2025 Cryptocurrency Security Turning Point: How Trust Chains and Databases Become the New Battleground

2025 should have marked a new chapter in the history of cryptographic technological innovation, but it ultimately went down as the “worst year” in security history. However, what is more worth noting is the true face behind this crisis — it reveals an ironic paradox in the crypto ecosystem: on-chain code defenses are becoming stronger and stronger, yet overall losses continue to rise. This new contradiction points to a long-ignored reality: the problem is not with the blockchain itself, but with the people, processes, and trust relationships surrounding it.

According to the just-released 2026 Crypto Crime Report by on-chain analysis platform Chainalysis, approximately $1.7 billion in crypto assets flowed into the hands of criminals in 2025. But this huge sum did not come from smart contract vulnerabilities or protocol-level code flaws; instead, it stemmed from stolen passwords, manipulated employees, impersonated support staff, and fake identities — these are pure Web2-style failures.

Mitchell Amador, CEO of the on-chain security platform Immunefi, was straightforward in an interview: “Although 2025 was the worst recorded year for hacking, these hacking incidents originated from Web2 operational failures, not on-chain code issues.” This distinction is crucial because it reveals an counterintuitive truth: precisely because on-chain security has improved, criminals are forced to adjust their strategies and target easier prey — humans themselves.

Breaking the Scam Defense Line: Individuals as New Attack Targets

Behind this shift is a set of alarming data. Identity impersonation scams increased by 1,400% over the past year, becoming the fastest-growing threat category. Meanwhile, AI-driven fraud methods have a success rate 450% higher than traditional scams. What does this mean? Criminal groups are abandoning complex attacks that require deep technical knowledge, instead adopting large-scale, automated fraud activities directly targeting individuals’ wallets and assets.

Recent cases highlight the danger of this trend. Blockchain researcher ZachXBT disclosed a social engineering attack where hackers stole $282 million worth of crypto assets — including 2.05 million Litecoin and 1,459 Bitcoin. The victims were not technically “hacked” but were cleverly deceived, leading to asset loss. The stolen funds were then converted into privacy coins like Monero and laundered through various channels.

Such incidents are not isolated. Chainalysis data shows that fraud and scams targeting individuals and institutions have surpassed traditional infrastructure hacking as the main threat vectors. Attackers no longer need to deeply research protocol vulnerabilities or find flaws in smart contracts; they only need a phone call, a forged message, or a fake website. This “low-tech, high-success-rate” mode is rapidly expanding its victim scale.

Chainalysis Data Reveals: Impersonation and AI Fraud Offensives

From the perspective of data relationship networks, this shift reflects the fragility of trust structures in the crypto ecosystem. When identity verification, communication channels, and user education break down, the entire system is exposed to new risks.

According to detailed analysis by Chainalysis, fraud related to AI has yielded much higher profits over the past 12 months compared to conventional scams. This indicates that criminals are widely adopting generative AI for phishing, fake customer service dialogues, and synthetic identity deception. AI enables a fraud team to target thousands of victims simultaneously, not just a single target. It’s an automated, large-scale crime.

Even more concerning is the extremely low barrier to entry for these new fraud tools. Anyone with basic technical knowledge can rent ready-made AI tools to carry out scams. In contrast, discovering and exploiting on-chain code vulnerabilities requires years of expertise and significant resource investment. The criminal economy has changed.

New Vulnerabilities of AI Agents: Security Risks of On-Chain Autonomous Systems

But concerns about the future run even deeper. Mitchell Amador raised an unsettling point: “By 2026, AI will change the pace in both camps of the security war. Defenders will rely on AI-powered speed for monitoring and response, while attackers will also use the same tools for vulnerability research, exploit development, and large-scale social engineering.”

More presciently, he warned about the new risks posed by on-chain AI agents. As more systems in the crypto ecosystem adopt autonomous AI agents for trading, fund management, and protocol governance, a whole new attack surface emerges. “This opens up new attack vectors,” Amador said. “The operation speed and capabilities of on-chain AI agents surpass human operators, but if their access paths or control layers are compromised, they will create unique vulnerabilities.”

This is a rarely discussed but critically important topic in crypto security. When intelligent systems begin autonomously managing on-chain assets, the threats they face are entirely different from traditional smart contracts. Traditional contracts are static code; AI agents are dynamic, learning, and potentially manipulable. “We are still in the early stages of learning how to properly protect these agents,” Amador added. “This will become one of the biggest security challenges in the next cycle.”

Industry Defense Status: A Clear Skills Gap

Despite these warnings, the defense posture of the crypto industry remains sluggish. Amador disclosed a disheartening set of data: over 90% of projects still have exploitable critical vulnerabilities. Even more shocking, even though defensive tools are widely available, most projects have not adopted them. Less than 1% of the industry employs firewalls, and fewer than 10% deploy AI-driven threat detection systems.

What does this mean? The vast majority of crypto projects are far from best practices in technical defense, let alone investing in personnel training, process security, and information protection. This widespread defensive lag further exacerbates the trend of human factors becoming the main threat vector.

A Paradigm Shift in Security

Returning to Mitchell Amador’s initial observation: crypto security is undergoing a profound paradigm shift. On-chain code is becoming increasingly difficult to exploit, which should be good news. But it also means that any security improvements are offset by the evolution of attack methods. Attackers are no longer competing with defenders over code but are dealing with humans.

The impact of this shift is far-reaching. Future crypto security will not primarily be decided at the blockchain layer but will unfold in user interfaces, enterprise processes, monitoring systems, and education. It concerns every link in the trust chain — from employee security awareness to user authentication, from wallet access controls to proxy system authorization management.

The lesson of 2025 is clear: in an ecosystem where on-chain defenses are becoming increasingly robust, humans and processes remain the weakest links. And with the rise of AI agents, the complexity and risks of this battlefield will further increase. For the entire industry, shifting focus from code vulnerabilities to constructively thinking about how to protect personnel, processes, and AI system integrity is no longer an option but an imperative.