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Submission Details
Severity: medium
Invalid

`_clampWeights` does not consider values equal to `absoluteMin` and `absoluteMax`

hajime

Vulnerability Details

in the _clampWeights, a code fragment iterates over _weights and applies a restriction based on absoluteMin and absoluteMax, which does not take into account values equal to them, but only those outside the range, but judging by the logic of the iteration itself, this is incorrect.

function _clampWeights(
int256[] memory _weights,
int256 _absoluteWeightGuardRail
) internal pure returns (int256[] memory) {
unchecked {
uint weightLength = _weights.length;
if (weightLength == 1) {
return _weights;
}
int256 absoluteMin = _absoluteWeightGuardRail;
int256 absoluteMax = ONE -
(PRBMathSD59x18.fromInt(int256(_weights.length - 1)).mul(_absoluteWeightGuardRail));
int256 sumRemainerWeight = ONE;
int256 sumOtherWeights;
for (uint i; i < weightLength; ++i) {
if (_weights[i] < absoluteMin) {
_weights[i] = absoluteMin;
sumRemainerWeight -= absoluteMin;
} else if (_weights[i] > absoluteMax) {
_weights[i] = absoluteMax;
sumOtherWeights += absoluteMax;
}
}
if (sumOtherWeights != 0) {
int256 proportionalRemainder = sumRemainerWeight.div(sumOtherWeights);
for (uint i; i < weightLength; ++i) {
if (_weights[i] != absoluteMin) {
_weights[i] = _weights[i].mul(proportionalRemainder);
}
}
}
}
return _weights;
}
​

Values less than absoluteMin are first set to absoluteMin and then subtracted from sumRemainerWeight. This implies that a value already equal to absoluteMin should also be subtracted.

Values greater than absoluteMax are set to absoluteMax and added to sumOtherWeights. This suggests that an existing value of absoluteMax should be added as well.

The code iterates through the _weights array and aims to apply boundaries based on absoluteMin and absoluteMax. The error is that it focuses only on values outside the range, overlooking weights already at the boundaries.

Impact

The incorrect adjustments to sumRemainerWeight and sumOtherWeights directly lead to an imprecise weight distribution. This can skew the results of the algorithm, especially if there are multiple weights at the minimum or maximum values.

Tools Used

Manual

Recommendations

Use <= , >=

Updates

Lead Judging Commences

n0kto Lead Judge 10 months ago
Submission Judgement Published
Validated
Assigned finding tags:

finding_clampWeights_weights_can_be_equal_to_absolute_variables

Likelihood: Low, when a weight is perfectly equal to absoluteMin or absoluteMax. Impact: Low, will skew a bit the results of weights.

Appeal created

n0kto Lead Judge
10 months ago
n0kto Lead Judge 10 months ago
Submission Judgement Published
Invalidated
Reason: Incorrect statement

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