CWE-1339 · Słabość
Insufficient Precision or Accuracy of a Real Number
- Abstrakcja
- Bazowa
- Status
- Szkic
- Dodano
- 8 lipca 2021
- Ostatnia zmiana
- 11 grudnia 2025
Opis
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.
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.
Skutki
Availability
DoS: Crash, Exit, or Restart
This weakness will generally lead to undefined results and therefore crashes. In some implementations the program will halt if the weakness causes an overflow during a calculation.
Integrity
Execute Unauthorized Code or Commands
The results of the math are not as expected. This could cause issues where a value would not be properly calculated and provide an incorrect answer.
Confidentiality, Availability, Access Control
Read Application Data; Modify Application Data
This weakness can sometimes trigger buffer overflows which can be used to execute arbitrary code. This is usually outside the scope of a product's implicit security policy.
Zapobieganie
Implementation, Patching and Maintenance
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.
Przykłady podatności
- CVE-2018-16069 Chain: series of floating-point precision errors (CWE-1339) in a web browser rendering engine causes out-of-bounds read (CWE-125), giving access to cross-origin data
- CVE-2017-7619 Chain: rounding error in floating-point calculations (CWE-1339) in image processor leads to infinite loop (CWE-835)
- CVE-2021-29529 Chain: machine-learning product can have a heap-based buffer overflow (CWE-122) when some integer-oriented bounds are calculated by using ceiling() and floor() on floating point values (CWE-1339)
- CVE-2008-2108 Chain: insufficient precision (CWE-1339) in random-number generator causes some zero bits to be reliably generated, reducing the amount of entropy (CWE-331)
- CVE-2006-6499 Chain: web browser crashes due to infinite loop - "bad looping logic [that relies on] floating point math [CWE-1339] to exit the loop [CWE-835]"
Słabość nadrzędna
Pokrewna
Może prowadzić do
Kiedy powstaje
- Implementation — This weakness is introduced when the developer picks a method to represent a real number. The weakness may only be visible with very specific numeric inputs.
Dotyczy
Not Language-Specific, Not OS-Specific, Not Architecture-Specific, Not Technology-Specific
Źródła
Wpis z katalogu CWE 4.20.