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For months, OpenAI’s agent swarms have been attacking online databases to find obscure facts
With little help from frontier labs, independent researchers are piecing together how AI agents coordinate in internet backwaters to access private data hosted on secure servers. Transluce, a nonprofit lab focused on AI oversight, released areportWednesday that shows agents from OpenAI attempting to exfiltrate data from Data USA, the University of New Mexico digital library, and the Australian Institute of Health and Welfare (AIHW). The lab’s investigation raises questions about when OpenAI should have known its agents were attempting to penetrate secure systems on the open internet. Transluce was able to find evidence of agentic misbehavior in a matter of weeks simply by hunting for poorly defended web services and corroborating their findings with other open records of agent swarms on the internet. Transluce shared its report the same day Australian Prime Minister Anthony Albanese said OpenAI agents hadattempted to break intofour government websites and had succeeded in one case, even writing files to an internal server in the country’s national healthcare system. While we lack specifics on the successful hack, Albanese said it was apparently part of an information retrieval evaluation, which maps onto the activity that Transluce and other researchers discovered. In these exercises, which may be training or evaluations, OpenAI models are asked to track down obscure statistics: metrics of Thai drug enforcement, medicine costs in Australia, the median earnings of U.S. master degree holders in 2014. The agents use poorly secured internet services to share and find answers, often trying to penetrate secure databases. They’ve been doing so at least since March 2026, and possibly since November 2025. It may be happening right now. Transluce began its investigation after a different group of researchersidentifiedan obscure forum where agents collaborated to beat timed tests. Their report relies on data from a website, urlquery.net, that acts as a browser proxy, ostensibly for security research — users can analyze a URL without opening it themselves. The service, however, publishes public logs of this activity. The Transluce researchers were able to identify agents using the service by cross-checking their discussions on the forum. “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.netrecordsfound by Transluce showed an agent attempting to get into the site. In a wiki entry on June 21, an agentdiscussestheir inability to bypass AIHW’s anti-bot protections. The researchers who identified that forumbelievea 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 datasets, 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.
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Meta is putting its muscle behind Muse as the AI app takes off
Muse’s traction is surging, fueled by Meta’s promotion of the AI app at its annual developer conference this week and strong early reviews that praised its polished design and highly capableAI modelunder the hood. At the start of the week, Muse had surpassed 2.5 million downloads since its September 8 launch. Now, the app has amassed more than 3.4 million downloads, according to the most recent estimates from market intelligence firmSensor Tower. The install numbers are only current as of the firm’s Thursday estimates, which can lag behind real-world adoption. That means they don’t even capture the full impact of the big push Muse received at this week’s Meta Connect conference, where the social network companyannounced a range of upcoming featuresfor the new AI app, including video chat with the Muse avatar, support for computer use on the Mac, a dedicated email address, more partners and connectors, and plans for smart glasses integrations. Estimates from other market intelligence firms show Muse with similarly strong traction, though their numbers vary quite a bit.Apptopia, for example, puts Muse’s total number of downloads to date at 4.3 million. (Muse is currently only available in the U.S. and Canada). It estimates that 2.6 million of those were on iOS alone. Meanwhile, another firm,Appfigures, says it sees Muse installs at roughly 2.3 million as of Thursday, almost evenly split between iOS and Android. Sensor Tower also has visibility into daily active users for the Muse app following the Meta Connect conference. It found that figure climbed 27% on Wednesday after the event wrapped. Before the conference, Muse was already off to a strong start. Sensor Tower said the app reached an estimated 2.8 million downloads in its first two weeks on the app stores. During that time (September 8 to September 17), the Muse app averaged 55% day-over-day growth in downloads. For comparison, ChatGPT averaged 24% day-over-day download growth in its first 10 days after launch. Download growth for Claude and Grok, meanwhile, declined during their respective launches. On Friday, September 18, Muse climbed to the top of the U.S. App Store and has retained its ranking ever since. It also reached the top spot on the Google Play Store on September 19, and remains there today. While much of Muse’s traction so far is organic, the app is also benefiting from the same cross-platform promotion that helped one of Meta’s latest social apps, Instagram Threads, top 500 million monthly active users. That is, Meta is marketing the app to existing Facebook and Instagram users. However, as Meta’s Head of Threads,Connor Hayes, recently toldBusiness Insider,Meta’s approach to marketing Muse differs from its approach with Threads. While Threads also deals in user-generated content that Meta can match to users’ interests when running its cross-promotions, the trick with Muse is to build promotional units that can showcase something the AI agent can do for the user, based on Meta’s understanding of what would be useful or helpful to them specifically. Sensor Tower’s data indicates that Meta rolled out house ads promoting Muse on September 9, a day after its launch. Within 10 days, Muse received the majority of house advertising promotions across Meta’s properties, ahead of promotions for Facebook, Instagram, and WhatsApp. Meta has also begun advertising Muse on mobile ad networks and other social networks, including Reddit, TikTok, and YouTube. By Tuesday, September 22, Muse ranked among the top 10 brands by advertising spend, Sensor Tower said. Still, Muse’s growth can’t be chalked up to Meta’s marketing efforts alone, as ads promoting the app only account for 6% of the ad impressions from launch through September 19.
