Conversations about AI in smart contract auditing have been on the rise. There is no doubt AI will play an increasingly important role in smart contract security. Nevertheless, while AI is already enhancing the efficiency and effectiveness of smart contract auditing, there are also risks associated with relying too heavily on AI when auditing Web3 projects. 

Let's explore pros and cons of using AI in smart contract auditing. 

Pros of using AI in smart contract auditing

Automated Code Analysis

AI-powered tools can analyze smart contract code to identify potential vulnerabilities and security risks. These tools use machine learning algorithms to detect patterns of common security issues, such as reentrancy bugs, unchecked external calls, and overflows/underflows.

By automating the code analysis process, AI can help auditors identify potential issues more quickly and efficiently. One of the notable AI companies able to provide automated code analysis is SolidityScan. 

Natural Language Processing (NLP)

NLP techniques can be used to analyze smart contract documentation, whitepapers, and other textual resources to extract information relevant to the auditing process.

For example, NLP algorithms can extract requirements, specifications, and business logic from written documentation. This information consequently can be used to make the auditing process more efficient. NLP can also help auditors understand the intended functionality of a smart contract and identify potential discrepancies between the code and its documentation.

Predictive Analysis

AI algorithms can analyze historical data on smart contract vulnerabilities and security incidents to identify trends and patterns. By analyzing past audit reports, security advisories, and exploit data, AI can help auditors anticipate potential security risks. Predictive analysis can also help auditors stay ahead of emerging threats and vulnerabilities.

Continuous Monitoring

AI-powered tools can provide continuous monitoring of smart contracts deployed on blockchain networks.

These tools can automatically detect and alert auditors to suspicious activity or potential security breaches in real-time. This way AI can help auditors identify and respond to security threats more proactively, reducing the risk of exploits. Chainlink's AI-powered tools, for instance, continuously analyze the behavior of smart contracts on the blockchain.

Cons of using AI in smart contract auditing

Yes, with all its benefits, AI-powered tools aren't meant to replace manual smart contract audits.

They are here to complement auditors' and developers' work. Let's explore potential risks if we rely too heavily on AI when auditing smart contracts.

• AI-powered tools may produce false positives. That is, there's a possibility of AI identifying issues that are not actually vulnerabilities. 

• AI algorithms may lack the ability to fully understand the context and intent behind smart contract code. While they can identify patterns indicative of common security vulnerabilities, they may struggle to recognize more subtle or complex issues that require a deeper understanding of the underlying blockchain platform, protocol, or industry domain.

• AI-powered auditing tools may be susceptible to adversarial attacks. In this case, malicious actors can manipulate input data to trick the algorithms into producing incorrect results. 

• AI models rely on training data to learn patterns and make predictions. If the training data is biased, incomplete, or outdated, the AI model may produce inaccurate or unreliable results.

Conclusions

AI-powered tools should complement smart contract auditing, not replace manual audits. 

Manual audits are essential for validating AI-generated findings and addressing complex security issues. Moreover, auditors should continuously evaluate and update AI models to ensure they remain effective in detecting security threats as they constantly evolve.

While AI-powered tools have the potential to augment auditors' capabilities and enhance the security of blockchain-based systems and applications, human expertise and oversight will remain essential.

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Audita's Team