
ICS 206–01: The New Standard Every OSINT Professional Must Know
Explore ICS 206–01: Essential updates for OSINT pros on AI citations, sourcing rules, retention, and a checklist for seamless compliance.What is an Intelligence Community Standard?A new directive, the Intelligence Community Standard (ICS), has just been released, offering a framework designed to ensure consistency, accuracy, and professionalism across the U.S. Intelligence Community (IC). ICS directives provide clear guidelines for processes, methodologies, and workflows, enabling intelligenc...

Point-and-Click OSINT: Dark Web Scraping with GUI Tools
Discover how to gather OSINT data from the dark web without coding. Learn point-and-click scraping tools, techniques, & essential privacy tips. This article is also published on my Medium page. You guys seemed to have enjoyed the last article — Python, dark web OSINT, the whole nine yards! Setting up those scripts, digging into the code… it’s the kind of stuff that makes a cybersecurity geek’s heart sing. But hey, I get it — not everyone wants to get their hands quite so dirty with code. A fe...

Python for Dark Web OSINT: Automate Threat Monitoring
Enhance your OSINT toolkit! Learn how to use Python to automate monitoring of dark web forums, leak sites, and marketplaces for actionable threat intelligence. This article is also published on my Medium page. In my previous article, “OSINT: Persistent Threat Monitoring with Google Programmable Search Engines,” I explored the value of open-source intelligence (OSINT) techniques for tracking threats. Since then, I’ve received many questions about how to apply similar methods to the dark web. W...
Writing about blockchain security and blockchain forensics. Follow me on Twitter for the latest insights.



ICS 206–01: The New Standard Every OSINT Professional Must Know
Explore ICS 206–01: Essential updates for OSINT pros on AI citations, sourcing rules, retention, and a checklist for seamless compliance.What is an Intelligence Community Standard?A new directive, the Intelligence Community Standard (ICS), has just been released, offering a framework designed to ensure consistency, accuracy, and professionalism across the U.S. Intelligence Community (IC). ICS directives provide clear guidelines for processes, methodologies, and workflows, enabling intelligenc...

Point-and-Click OSINT: Dark Web Scraping with GUI Tools
Discover how to gather OSINT data from the dark web without coding. Learn point-and-click scraping tools, techniques, & essential privacy tips. This article is also published on my Medium page. You guys seemed to have enjoyed the last article — Python, dark web OSINT, the whole nine yards! Setting up those scripts, digging into the code… it’s the kind of stuff that makes a cybersecurity geek’s heart sing. But hey, I get it — not everyone wants to get their hands quite so dirty with code. A fe...

Python for Dark Web OSINT: Automate Threat Monitoring
Enhance your OSINT toolkit! Learn how to use Python to automate monitoring of dark web forums, leak sites, and marketplaces for actionable threat intelligence. This article is also published on my Medium page. In my previous article, “OSINT: Persistent Threat Monitoring with Google Programmable Search Engines,” I explored the value of open-source intelligence (OSINT) techniques for tracking threats. Since then, I’ve received many questions about how to apply similar methods to the dark web. W...
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Writing about blockchain security and blockchain forensics. Follow me on Twitter for the latest insights.

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AuditGPT employs cutting-edge AI to identify smart contract vulnerabilities that standard tools miss. Enhance your blockchain project’s security.
You can also find this article on my Medium page.
In the ever-evolving world of blockchain technology, verifying smart contracts presents a significant challenge. Why? Once deployed, they’re immutable. This review dives into “AuditGPT: Auditing Smart Contracts with ChatGPT,” a 2024 paper by Shihao Xia and colleagues from prestigious institutions. They’ve crafted AuditGPT, a cutting-edge tool that revolutionizes the Ethereum smart contract auditing process by harnessing the power of large language models (LLMs).
AuditGPT emerges in response to the limitations of existing manual and automated smart contract auditing methods, which often fall short in efficiency and thoroughness. The core of the research revolves around the automated verification of Ethereum Request for Comment (ERC) standards, which govern the behavior of smart contracts on the Ethereum platform. The tool specifically addresses ERC compliance through a novel application of LLMs.
The researchers’ methodology involves an empirical study of 222 ERC rules across four popular ERC standards, leading to a deep understanding of these rules’ specifications and their implementations in the Solidity programming language. AuditGPT operates in two phases: a startup phase for rule extraction and a working phase for individual contract inspection. This approach ensures targeted and efficient rule verification by breaking down complex contracts into manageable segments.
Key findings from the evaluation of AuditGPT indicate a high success rate in identifying ERC rule violations. The tool detected a significant number of violations, including several with potential high-security impacts, and demonstrated substantial improvements in cost and time efficiency compared to traditional human auditing services.