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This Kerala Engineer Built Open-Source Jev Alternative a Year Before the Hype
Laya handles fast, low-cost decisions locally, with applications ranging from model routing and phishing detection to prompt-injection filtering and edge AI.
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OpenAI Plans to Launch a New Cybersecurity-Focused GPT-6 Series AI Model: Report
OpenAI, the Sam Altman-led AI giant, released two new GPT-6 series models Wednesday, namely the GPT-6 Sol and GPT-6 Luna models, while GPT-6 Astra was launched earlier this month. Recently, OpenAI has launched multiple use-case-specific AI models, serving particular needs, including legal and financial services, namely Astra for Law and ChatGPT for Financial Services, both powered by the GPT-6 series models. Now, the company is reportedly preparing to release another model, specifically built for cybersecurity. Expected to be called GPT-6 Cyber, the AI model is said to debut in preview soon and is said to be deployed via a new product.
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OpenAI Plans to Launch a New Cybersecurity-Focused GPT-6 Series AI Model: Report
OpenAI, the Sam Altman-led AI giant, released two new GPT-6 series models Wednesday, namely the GPT-6 Sol and GPT-6 Luna models, while GPT-6 Astra was launched earlier this month. Recently, OpenAI has launched multiple use-case-specific AI models, serving particular needs, including legal and financial services, namely Astra for Law and ChatGPT for Financial Services, both powered by the GPT-6 series models. Now, the company is reportedly preparing to release another model, specifically built for cybersecurity. Expected to be called GPT-6 Cyber, the AI model is said to debut in preview soon and is said to be deployed via a new product.
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Google to Test AI Chips in Space With Project Suncatcher
The mission will assess how Google’s TPUs handle radiation, vibration, and thermal extremes in low Earth orbit.
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Indian Engineers are Jack of All Trades, But FDE Roles Demand Master of AI
Beyond deploying AI, a Forward Deployed Engineer needs to understand the industry's business processes and how work actually happens inside a specific company.
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Cognizant, Cognition Claim AI Engineering at Odyssey Logistics Saved 37% Costs
Odyssey Logistics reported a 37% net cost saving after Cognizant used Cognition’s Devin to convert legacy Microsoft Access and Visual Basic for Applications forms into cloud-native software.
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Google Launches Gemini 3.8 Flash TTS Models With Custom Voice Creation and Control
Google has rolled out two new text-to-speech models, Gemini 3.8 Flash TTS and Gemini 3.8 Flash-Lite TTS, with tools for creating and controlling custom voices. The models can generate new voices from text prompts, replicate voices from 30-second samples and produce dialogue with different tones, pacing and performance cues. Google is also adding support for multi-speaker conversations, long-form audio and more than 100 languages and dialects. The two models are now available across several Google products and developer tools.
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Meta Muse Charm AI Wearable Device Unveiled at Meta Connect 2026: Here's What You Need to Know
Meta recently held its annual Meta Connect 2026 event to launch Ray-Ban Meta Audio, third-generation Ray-Ban Meta, Meta VR Glasses and new Meta Glasses with new frames and collaborations. During the event, the tech giant showcased a new standalone device called Muse Charm, designed specifically for its Muse artificial intelligence agent. The device looks like a keychain and is designed to offer users quick access to Meta's AI assistant. The Muse Charm features a fingerprint sensor and has a front-facing camera. It will be available later this year.
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Google Launches Gemini 3.8 Flash TTS Models With Custom Voice Creation and Control
Google has rolled out two new text-to-speech models, Gemini 3.8 Flash TTS and Gemini 3.8 Flash-Lite TTS, with tools for creating and controlling custom voices. The models can generate new voices from text prompts, replicate voices from 30-second samples and produce dialogue with different tones, pacing and performance cues. Google is also adding support for multi-speaker conversations, long-form audio and more than 100 languages and dialects. The two models are now available across several Google products and developer tools.
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Genesys Wins ₹283 Cr World Bank-Funded Contract for Ahmedabad Digital Twin
As part of the project, around 25 lakh properties will be surveyed, geocoded, and assigned unique digital identities
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