Security Considerations

While it is usually quite easy to build software that works as expected, it is much harder to check that nobody can use it in a way that was not anticipated.

In Solidity, this is even more important because you can use smart contracts to handle tokens or, possibly, even more valuable things. Furthermore, every execution of a smart contract happens in public and, in addition to that, the source code is often available.

Of course you always have to consider how much is at stake: You can compare a smart contract with a web service that is open to the public (and thus, also to malicious actors) and perhaps even open source. If you only store your grocery list on that web service, you might not have to take too much care, but if you manage your bank account using that web service, you should be more careful.

This section will list some pitfalls and general security recommendations but can, of course, never be complete. Also, keep in mind that even if your smart contract code is bug-free, the compiler or the platform itself might have a bug. A list of some publicly known security-relevant bugs of the compiler can be found in the list of known bugs, which is also machine-readable. Note that there is a bug bounty program that covers the code generator of the Solidity compiler.

As always, with open source documentation, please help us extend this section (especially, some examples would not hurt)!

NOTE: In addition to the list below, you can find more security recommendations and best practices in Guy Lando’s knowledge list and the Consensys GitHub repo.


Private Information and Randomness

Everything you use in a smart contract is publicly visible, even local variables and state variables marked private.

Using random numbers in smart contracts is quite tricky if you do not want miners to be able to cheat.


Any interaction from a contract (A) with another contract (B) and any transfer of Ether hands over control to that contract (B). This makes it possible for B to call back into A before this interaction is completed. To give an example, the following code contains a bug (it is just a snippet and not a complete contract):

pragma solidity >=0.4.0 <0.7.0;

contract Fund {
    /// Mapping of ether shares of the contract.
    mapping(address => uint) shares;
    /// Withdraw your share.
    function withdraw() public {
        if (msg.sender.send(shares[msg.sender]))
            shares[msg.sender] = 0;

The problem is not too serious here because of the limited gas as part of send, but it still exposes a weakness: Ether transfer can always include code execution, so the recipient could be a contract that calls back into withdraw. This would let it get multiple refunds and basically retrieve all the Ether in the contract. In particular, the following contract will allow an attacker to refund multiple times as it uses call which forwards all remaining gas by default:

pragma solidity >=0.4.0 <0.7.0;

contract Fund {
    /// Mapping of ether shares of the contract.
    mapping(address => uint) shares;
    /// Withdraw your share.
    function withdraw() public {
        (bool success,) =[msg.sender])("");
        if (success)
            shares[msg.sender] = 0;

To avoid re-entrancy, you can use the Checks-Effects-Interactions pattern as outlined further below:

pragma solidity >=0.4.11 <0.7.0;

contract Fund {
    /// Mapping of ether shares of the contract.
    mapping(address => uint) shares;
    /// Withdraw your share.
    function withdraw() public {
        uint share = shares[msg.sender];
        shares[msg.sender] = 0;

Note that re-entrancy is not only an effect of Ether transfer but of any function call on another contract. Furthermore, you also have to take multi-contract situations into account. A called contract could modify the state of another contract you depend on.

Gas Limit and Loops

Loops that do not have a fixed number of iterations, for example, loops that depend on storage values, have to be used carefully: Due to the block gas limit, transactions can only consume a certain amount of gas. Either explicitly or just due to normal operation, the number of iterations in a loop can grow beyond the block gas limit which can cause the complete contract to be stalled at a certain point. This may not apply to view functions that are only executed to read data from the blockchain. Still, such functions may be called by other contracts as part of on-chain operations and stall those. Please be explicit about such cases in the documentation of your contracts.

