5 key vulnerabilities of smart contracts

What is a smart contract?

A smart contract is a sort of code that makes it simple and automatic to verify and carry out a contract. It has been discussed how to hire outside agents to carry out the strategy, but it is obvious that this represents a significant paradigm shift for the commercial sector. These contracts operate on the blockchain and don't require any prior human involvement to validate and uphold the terms.

Some pertinent use cases can be found in loan agreements, where smart contracts enable the debtor to immediately revoke access to funds in the event that the debtor fails to make the agreed-upon interest or installment payments. Smart contracts enable data verification and the application of insurance contract provisions while preventing potential conflicts.

However, creating a solid smart contract is challenging. Its ability to represent value, transparency, and immutability are three of its key characteristics. These characteristics, however, also make them a security risk and a very desirable target for cybercriminals. There are several instances of capital collapse and corporate losses caused by certain vulnerabilities, even when there is no intentional attack.

They might therefore have a propensity to be vulnerable in particular ways. In this essay, we'll go over the top five issues that frequently arise.

1-Integer arithmetic mistake

The integer arithmetic error is a very typical error. Because they don't support floating point, smart contracts often display values as integers.

It is necessary to reduce the value to a lower unit in order to allow for appropriate precision when using whole numbers to describe values (which is typical in financial systems). Since it would be impossible to express 0.5 dollars in dollars, the simplest example is to state the value in cents. In fact, several coins already support 18 decimal digits, greatly improving the correctness of smart contracts.

The potential for integer overflow is one issue that developers nowadays are aware of.

The integers represented in the computer also have a maximum value, and whenever this number is achieved, they simply go back to the beginning and start from the minimum value. This is similar to how a car's mileage is expressed. An extremely high number will result from subtracting 4 from 3 in an unsigned integer, which will also overflow. This possible issue, which can be prevented by utilizing a secure math library, is frequently known to developers.

But many programmers don't appear to understand the lack of accuracy that results from improper integer arithmetic. The calculation of percentages is a common example where the order of operations is crucial. For instance, to find 25%, we typically multiply it by 25 and divide it by 100.

Let's say we just want to calculate 25% of 80 using whole numbers. When expressed as 80/100 * 25, there will be a rounding mistake and the answer will be 0. Here, there is a minor problem in that the division came before the multiplication.

Despite being a pretty minor error, it serves as an illustration of something that commonly occurs.

2- Block gas limit vulnerabilities

With the help of the block gas limit, Ethereum controls how big the block can get. This merely indicates that there is a cap on the gas that transactions contained in these blocks may use. In other words, if a transaction uses too much gas, it won't ever run into problems and won't ever complete.

This may result in a typical vulnerability: The transaction can quickly exhaust and roll back if data is stored in resizable arrays and then accessed by looping across these arrays. This occurs when the number of components in the assembly rises, which often happens during production rather than testing.

Because the test dataset is typically less than the production dataset, this vulnerability is extremely serious even though the affected contracts typically pass unit testing and function well with few users. However, they will fail as the project advances and the volume of data rises. When employing regular payments in this situation, it may have an impact on the money, making their recovery impossible.

3-Frontrunning

This is a consequence of the blockchain's transparency and might be characterized as the occupation of unconfirmed transactions.

Before the miners add them to the block, all pending transactions are available in the memory pool, where interested parties may easily check their contents and "advance" the transaction by making a larger payment.

This is highly frequent in decentralized financial systems and is simple to automate.

To tackle these kinds of issues, substantial refactoring or redesign are frequently necessary.

4. Lack of prerequisite controls or parameters

Another simple but frequent programming error is failing to validate function parameters or neglecting to do the appropriate tests to ensure that an action is valid. Typically, this pertains to address parameters that are not checked against address zero or, for example, whether an unauthenticated user has sufficient token balance to carry out a particular operation. Another excellent illustration is access control, where only specific user categories ought to be permitted to call a specific function, but this verification is never carried out.

These mistakes frequently come from a design process oversight. For all functions, it is a good practice to have textual instructions that list the inputs, prerequisites, and actions to take. A design pattern such as Check-Effect-Interaction should always be followed to avoid this kind of vulnerability.

5 logic errors

The four things mentioned above are more geared towards smart contracts, but there are still other things that are fundamental to programming. The most frequent issue, though, is typically a simple mistake in the smart contract's logic. These mistakes, which have a significant impact on security, can be the result of simple typographical errors or specification ambiguities.

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