Floating-point numbers can take on two kinds of exceptional values, infinity
and NaN
(not-a-number). These values are produced as a result of exceptional or otherwise unresolvable floating point operations. Additionally, they may be obtained directly from user input through methods like Double.valueOf(String s)
. Failure to detect and handle such values can result in inconsistent behavior.
NaN
values are particularly problematic because the expression NaN == NaN
always returns false
(See FLP02-J. Do not attempt comparisons with NaN). In general, any comparisons with NaN
return false
, and all arithmetic functions on NaN
inputs simply propagate the taint throughout the code. Just one occurrence of a NaN
value can effectuate regressions within other code segments.
The method Double.valueOf(String s)
can return NaN
or an infinite double
as specified by its contract. Programs should install checks to ensure that all floating point inputs (especially those obtained from the user) do not contain either of these values before proceeding to operate on them. The methods Double.isNaN(double d)
and Double.isInfinite(double d)
can be used for this purpose.
Noncompliant Code Example
This noncompliant code example accepts user data without validating it.
double currentBalance; // User's cash balance void doDeposit(String userInput){ double val; try { val = Double.valueOf(userInput); } catch(NumberFormatException e) { // Handle input format error } if(val >= Double.MAX_VALUE - currentBalance) { // Handle range error } currentBalance += val; }
This can be a problem if an invalid value is entered for val
and subsequently used in calculations or as control values. The user could, for example, input the strings infinity
or NaN
on the command line, which would be parsed by Double.valueOf(String s)
into the floating-point representations of either infinity
or NaN
. All subsequent calculations using these values would be invalid, possibly causing runtime exceptions or enabling denial of service (DoS) attacks.
In this compliant solution, entering NaN
for val
would force currentBalance
to also equal NaN
, corrupting its value. If this value is used in other expressions, every resulting value will become NaN
, possibly corrupting important data.
Compliant Solution
This compliant solution validates the floating point input before using it. The value is tested to ensure that it is neither infinity
, negative infinity
nor NaN
.
double currentBalance; // User's cash balance void doDeposit(String s){ double val; try { val = Double.valueOf(userInput); } catch(NumberFormatException e) { // Handle input format error } if (Double.isInfinite(val)){ // Handle infinity error } if (Double.isNaN(val)) { // Handle NaN error } if(val >= Double.MAX_VALUE - currentBalance) { // Handle range error } currentBalance += val; }
Exceptions
EX1: Occasionally, NaN
or infinity may be acceptable as expected inputs to a program. In such cases, explicit checks may not be necessary. However, such programs must be prepared to handle these inputs gracefully and should not allow the propagation of taint to other values by using them in mathematical expressions where they are inappropriate.
Risk Assessment
Incorrect or missing validation of floating point input can result in miscalculations and unexpected results, possibly leading to inconsistent program behavior and Denial of Service (DoS).
Recommendation |
Severity |
Likelihood |
Remediation Cost |
Priority |
Level |
---|---|---|---|---|---|
FLP06- J |
low |
probable |
medium |
P4 |
L3 |
Automated Detection
TODO
Related Vulnerabilities
Other Languages
This rule appears in the C Secure Coding Standard as FLP04-C. Check floating point inputs for exceptional values
This rule appears in the C++ Secure Coding Standard as FLP04-CPP. Check floating point inputs for exceptional values.
References
[IEEE 754]
[IEEE 1003.1, 2004]
FLP04-J. Use the strictfp modifier for floating point calculation consistency 07. Floating Point (FLP) FLP07-J. Do not use floating point variables as loop counters