For months, OpenAI’s agent swarms have been attacking online databases to find obscure facts

“We found a large quantity of automated activity that had close ties and overlap with the DSE Wiki dataset, and that now OpenAI has confirmed is at least partially part of the same swarm,” Conrad Stosz, the head of governance at Transluce, told TechCrunch, while noting that not every activity they spotted could be linked to OpenAI, or even AI agents generally.

However, the wiki shows that the agents were tasked with finding a fairly obscure fact — the average annual cost per person for “dermatologicals” in the state of Victoria in January 2022. On June 20, urlquery.net records found by Transluce showed an agent attempting to get into the site. In wiki entry on June 21, an agent discusses their inability to bypass AIHW’s anti-bot protections.

The researchers who identified that forum believe a human OpenAI employee first visited the site on that same day, June 21. Most agentic activity on the forum ceased the next day. This was also shortly after the exploit of Australia’s healthcare system revealed by Albanese took place, on June 18. OpenAI has said it did not learn about that activity until August.

OpenAI didn’t answer questions about when its employees discovered the wiki forum, what kind of information they obtained from it, or what they could have learned from it about the exploits.

“Our initial review suggests that much of the activity described in Transluce’s report overlaps with cases at varying stages of investigation in our ongoing review of misaligned model activity,” an OpenAI spokesperson told TechCrunch. “We’ve reached out to the University of New Mexico and Data USA and have been in communication with the Australian government about affected government websites. In our broader review, we’re continuing to prioritize the most serious incidents while expanding our work to lower-severity activity, including agents spamming websites. Given the scale of this work and the need to verify each case, we expect the review to take months.”

Stosz says that without a clearer understanding of how OpenAI monitors its agents, it would be hard to say what the lab should have known about them, but that “it seems likely that if they had exhaustively studied and understood all of the outgoing requests and incoming responses for those agents involved in the DSE wiki, that they would have discovered this activity.”

Selena Zhang, a member of Transluce’s technical staff who contributed to the report, said that urlquery.net records show requests for similar data sets, using similar techniques, in March 2026, and perhaps as early as November 2025. She noted that the same kind of agent-associated activity has taken place on urlquery.net as recently as this week.

Stosz, who previously led the U.S. Center for AI Standards and Innovation, said Transluce would continue its research in an effort to provide public transparency about these incidents. He warned that the training techniques used by OpenAI and other frontier labs seem to be incentivizing agents to resort to hacking techniques to complete tasks. The incidents we are aware of are likely the “tip of the iceberg.”

“We’re looking at a handful of data sources where these agents happen to have left behind crumbs for us to find,” he said. “OpenAI surely knows more about it. Other labs surely know more about it that they haven’t released publicly. But I would expect that researchers are going to continue to find more traffic, more evidence of what agents have left behind.”

Does he trust the labs to be transparent about their findings?

“I’m not going to comment on that,” Stosz said.