Sending and Receiving Ether

  • Neither contracts nor “external accounts” are currently able to prevent that someone sends them Ether. Contracts can react on and reject a regular transfer, but there are ways to move Ether without creating a message call. One way is to simply “mine to” the contract address and the second way is using selfdestruct(x).
  • If a contract receives Ether (without a function being called), either the receive Ether or the fallback function is executed. If it does not have a receive nor a fallback function, the Ether will be rejected (by throwing an exception). During the execution of one of these functions, the contract can only rely on the “gas stipend” it is passed (2300 gas) being available to it at that time. This stipend is not enough to modify storage (do not take this for granted though, the stipend might change with future hard forks). To be sure that your contract can receive Ether in that way, check the gas requirements of the receive and fallback functions (for example in the “details” section in Remix).
  • There is a way to forward more gas to the receiving contract using""). This is essentially the same as addr.transfer(x), only that it forwards all remaining gas and opens up the ability for the recipient to perform more expensive actions (and it returns a failure code instead of automatically propagating the error). This might include calling back into the sending contract or other state changes you might not have thought of. So it allows for great flexibility for honest users but also for malicious actors.
  • Use the most precise units to represent the wei amount as possible, as you lose any that is rounded due to a lack of precision.
  • If you want to send Ether using address.transfer, there are certain details to be aware of:
    1. If the recipient is a contract, it causes its receive or fallback function to be executed which can, in turn, call back the sending contract.
    2. Sending Ether can fail due to the call depth going above 1024. Since the caller is in total control of the call depth, they can force the transfer to fail; take this possibility into account or use send and make sure to always check its return value. Better yet, write your contract using a pattern where the recipient can withdraw Ether instead.
    3. Sending Ether can also fail because the execution of the recipient contract requires more than the allotted amount of gas (explicitly by using require, assert, revert or because the operation is too expensive) - it “runs out of gas” (OOG). If you use transfer or send with a return value check, this might provide a means for the recipient to block progress in the sending contract. Again, the best practice here is to use a “withdraw” pattern instead of a “send” pattern.

Callstack Depth

External function calls can fail any time because they exceed the maximum call stack of 1024. In such situations, Solidity throws an exception. Malicious actors might be able to force the call stack to a high value before they interact with your contract.

Note that .send() does not throw an exception if the call stack is depleted but rather returns false in that case. The low-level functions .call(), .delegatecall() and .staticcall() behave in the same way.


Never use tx.origin for authorization. Let’s say you have a wallet contract like this:

pragma solidity >=0.5.0 <0.7.0;

contract TxUserWallet {
    address owner;

    constructor() public {
        owner = msg.sender;

    function transferTo(address payable dest, uint amount) public {
        require(tx.origin == owner);

Now someone tricks you into sending Ether to the address of this attack wallet:

pragma solidity ^0.6.0;

interface TxUserWallet {
    function transferTo(address payable dest, uint amount) external;

contract TxAttackWallet {
    address payable owner;

    constructor() public {
        owner = msg.sender;

    receive() external payable {
        TxUserWallet(msg.sender).transferTo(owner, msg.sender.balance);

If your wallet had checked msg.sender for authorization, it would get the address of the attack wallet, instead of the owner address. But by checking tx.origin, it gets the original address that kicked off the transaction, which is still the owner address. The attack wallet instantly drains all your funds.

Two’s Complement / Underflows / Overflows

As in many programming languages, Solidity’s integer types are not actually integers. They resemble integers when the values are small, but behave differently if the numbers are larger. For example, the following is true: uint8(255) + uint8(1) == 0. This situation is called an overflow. It occurs when an operation is performed that requires a fixed size variable to store a number (or piece of data) that is outside the range of the variable’s data type. An underflow is the converse situation: uint8(0) - uint8(1) == 255.

In general, read about the limits of two’s complement representation, which even has some more special edge cases for signed numbers.

Try to use require to limit the size of inputs to a reasonable range and use the SMT checker to find potential overflows, or use a library like SafeMath if you want all overflows to cause a revert.

Code such as require((balanceOf[_to] + _value) >= balanceOf[_to]) can also help you check if values are what you expect.

Clearing Mappings

The Solidity type mapping (see Mapping Types) is a storage-only key-value data structure that does not keep track of the keys that were assigned a non-zero value. Because of that, cleaning a mapping without extra information about the written keys is not possible. If a mapping is used as the base type of a dynamic storage array, deleting or popping the array will have no effect over the mapping elements. The same happens, for example, if a mapping is used as the type of a member field of a struct that is the base type of a dynamic storage array. The mapping is also ignored in assignments of structs or arrays containing a mapping.

pragma solidity >=0.5.0 <0.7.0;

contract Map {
    mapping (uint => uint)[] array;

    function allocate(uint _newMaps) public {
        for (uint i = 0; i < _newMaps; i++)

    function writeMap(uint _map, uint _key, uint _value) public {
        array[_map][_key] = _value;

    function readMap(uint _map, uint _key) public view returns (uint) {
        return array[_map][_key];

    function eraseMaps() public {
        delete array;

Consider the example above and the following sequence of calls: allocate(10), writeMap(4, 128, 256). At this point, calling readMap(4, 128) returns 256. If we call eraseMaps, the length of state variable array is zeroed, but since its mapping elements cannot be zeroed, their information stays alive in the contract’s storage. After deleting array, calling allocate(5) allows us to access array[4] again, and calling readMap(4, 128) returns 256 even without another call to writeMap.

If your mapping information must be deleted, consider using a library similar to iterable mapping, allowing you to traverse the keys and delete their values in the appropriate mapping.

