When it comes to the industries of blockchain technology and decentralized finance (DeFI), billions of dollars flow through smart contracts daily. These self-executing programs power everything from token transactions to lending platforms. But there’s a problem—too many people assume smart contracts are bulletproof.
Jeremiah O’Connor, Chief Scientist, CTO, and Co-Founder of Trugard Labs, a platform dedicated to detecting and eliminating vulnerabilities in blockchain systems, tells CPOMagazine:
“The biggest misconception is that once deployed, smart contracts are inherently secure,” he continues, “In reality, even minor flaws can cause massive damage.”
Additionally, the damage has been done: devastating hacks like the DAO exploit and other high-profile attacks have proven that the stakes couldn’t be higher.
But why does this keep happening? For one, the rapid pace of development in blockchain leaves little room for rigorous testing. Smart contracts are often deployed quickly, sometimes without thorough audits, in a race to innovate and capture market share. The consequences can be severe.
From Cybersecurity to Blockchain: Addressing a Growing Problem
The idea for Trugard didn’t happen overnight. For its founders, it grew out of years of firsthand experience tackling security challenges.
“I see transaction security as the pinnacle of cybersecurity since it directly targets what attackers value most: financial assets,” explains O’Connor. His time on Binance’s Security Data Science team drove this realization further.
“At Binance, I analyzed the Binance Smart Chain (BSC) to deal with the scams and vulnerabilities we were seeing there. That made it clear: the broader blockchain ecosystem lacked scalable, reliable security tools.”
The problem was not just individual flaws but the sheer scale of smart contracts being deployed. “Manual auditing is slow and can’t keep up. New vulnerabilities are being discovered all the time, and attackers are always looking for the next loophole to exploit.”
This realization sparked a series of conversations with Anoop, a former colleague from Cisco, who shared a similar interest in blockchain security.
“We talked about what was happening in the industry, what we were each seeing at Binance and AWS, and where things were headed. The gaps in blockchain security were too big to ignore. That’s when we decided to take action.”
Together, they built Trugard Labs to address what they describe as a systemic problem: the lack of accessible, automated tools to identify vulnerabilities before they cause damage.
Anoop Nannra, Co-Founder and CEO of Trugard, explained the critical role of smart contracts within blockchain infrastructure, drawing a clear analogy to traditional network systems.
“We consider smart contracts as infrastructure,” he said. “The L1/L2 networks act as pipes responsible for the movement of assets, while contracts serve as the singular controller for the issuance and governance of digital assets.”
Nannra continued, “Once you establish the notion of a controller, it’s easy to draw parallels to IP infrastructure and the role of network controllers, which must be secured, monitored, and protected from hackers and exploits. Simply put, if a hacker discovers or injects an exploit into a network controller, they have the keys to the castle—and it’s no different with smart contracts and digital assets.”
Smart Contract Risks Aren’t Theoretical—They’re Everywhere
The vulnerabilities lurking in smart contracts are well-known but often underestimated.
“Some of the most common issues include Hidden Mint functions, where attackers inflate token supply, or Hidden Balance Updates, which allow arbitrary adjustments to user balances,” O’Connor says. These aren’t isolated risks—they happen far too frequently across the ecosystem.
Take Reentrancy Attacks, for example. These occur when a malicious contract exploits logic gaps to repeatedly call back into a vulnerable contract. “It’s like draining a bucket of water before it’s been fully refilled,” O’Connor explains. “This is what caused the DAO hack, which remains one of the most infamous examples of a smart contract failure.”
Then there are Malicious Boolean Checks, where pause-like functions designed to protect the system can be manipulated. “An attacker can freeze transfers or block allowances, effectively locking user funds,” he adds.
Another critical risk is Library Tampering. Many smart contracts depend on widely trusted libraries like SafeMath. But what happens when someone tweaks the code? “Subtle changes to libraries can introduce vulnerabilities that spread across multiple contracts, sometimes without developers realizing it,” O’Connor notes.
These flaws often hide in plain sight. With thousands of contracts deployed daily, identifying these issues at scale has become a major challenge.
“The volume of code being written today is massive. Without automated tools to spot these flaws, it’s no surprise that so many vulnerabilities slip through,” he says.
Why AI Is Essential for Smart Contract Security
This is where AI and machine learning come in. While traditional audits rely on human expertise, AI enables security assessments to happen faster, at scale, and with greater precision.
“AI allows us to analyze huge datasets, identify patterns, and catch anomalies that might indicate vulnerabilities,” O’Connor explains. Machine learning models, for instance, can flag issues like reentrancy attacks, unchecked external calls, or manipulation of minting functions—and they do it in real-time.
“What sets AI apart is its ability to work with bytecode,” he adds. “Almost all smart contracts are deployed as bytecode, not human-readable code. Without advanced tools, you’re essentially flying blind.”
Trugard’s system employs algorithms like XGBoost and CatBoost, which automate detection and help prioritize risks. Beyond code, the platform monitors blockchain activity to detect suspicious behaviors, like frontrunning or unauthorized balance updates, before they escalate.
A Broader Audience for Smart Contract Security
As blockchain matures, smart contract security is no longer the sole concern of developers. It’s an industry-wide challenge that impacts everyone, from individual users to large enterprises.
DeFi platforms increasingly rely on automated tools to monitor contracts and secure user funds. Centralized exchanges like Binance and Coinbase assess token safety before listing new assets. Wallet providers, like MetaMask and Ledger, are integrating solutions to warn users about risky transactions.
Compliance agencies and forensic investigators are also entering the space. With tools like Trugard, they can analyze transactions, detect fraudulent activity, and track malicious contracts more effectively.
Even individual users stand to benefit. “Most retail users don’t have the expertise to check if a smart contract is safe to interact with. Making security tools accessible can prevent a lot of costly mistakes,” O’Connor says.
Changing the Conversation About Security
Jeremiah O’Connor of Trugard believes that the industry needs a cultural shift in how it approaches security.
“Too often, developers think of smart contracts as ‘set and forget,’” O’Connor explains. “Once the code is live, it’s immutable. But immutability doesn’t mean it’s perfect. If vulnerabilities exist, they’re there forever.”
This misunderstanding has allowed significant risks to go unchecked. Without the right tools to analyze and monitor contracts, vulnerabilities remain invisible—until they’re exploited.
The work being done to secure smart contracts is far from over, but progress is being made. By automating detection and monitoring at scale, tools like Trugard are helping developers, enterprises, and regulators get ahead of the problem.
“It’s not about eliminating every vulnerability—that’s impossible,” O’Connor concludes. “It’s about making blockchain safer step by step and catching risks before they become catastrophic.”
As blockchain adoption continues to grow, the need for smarter, automated security tools will only become more urgent. The risks may not be going away anytime soon, but the industry is starting to shift—from reacting to problems after the fact to proactively preventing them altogether.