AuditGPT represents a significant advancement in smart contract auditing with its ability to effectively break down and analyze individual rules. One of its strengths lies in its modular approach, which allows for focused auditing of specific ERC rules, a methodology that enhances accuracy and efficiency. However, the research also notes limitations such as restricted testing to only three ERC standards and potential underperformance in more complex contract scenarios. This limitation suggests room for further refinement and testing across a broader range of contracts and ERC rules.
While the tool reduces false positives significantly, the challenge of interpreting complex contract semantics remains an area for potential improvement. The reliance on the correctness and comprehensiveness of the extracted rules for its operation also poses risks if the initial rule extraction phase is not sufficiently accurate.
The most surprising aspect of AuditGPT? Its pioneering use of LLMs in the complex world of smart contract auditing. Traditionally, this field has been dominated by manual processes and simpler automated tools, which often overlook nuanced violations. The introduction of LLMs to interpret and enforce ERC rules marks a revolutionary shift. This approach not only boosts the detection of subtle rule violations but also slashes auditing times from hours to mere minutes.
While the AuditGPT discussed in the article is distinct, you might find the ChatGPT smart contract audit plugin interesting to explore in the meantime. Here’s the link to give it a try.
The implications of AuditGPT are profound for the field of blockchain technology. This tool automates the auditing process, delivering both high accuracy and efficiency. Could it become a standard in the smart contract development and deployment pipeline? Quite possibly. In doing so, it would ensure enhanced security and compliance with established standards. Looking ahead, future research could broaden AuditGPT’s scope to encompass more ERC standards. Additionally, it could be integrated with real-time deployment processes, offering predictive insights about potential contract vulnerabilities before they’re ever exploited.
“AuditGPT: Auditing Smart Contracts with ChatGPT” provides compelling evidence of the viability and benefits of using LLMs for smart contract auditing. This tool sets a new benchmark in the field and prompts further exploration into integrating artificial intelligence technologies within blockchain frameworks. The research invites stakeholders in the blockchain ecosystem to reconsider the current methodologies of smart contract auditing and to embrace more advanced, efficient, and reliable tools like AuditGPT.
Can ChatGPT Revolutionize Smart Contract Auditing? Unveiling AI’s Potential in Blockchain Security
Discover how blockchain is transforming industries on the Blockchain Insights Hub. Follow me on Twitter for real-time updates on the intersection of blockchain and cybersecurity. Subscribe now to get my exclusive report on the top blockchain security threats of 2024. Dive deeper into my blockchain insights on Medium.
AuditGPT employs cutting-edge AI to identify smart contract vulnerabilities that standard tools miss. Enhance your blockchain project’s security.
You can also find this article on my Medium page.
In the ever-evolving world of blockchain technology, verifying smart contracts presents a significant challenge. Why? Once deployed, they’re immutable. This review dives into “AuditGPT: Auditing Smart Contracts with ChatGPT,” a 2024 paper by Shihao Xia and colleagues from prestigious institutions. They’ve crafted AuditGPT, a cutting-edge tool that revolutionizes the Ethereum smart contract auditing process by harnessing the power of large language models (LLMs).
AuditGPT emerges in response to the limitations of existing manual and automated smart contract auditing methods, which often fall short in efficiency and thoroughness. The core of the research revolves around the automated verification of Ethereum Request for Comment (ERC) standards, which govern the behavior of smart contracts on the Ethereum platform. The tool specifically addresses ERC compliance through a novel application of LLMs.
The researchers’ methodology involves an empirical study of 222 ERC rules across four popular ERC standards, leading to a deep understanding of these rules’ specifications and their implementations in the Solidity programming language. AuditGPT operates in two phases: a startup phase for rule extraction and a working phase for individual contract inspection. This approach ensures targeted and efficient rule verification by breaking down complex contracts into manageable segments.
Key findings from the evaluation of AuditGPT indicate a high success rate in identifying ERC rule violations. The tool detected a significant number of violations, including several with potential high-security impacts, and demonstrated substantial improvements in cost and time efficiency compared to traditional human auditing services.

AuditGPT represents a significant advancement in smart contract auditing with its ability to effectively break down and analyze individual rules. One of its strengths lies in its modular approach, which allows for focused auditing of specific ERC rules, a methodology that enhances accuracy and efficiency. However, the research also notes limitations such as restricted testing to only three ERC standards and potential underperformance in more complex contract scenarios. This limitation suggests room for further refinement and testing across a broader range of contracts and ERC rules.
While the tool reduces false positives significantly, the challenge of interpreting complex contract semantics remains an area for potential improvement. The reliance on the correctness and comprehensiveness of the extracted rules for its operation also poses risks if the initial rule extraction phase is not sufficiently accurate.
The most surprising aspect of AuditGPT? Its pioneering use of LLMs in the complex world of smart contract auditing. Traditionally, this field has been dominated by manual processes and simpler automated tools, which often overlook nuanced violations. The introduction of LLMs to interpret and enforce ERC rules marks a revolutionary shift. This approach not only boosts the detection of subtle rule violations but also slashes auditing times from hours to mere minutes.
While the AuditGPT discussed in the article is distinct, you might find the ChatGPT smart contract audit plugin interesting to explore in the meantime. Here’s the link to give it a try.
The implications of AuditGPT are profound for the field of blockchain technology. This tool automates the auditing process, delivering both high accuracy and efficiency. Could it become a standard in the smart contract development and deployment pipeline? Quite possibly. In doing so, it would ensure enhanced security and compliance with established standards. Looking ahead, future research could broaden AuditGPT’s scope to encompass more ERC standards. Additionally, it could be integrated with real-time deployment processes, offering predictive insights about potential contract vulnerabilities before they’re ever exploited.
“AuditGPT: Auditing Smart Contracts with ChatGPT” provides compelling evidence of the viability and benefits of using LLMs for smart contract auditing. This tool sets a new benchmark in the field and prompts further exploration into integrating artificial intelligence technologies within blockchain frameworks. The research invites stakeholders in the blockchain ecosystem to reconsider the current methodologies of smart contract auditing and to embrace more advanced, efficient, and reliable tools like AuditGPT.
Can ChatGPT Revolutionize Smart Contract Auditing? Unveiling AI’s Potential in Blockchain Security
Discover how blockchain is transforming industries on the Blockchain Insights Hub. Follow me on Twitter for real-time updates on the intersection of blockchain and cybersecurity. Subscribe now to get my exclusive report on the top blockchain security threats of 2024. Dive deeper into my blockchain insights on Medium.
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