Minor Details

  • Types that do not occupy the full 32 bytes might contain “dirty higher order bits”. This is especially important if you access - it poses a malleability risk: You can craft transactions that call a function f(uint8 x) with a raw byte argument of 0xff000001 and with 0x00000001. Both are fed to the contract and both will look like the number 1 as far as x is concerned, but will be different, so if you use keccak256( for anything, you will get different results.


Take Warnings Seriously

If the compiler warns you about something, you should better change it. Even if you do not think that this particular warning has security implications, there might be another issue buried beneath it. Any compiler warning we issue can be silenced by slight changes to the code.

Always use the latest version of the compiler to be notified about all recently introduced warnings.

Restrict the Amount of Ether

Restrict the amount of Ether (or other tokens) that can be stored in a smart contract. If your source code, the compiler or the platform has a bug, these funds may be lost. If you want to limit your loss, limit the amount of Ether.

Keep it Small and Modular

Keep your contracts small and easily understandable. Single out unrelated functionality in other contracts or into libraries. General recommendations about source code quality of course apply: Limit the amount of local variables, the length of functions and so on. Document your functions so that others can see what your intention was and whether it is different than what the code does.

Use the Checks-Effects-Interactions Pattern

Most functions will first perform some checks (who called the function, are the arguments in range, did they send enough Ether, does the person have tokens, etc.). These checks should be done first.

As the second step, if all checks passed, effects to the state variables of the current contract should be made. Interaction with other contracts should be the very last step in any function.

Early contracts delayed some effects and waited for external function calls to return in a non-error state. This is often a serious mistake because of the re-entrancy problem explained above.

Note that, also, calls to known contracts might in turn cause calls to unknown contracts, so it is probably better to just always apply this pattern.

Include a Fail-Safe Mode

While making your system fully decentralised will remove any intermediary, it might be a good idea, especially for new code, to include some kind of fail-safe mechanism:

You can add a function in your smart contract that performs some self-checks like “Has any Ether leaked?”, “Is the sum of the tokens equal to the balance of the contract?” or similar things. Keep in mind that you cannot use too much gas for that, so help through off-chain computations might be needed there.

If the self-check fails, the contract automatically switches into some kind of “failsafe” mode, which, for example, disables most of the features, hands over control to a fixed and trusted third party or just converts the contract into a simple “give me back my money” contract.

Ask for Peer Review

The more people examine a piece of code, the more issues are found. Asking people to review your code also helps as a cross-check to find out whether your code is easy to understand - a very important criterion for good smart contracts.

Formal Verification

Using formal verification, it is possible to perform an automated mathematical proof that your source code fulfills a certain formal specification. The specification is still formal (just as the source code), but usually much simpler.

Note that formal verification itself can only help you understand the difference between what you did (the specification) and how you did it (the actual implementation). You still need to check whether the specification is what you wanted and that you did not miss any unintended effects of it.

Solidity implements a formal verification approach based on SMT solving. The SMTChecker module automatically tries to prove that the code satisfies the specification given by require/assert statements. That is, it considers require statements as assumptions and tries to prove that the conditions inside assert statements are always true. If an assertion failure is found, a counterexample is given to the user, showing how the assertion can be violated.

The SMTChecker also checks automatically for arithmetic underflow/overflow, trivial conditions and unreachable code. It is currently an experimental feature, therefore in order to use it you need to enable it via a pragma directive.

The SMTChecker traverses the Solidity AST creating and collecting program constraints. When it encounters a verification target, an SMT solver is invoked to determine the outcome. If a check fails, the SMTChecker provides specific input values that lead to the failure.

While the SMTChecker encodes Solidity code into SMT constraints, it contains two reasoning engines that use that encoding in different ways.

SMT Encoding

The SMT encoding tries to be as precise as possible, mapping Solidity types and expressions to their closest SMT-LIB representation, as shown in the table below.

Solidity type SMT sort Theories (quantifier-free)
Boolean Bool Bool
intN, uintN, address, bytesN, enum Integer LIA, NIA
array, mapping, bytes, string Array Arrays
other types Integer LIA

Types that are not yet supported are abstracted by a single 256-bit unsigned integer, where their unsupported operations are ignored.

For more details on how the SMT encoding works internally, see the paper SMT-based Verification of Solidity Smart Contracts.

Model Checking Engines

The SMTChecker module implements two different reasoning engines that use the SMT encoding above, a Bounded Model Checker (BMC) and a system of Constrained Horn Clauses (CHC). Both engines are currently under development, and have different characteristics.

