Arbitrum Hacks in 2023

Karolina

06 Oct 2023
Arbitrum Hacks in 2023

The innovations brought about by decentralized platforms promise a new era of finance and applications. Yet, as with any emergent technology, vulnerabilities and risks are unearthed, especially in the early stages. 2023 has borne witness to a series of security breaches, particularly on the Arbitrum network. This article dives deep into these breaches, shedding light on the incidents and understanding their implications, it shows some hacks on the Arbitrum network.

What is Arbitrum?

Arbitrum, an exciting and innovative off-chain scaling solution, has captured significant attention in the crypto world. Designed to optimize Ethereum, it stands out due to its ability to reduce transaction costs while simultaneously increasing the speed of transaction processing. At its core, Arbitrum utilizes "rollups," which bundle or "roll" multiple transactions into a single one, thereby offering a more efficient way to process high volumes of transactions.

The rise of decentralized applications (dApps) and DeFi platforms requires scalable solutions, and Arbitrum offers precisely that. Its mechanism allows developers to create smart contracts in a secure environment without compromising on the decentralized principles that underpin the Ethereum network. This breakthrough has led to a growing number of projects choosing Arbitrum as their preferred network.

However, with greater adoption comes greater scrutiny, and the network has faced its fair share of challenges in 2023. As we delve deeper into this year's Arbitrum hacks, it's essential to understand the foundational role the network plays in the larger blockchain ecosystem and why its security is of utmost importance.

A Turbulent Year for Arbitrum Security - Arbitrum Hacks

Security challenges have never been more pertinent than in 2023 with the Arbitrum network finding itself embroiled in a series of significant hacks. These security breaches have not only resulted in substantial financial losses but have also raised questions about the security standards of protocols built on this layer.

The Rodeo Finance Exploit - Jul 11, 2023

Rodeo Finance, a DeFi protocol on the Arbitrum Network, suffered a loss of 472 Ether, amounting to approximately $888,000.

The security breach was made public by blockchain security company PeckShield, which traced the path of the stolen funds. It was found that the hacker had transferred the looted Ether from Arbitrum to Ethereum.

By leveraging the Oracle manipulation technique, the hacker could alter price feeds, thereby exploiting the platform for nearly a million dollars worth of crypto.

This technique involved feeding incorrect data from off-chain resources into smart contracts. By manipulating this data, hackers could mislead the smart contract into undesired actions, in this case, transferring a substantial amount of Ether.

The aftermath saw the hacker cleverly masking their activities. They exchanged the stolen assets for various tokens, eventually converting them back to Ether. This Ether was then routed through Tornado Cash, a cryptocurrency mixer, further obfuscating the fund's origins.

In the immediate aftermath, Rodeo Finance's token value plummeted, registering a 65% decline in just an hour.

Read More About This Hack HERE

The Jimbos Protocol Hack - May 28, 2023

Jimbos, a recently launched decentralized crypto protocol on Arbitrum, encountered a security breach that led to the theft of 4,090 Ether, approximately valued at $7.7 million.

The hacker exploited a "slippage" issue, a term referring to the variance between a trade's expected price and the actual execution price. While slippage typically results from large trades or liquidity mismatches, in Jimbos' case, it was an absence of control measures against excessive slippage that was the culprit.

The hacker managed to manipulate the protocol's liquidity at distorted prices, eventually extracting 4,090 Ether through a reverse swap mechanism.

As a result, the native token of Jimbos, JIMBO, suffered a severe hit, losing around 40% of its value overnight.

Read More About This Hack HERE

Sentiment's Million Dollar Heist - April 5, 2023

Sentiment, another DeFi protocol on Arbitrum, lost almost $1 million to hackers. In a bid to retrieve the stolen funds, the protocol's developers announced a 10% recovery bounty, offering $95,000 to anyone aiding in the funds' return.

The hack was attributed to a "read-only reentrancy" bug, previously identified by smart contract auditor ChainSecurity. This type of vulnerability allows hackers to continuously drain funds by repeatedly invoking a smart contract's withdrawal function.

It was later unveiled that the attacker leveraged this bug to manipulate an integration between Sentiment and the decentralized exchange Balancer, thereby tricking the protocol into releasing almost $1 million in various assets, including USDC, USDT, Bitcoin, and Ether.

Read More About This Hack HERE

The Massive Phishing Scheme and Airdrop Theft - March 31 & 25, 2023

On March 31, over a million Arbitrum tokens (ARB) were pilfered. Two wallets were primarily involved in this theft, converting a substantial number of ARB tokens to Ethereum. The connection between these wallets, if any, remains uncertain.

Close on the heels of this incident, on March 25, hackers made away with $500,000 worth of tokens intended for Arbitrum's airdrop. They achieved this by exploiting vanity addresses, which are personalized crypto addresses.

By generating similar vanity addresses, the attackers redirected the airdropped tokens to their own wallets, rendering the original owners powerless.

Although vanity addresses can provide a unique personal touch to one's crypto holdings, they pose considerable security risks, particularly when generated through potentially insecure platforms.

In the context of these breaches, it's also noteworthy that according to a report from the bug bounty platform Immunefi, there's been a 63% surge in hacks across various blockchains in the second quarter of 2023 compared to the previous year. With DeFi platforms incurring losses of $228 million in just this quarter, the Arbitrum breaches are a small, yet significant fraction of a much larger problem plaguing the crypto world.

Read More About This Hacks HERE and HERE

Lessons and Moving Forward

Security breaches, while detrimental, offer invaluable lessons for both developers and users in the decentralized landscape. The series of hacks on the Arbitrum network in 2023 reiterates the need for vigilance and proactive measures. Here's what can be gleaned from the unfortunate events:

  • Robust Smart Contract Audits. While many projects undergo smart contract audits, the presence of exploitable bugs like the "read-only reentrancy" in Sentiment suggests the need for more comprehensive and rigorous checks.
  • Advanced Oracle Security. The Rodeo Finance incident underlines the importance of securing oracles against manipulations. Developers need to explore advanced mechanisms to ensure the authenticity of data fed into smart contracts.
  • User Education and Vigilance. The vanity address exploit during the Arbitrum airdrop highlights that users themselves can sometimes be vulnerabilities. Educational initiatives can help users avoid pitfalls and adopt best practices.
  • Adaptive Security Measures. The crypto landscape evolves at a breakneck pace. Protocols need to implement adaptive security mechanisms that can adjust to new threats and vulnerabilities as they emerge.
  • Community Collaboration. Open-source collaboration and global community feedback can help in identifying potential threats and vulnerabilities before they are exploited.

Conclusion

The Arbitrum hacks of 2023 stand as a stark reminder of the challenges and vulnerabilities inherent in the world of decentralized finance and applications.

However, every challenge presents an opportunity. The crypto community's resilience is evident in its ability to rally together, learn from these setbacks, and continuously work towards creating a more secure and trustworthy ecosystem. As we look forward, it's essential to strike a balance between rapid innovation and the safety of protocols and users.

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!