AI Tools Are Generating Massive Attacks for Little Cost

One campaign targets 105 sites using open-weight models; in another, public models gained full domain control for $12. Cyber-defense will have to change.

Over five days in September, a Chinese-speaking attacker used three different AI harnesses and both open-weight and public AI models to target 105 different e-commerce sites.

Often within a day, and at most within hours, the autonomous hacking system compromised at least 27 different companies. Malicious agents stole at least 600,000 payment card records from two, installed credit-card skimmers on the websites of five, and gained some degree of illicit access to the rest, which includes at least one Fortune 500 company, according to Gambit Security, which discovered the campaign.

The total bill for the attackers? An average of $25.46 per completed target.

“The scale and success of this campaign are remarkable for just one week, especially considering the size of some of the victims,” says Sa’ar Elias, co-founder and chief research officer for Gambit Security. “Work that would previously have required a coordinated team of skilled attackers can now be carried out by one person without much prior knowledge.”

The autonomous credit-card and data-stealing campaign is not an outlier. Agentic AI has sped up vulnerability research, leading to a massive surge in CVE assignments. Attackers are increasingly using AI to automate attacks, exploit systems faster, and even act as fully autonomous hackers.

In another instance, researchers with AI cyber-defense firm Silverfort conduct lab tests using an orchestrating agent and publicly available versions of Claude Opus to explore how quickly autonomous AI can turn initial access into a full compromise. The “attacker” gained complete domain control in eight minutes, says Colin Ferris, threat hunting and incident response lead at Silverfort.

The total cost: About $12.

“The barrier to entry is falling,” Ferris says. “What it takes is a basic foothold, not exotic skill, and that’s why this won’t stay confined to sophisticated actors.”

Security Teams Looking for Cheap Defenses

Prices in dark markets have reflected the reduction in costs for attackers. Because of increasing supply in the underground markets, the average price of sold initial access declined from just over $1,400 to $429, according to figures from threat intelligence firm Flashpoint. While fewer companies are paying ransoms — 28% in the first half of 2026 — ransomware activity continued to grow by 45%, the company said.

“Initial access is where we’ve measured the price drop,” says Ian Gray, vice president of intelligence for Flashpoint. “Elsewhere in the attack chain, we see AI making operations faster and easier to scale.”

In many ways, the situation resembles the one on current battlefields: Cheap autonomous or directed attacks by drones are making expensive defenses uneconomical, which means that defenders have to find cheaper ways to defend and harden systems. In the latest campaign, cyberattackers used the agentic AI system Hermes and two AI penetration-testing frameworks, Strix and Cairn, according to Gambit Security.

“Attackers can now launch increasingly sophisticated attacks at very low marginal costs, while defenders must maintain a high level of reliability across complex environments,” says Gambit Security’s Elias. “Defending against every individual attempt can quickly become an unsustainable economic proposition.”

Applying AI to existing security processes will be necessary, but not enough, he says. Instead, companies need to look at their business processes, determine which ones matter most, and find ways to protect them and prevent disruption.

No Place to Hide From AI

For the past two decades, cybersecurity experts have warned that companies can’t expect to avoid attacks simply because they are in an obscure business or have a relatively small attack surface. Every part of a company that is attached to the Internet or connected to a partner connected to the Internet will be attacked, says Albert Ziegler, chief information security officer at offensive cybersecurity firm XBOW.

“These are not incredibly expensive attacks, but also these are attacks that work because the sites haven’t been hardened enough,” he says. “It’s that it’s not enough to protect a couple of crown jewel sites that you are very concerned about.”

One way to bolster defenses is to focus on the basic paths that AI agents tend to exploit — overprivileged accounts, reused credentials, and unmanaged service accounts — and automate access decisions, so humans do not slow down responses, Silverfort’s Ferris says. When Silverfort researchers improved controls, especially authentication and access, the same agent that took the domain in minutes hit 21 dead ends and gave up, he says.

“AI didn’t create these weaknesses; it just finds them faster,” Ferris says. “Controls that stop the attack at the point of access are cheaper than cleanup afterwards.”

Companies should focus on the economics of recovering from an attack and how to protect their minimum viable business processes, says Gambit Security’s Elias. Business leaders should focus on what investments will have the most business impact.

Unfortunately, that may mean budgets need to grow to adapt to the economics of AI, he says. However, “spending should increasingly be measured by how effectively it protects business operations,” he notes, “rather than simply how many threats or tools a security program can manage.”