2507.05558v3.pdf
How does A1 work?🛠
First, the tool loads the contract code: its ABI (an interface that describes which functions can be called) and up-to-date blockchain data: balances, transactions, and network status. This is important because the vulnerability may depend on the number of tokens on the contract or recent transactions.
Then the system analyzes the code🔎: it examines the structure, functions, and variables, and looks for suspicious places. For example, A1 may detect a function that does not check the caller, or logic that allows the function to be called again before the state is updated.
When a vulnerability is found, the fun begins: A1 creates an exploit✏️
Let's say she discovered reentrancy. A1 then generates an attacking smart contract that invokes the vulnerable function in a loop.
This code is being tested in a blockchain simulation, for example, on a local Ethereum node, to see if the attack will work. If the attack is successful, A1 estimates the profit: how many tokens or ether can be withdrawn and how this correlates with gas costs.
If the result is positive, the exploit is saved as a proof-of-concept, a ready-made example of an attack🧪
However, A1 is not limited to one scenario. If the analysis reveals a suspicious function, the system tries different ways of operation: it changes parameters, the order of calls, and combines functions. If the attack did not work, A1 searches for the cause and tests a different approach.
The article states that A1 found vulnerabilities in real contracts that were missed by tools like Mythril and Slither. She even identified bugs that required complex attacks, such as manipulating oracles or using flash credits💸
In general, for those who want to dig even deeper, take a look at the article there is code, examples of attacks and details, for example, how A1 works with EVM ❤️
#smart_contract #crypto #crypto_protection #attacks #pentest #explication #neural_networks
First, the tool loads the contract code: its ABI (an interface that describes which functions can be called) and up-to-date blockchain data: balances, transactions, and network status. This is important because the vulnerability may depend on the number of tokens on the contract or recent transactions.
Then the system analyzes the code🔎: it examines the structure, functions, and variables, and looks for suspicious places. For example, A1 may detect a function that does not check the caller, or logic that allows the function to be called again before the state is updated.
When a vulnerability is found, the fun begins: A1 creates an exploit✏️
Let's say she discovered reentrancy. A1 then generates an attacking smart contract that invokes the vulnerable function in a loop.
This code is being tested in a blockchain simulation, for example, on a local Ethereum node, to see if the attack will work. If the attack is successful, A1 estimates the profit: how many tokens or ether can be withdrawn and how this correlates with gas costs.
If the result is positive, the exploit is saved as a proof-of-concept, a ready-made example of an attack🧪
However, A1 is not limited to one scenario. If the analysis reveals a suspicious function, the system tries different ways of operation: it changes parameters, the order of calls, and combines functions. If the attack did not work, A1 searches for the cause and tests a different approach.
The article states that A1 found vulnerabilities in real contracts that were missed by tools like Mythril and Slither. She even identified bugs that required complex attacks, such as manipulating oracles or using flash credits💸
In general, for those who want to dig even deeper, take a look at the article there is code, examples of attacks and details, for example, how A1 works with EVM ❤️
#smart_contract #crypto #crypto_protection #attacks #pentest #explication #neural_networks