

Fuzz testing (fuzzing) is a powerful technique for generating large numbers of diverse inputs - either randomly or algorithmically - and dynamically invoking the code with those inputs. Even with random inputs, it is often capable of generating unexpected results such as crashes, memory corruption, or resource consumption. Fuzzing effectively produces repeatable test cases that clearly indicate bugs, which helps developers to diagnose the issues.
Efektivitas : High

Automated Static Analysis

Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)
Efektivitas : High

Catatan Pemetaan Kerentanan

Justifikasi : This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.
Komentar : Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.

Catatan

This weakness has traditionally been under-studied and under-reported, although vulnerabilities in popular software have been published in 2008 and 2009.

Referensi

REF-62

The Art of Software Security Assessment
Mark Dowd, John McDonald, Justin Schuh.

REF-1534

Automated Technical Debt Measure, Version 2
OMG.
https://www.omg.org/spec/ATDM2/1.0/PDF

REF-1541

Secure Coding Guide for Python
OpenSSF.
https://best.openssf.org/Secure-Coding-Guide-for-Python/

Pengajuan

Nama Organisasi Tanggal Tanggal rilis Version
PLOVER 2006-07-19 +00:00 2006-07-19 +00:00 Draft 3

Modifikasi

Nama Organisasi Tanggal Komentar
CWE Content Team MITRE 2008-09-08 +00:00 updated Applicable_Platforms, Common_Consequences, Relationships, Other_Notes, Taxonomy_Mappings
CWE Content Team MITRE 2008-11-24 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2009-05-27 +00:00 updated Demonstrative_Examples
CWE Content Team MITRE 2009-07-27 +00:00 updated Description, Observed_Examples, Other_Notes, Research_Gaps
CWE Content Team MITRE 2010-12-13 +00:00 updated Demonstrative_Examples
CWE Content Team MITRE 2011-06-01 +00:00 updated Common_Consequences, Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2011-09-13 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2012-05-11 +00:00 updated References, Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2014-07-30 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2017-11-08 +00:00 updated Taxonomy_Mappings
CWE Content Team MITRE 2019-01-03 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2020-02-24 +00:00 updated Relationships
CWE Content Team MITRE 2020-08-20 +00:00 updated Relationships
CWE Content Team MITRE 2020-12-10 +00:00 updated Relationships
CWE Content Team MITRE 2022-06-28 +00:00 updated Observed_Examples
CWE Content Team MITRE 2023-04-27 +00:00 updated Detection_Factors, Relationships
CWE Content Team MITRE 2023-06-29 +00:00 updated Mapping_Notes
CWE Content Team MITRE 2025-12-11 +00:00 updated Weakness_Ordinalities
CWE Content Team MITRE 2026-10-28 +00:00 updated Applicable_Platforms, Common_Consequences, Demonstrative_Examples, Description, Modes_of_Introduction, References, Relationships, Taxonomy_Mappings