Mass deployment of AI agents is a disaster waiting to happen, says CertiK CEO

The global rush to deploy autonomous AI agents across the internet, enterprise networks and consumer applications is creating a catastrophic security debt, according to the chief of blockchain security auditor Certik.

While corporations ambitiously market these tools as productivity miracles, the crude reality is that it can be a very, very risky thing to do. Unisolated, unvetted AI agents are a massive security disaster waiting to happen, Ronghui Gu, the co-founder and CEO of CertiK, told CoinDesk.

Gu warned that users are potentially exposing their most sensitive files, local credentials and money accounts to autonomous systems that can be easily manipulated, hijacked and openly scammed.

“Right now, agents are no longer just answering questions in a chat window,” Gu told CoinDesk on the heels of CertiK’s landmark deep-dive report into widespread agent infrastructure. “They are beginning to call external tools, read local files, trigger workflows, and interact with financial infrastructure. But if you do not isolate the execution environment and scan these tools first, you are handing a compromised identity broad internal access to your entire network.”

The fundamental flaw in the current AI agent boom is a mistaken trust model, according to Gu.

Charles Hoskinson, founder and CEO of Cardano’s Input Output, said that by 2035 they will become more relevant than humans on the internet. Coinbase CEO Brian Armstrong, recently said “very soon there are going to be more AI agents than humans making transactions” and Binance Founder Changpeng Zhao, predicted they “will make one million times more payments than humans.”

Gu said many popular, open-source AI applications are built under the assumption that because they run locally on a user’s computer or connect via standard chat apps like WhatsApp, they are safe from external threats.

The reality is entirely the opposite, he noted. The moment a user grants an AI agent permission to read local system storage, view execution histories or manage personal email and business database credentials, that agent becomes the ultimate inside threat.

CertiK’s recent analysis of early-state, rapidly growing agent structures uncovered a staggering accumulation of security vulnerabilities, including hundreds of critical security advisories, unpatched common vulnerabilities and exposures (CVEs) and other massive exposures of local credentials and session memories resulting from completely inconsistent boundary checks.

More alarming yet is how easily these autonomous systems can be completely redirected at the reasoning layer without a single line of malicious code ever being written, Gu emphasized.

Through basic “prompt injection” attacks, a bad actor can embed hidden natural language instructions inside a benign webpage, a PDF document, or an incoming email, he added.

When the unisolated AI agent reads that file to process a task for the user, it fails to separate trusted system commands from the untrusted external data, Gu explained. The agent then silently overwrites its original rules, obeys the malicious instruction, and can be forced to exfiltrate data or trigger unauthorized fund transfers.

Gu revealed that CertiK discovered hundreds of malicious skills, fake installers, and lookalike dependency packages sitting directly on open agent utility hubs. Because these malicious plug-ins use standard natural language to subtly influence the agent’s behavior and change its goals, they completely bypass legacy, signature-based antivirus software.

“The scam apps use natural language to influence behavior, making them totally resistant to traditional antivirus scans,” Gu explained. “And right now, it is even easier to scam the machine than it is to scam a human.”

In what Gu describes as a bizarre evolution of financial crime, CertiK’s telemetry has observed an explosion of onchain, automated scams that run for only 10 minutes or a few hours before completely vanishing.

These hyperfast, ephemeral exploits are specifically designed by hackers to target and scam other autonomous AI trading bots and automated agent systems, executing machine-on-machine financial drainage before any human even realizes a compromise has occurred.

Gu states that the software engineering industry must completely abandon its reliance on trust-based interactions and move immediately toward an isolated, “Zero Trust” architecture where every command and dependency is continuously verified.