CWE-197: Numeric Truncation Error
CWE版本: 4.18
更新日期: 2025-09-09
弱点描述
Truncation errors occur when a primitive is cast to a primitive of a smaller size and data is lost in the conversion.
扩展描述
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. While this method 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.
常见后果
影响范围: Integrity
技术影响: Modify Memory
说明: The true value of the data is lost and corrupted data is used.
潜在缓解措施
阶段: Implementation
描述: Ensure that no casts, implicit or explicit, take place that move from a larger size primitive or a smaller size primitive.
检测方法
方法: 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.
有效性: High
方法: 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.)
有效性: High
观察示例
参考: 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.
参考: CVE-2009-0231
Integer truncation of length value leads to heap-based buffer overflow.
参考: 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.
引入模式
| 阶段 | 说明 |
|---|---|
| Implementation | - |
适用平台
编程语言
分类映射
| 分类名称 | 条目ID | 条目名称 | 映射适配度 |
|---|---|---|---|
| PLOVER | - | Numeric truncation error | - |
| CLASP | - | Truncation error | - |
| CERT C Secure Coding | FIO34-C | Distinguish between characters read from a file and EOF or WEOF | CWE More Abstract |
| CERT C Secure Coding | FLP34-C | Ensure that floating point conversions are within range of the new type | CWE More Abstract |
| CERT C Secure Coding | INT02-C | Understand integer conversion rules | - |
| CERT C Secure Coding | INT05-C | Do not use input functions to convert character data if they cannot handle all possible inputs | - |
| CERT C Secure Coding | INT31-C | Ensure that integer conversions do not result in lost or misinterpreted data | CWE More Abstract |
| The CERT Oracle Secure Coding Standard for Java (2011) | NUM12-J | Ensure conversions of numeric types to narrower types do not result in lost or misinterpreted data | - |
| Software Fault Patterns | SFP1 | Glitch in computation | - |