Bounded Model Checker (BMC)

The BMC engine analyzes functions in isolation, that is, it does not take the overall behavior of the contract throughout many transactions into account when analyzing each function. Loops are also ignored in this engine at the moment. Internal function calls are inlined as long as they are not recursive, direct or indirectly. External function calls are inlined if possible, and knowledge that is potentially affected by reentrancy is erased.

The characteristics above make BMC easily prone to reporting false positives, but it is also lightweight and should be able to quickly find small local bugs.

Constrained Horn Clauses (CHC)

The Solidity contract’s Control Flow Graph (CFG) is modelled as a system of Horn clauses, where the lifecycle of the contract is represented by a loop that can visit every public/external function non-deterministically. This way, the behavior of the entire contract over an unbounded number of transactions is taken into account when analyzing any function. Loops are fully supported by this engine. Function calls are currently unsupported.

The CHC engine is much more powerful than BMC in terms of what it can prove, and might require more computing resources.

Abstraction and False Positives

The SMTChecker implements abstractions in an incomplete and sound way: If a bug is reported, it might be a false positive introduced by abstractions (due to erasing knowledge or using a non-precise type). If it determines that a verification target is safe, it is indeed safe, that is, there are no false negatives (unless there is a bug in the SMTChecker).

Function calls to the same contract (or base contracts) are inlined when possible, that is, when their implementation is available. Calls to functions in other contracts are not inlined even if their code is available, since we cannot guarantee that the actual deployed code is the same. Complex pure functions are abstracted by an uninterpreted function (UF) over the arguments.

Functions SMT behavior
assert Verification target
require Assumption
internal Inline function call
external Inline function call Erase knowledge about state variables and local storage references
gasleft, blockhash, keccak256, ecrecover ripemd160, addmod, mulmod Abstracted with UF
pure functions without implementation (external or complex) Abstracted with UF
external functions without implementation Unsupported
others Currently unsupported

Using abstraction means loss of precise knowledge, but in many cases it does not mean loss of proving power.

pragma solidity >=0.5.0;
pragma experimental SMTChecker;

contract Recover
    function f(
        bytes32 hash,
        uint8 _v1, uint8 _v2,
        bytes32 _r1, bytes32 _r2,
        bytes32 _s1, bytes32 _s2
    ) public pure returns (address) {
        address a1 = ecrecover(hash, _v1, _r1, _s1);
        require(_v1 == _v2);
        require(_r1 == _r2);
        require(_s1 == _s2);
        address a2 = ecrecover(hash, _v2, _r2, _s2);
        assert(a1 == a2);
        return a1;

In the example above, the SMTChecker is not expressive enough to actually compute ecrecover, but by modelling the function calls as uninterpreted functions we know that the return value is the same when called on equivalent parameters. This is enough to prove that the assertion above is always true.

Abstracting a function call with an UF can be done for functions known to be deterministic, and can be easily done for pure functions. It is however difficult to do this with general external functions, since they might depend on state variables.

External function calls also imply that any current knowledge that the SMTChecker might have regarding mutable state variables needs to be erased to guarantee no false negatives, since the called external function might direct or indirectly call a function in the analyzed contract that changes state variables.

Reference Types and Aliasing

Solidity implements aliasing for reference types with the same data location. That means one variable may be modified through a reference to the same data area. The SMTChecker does not keep track of which references refer to the same data. This implies that whenever a local reference or state variable of reference type is assigned, all knowledge regarding variables of the same type and data location is erased. If the type is nested, the knowledge removal also includes all the prefix base types.

pragma solidity >=0.5.0;
pragma experimental SMTChecker;
// This will report a warning
contract Aliasing
    uint[] array;
    function f(
        uint[] memory a,
        uint[] memory b,
        uint[][] memory c,
        uint[] storage d
    ) internal view {
        require(array[0] == 42);
        require(a[0] == 2);
        require(c[0][0] == 2);
        require(d[0] == 2);
        b[0] = 1;
        // Erasing knowledge about memory references should not
        // erase knowledge about state variables.
        assert(array[0] == 42);
        // Fails because `a == b` is possible.
        assert(a[0] == 2);
        // Fails because `c[i] == b` is possible.
        assert(c[0][0] == 2);
        assert(d[0] == 2);
        assert(b[0] == 1);

After the assignment to b[0], we need to clear knowledge about a since it has the same type (uint[]) and data location (memory). We also need to clear knowledge about c, since its base type is also a uint[] located in memory. This implies that some c[i] could refer to the same data as b or a.

Notice that we do not clear knowledge about array and d because they are located in storage, even though they also have type uint[]. However, if d was assigned, we would need to clear knowledge about array and vice-versa.