AI-rewritten: This is a summary of an article from Ars Technica, rewritten by AI (Qwen, running locally) to make it easier to read. The facts come from the original article – read it for the full story.

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Safety researchers warn that AI-generated explicit content is spreading unchecked because regulators lack effective tools to stop it. A study by Google found this harmful material often hides in private clouds or direct messages, making detection difficult. Consequently, experts say the most critical point for intervention is at the source: the AI tools used to create these images. Recent testing suggests that leading image generators from Google and OpenAI are becoming less effective at blocking explicit outputs as their capabilities grow.

White Circle researchers published findings exposing flaws in DALL·E 3, Google’s Nano Banana 2, and GPT-Image-2. Using only off-the-shelf tools available online, they bypassed safety filters to generate explicit images. In the best case scenario on DALL·E 3, about 13 percent of attack prompts produced confirmed explicit content. The rate was under 10 percent for Nano Banana 2 and roughly 3 percent for GPT-Image-2. White Circle researchers note that none of these requests required custom-built or frontier AI models to succeed.

White Circle plans to open-source its attack pipeline at the NeurIPS conference in November 2026, aiming to help model makers understand vulnerabilities before they are exploited. While the company has shared findings with some labs through mutual contacts, neither Google nor OpenAI responded to requests for comment. White Circle suggests that newer models may be more capable of generating diverse content or that safety has been deprioritized in favor of capability. They are also discussing mandatory third-party safety testing with government officials to ensure companies invest more in security measures.