Weakness · High
CWE-1339: Insufficient Precision or Accuracy of a Real Number
What it is
The product processes a real number with an implementation in which the number's representation does not preserve required accuracy and precision in its fractional part, causing an incorrect result.
- Severity (our rating)
- High
- Likelihood of exploit
- Not rated by MITRE
- Introduced during
- Implementation
- Exploited in the wild
- No CVE in CISA's catalog
In more detail
When a security decision or calculation requires highly precise, accurate numbers such as financial calculations or prices, then small variations in the number could be exploited by an attacker. There are multiple ways to store the fractional part of a real number in a computer. In all of these cases, there is a limit to the accuracy of recording a fraction. If the fraction can be represented in a fixed number of digits (binary or decimal), there might not be enough digits assigned to represent the number. In other cases the number cannot be represented in a fixed number of digits due to repeating in decimal or binary notation (e.g. 0.333333...) or due to a transcendental number such as Π or √2. Rounding of numbers can lead to situations where the computer results do not adequately match the result of sufficiently accurate math.
What an attacker can do
- DoS: Crash, Exit, or Restart (Availability)
- Execute Unauthorized Code or Commands (Integrity)
- Read Application Data (Confidentiality, Availability, Access Control)
- Modify Application Data (Confidentiality, Availability, Access Control)
How to prevent it
Implementation
- The developer or maintainer can move to a more accurate representation of real numbers. In extreme cases, the programmer can move to representations such as ratios of BigInts which can represent real numbers to extremely fine precision. The programmer can also use the concept of an Unum real. The memory and CPU tradeoffs of this change must be examined. Since floating point reals are used in many products and many locations, they are implemented in hardware and most format changes will cause the calculations to be moved into software resulting in slower products.
How to find it
- 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.)
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Start freeSource: MITRE Common Weakness Enumeration, CWE version 4.19.1. CWE is a trademark of The MITRE Corporation.