Meta rolls out new AI tools to detect ads that secretly lead to child sexual abuse material

Meta announced Wednesday that it took action against 33.2 million pieces of child sexual exploitation content on Facebook and Instagram in the first half of 2026. At the same time, the company is rolling out new AI tools to find ads and accounts that may be used to secretly direct people to illegal child abuse material.

More than 97% of the content Meta acted on was found by its systems before users reported it, the company said. In India, Meta acted on 5.3 million pieces of child sexual exploitation content during the same period, with more than 98% detected before users reported it.

Meta said its latest AI tools are aimed at people using ads that look harmless to send users to illegal content outside Meta’s platforms.

The company has introduced a new large language model (LLM) system to detect what it calls “signposting.” This refers to ads that may look normal but are suspected of directing users to illegal content or other harmful activity elsewhere online. Meta says this is a tactic it has recently seen bad actors use as they continue to change their methods to avoid detection. While the ads themselves may not contain illegal material, they can still act as a gateway to websites hosting child sexual abuse material.

Because of this, Meta said it’s now looking at where an ad sends users, and not just what the ad contains. The company can use this information to block websites or other destinations that break its rules and take action against the accounts behind them.

Meta is also using additional AI-driven scans to find child exploitation content that earlier systems may have missed. The company said it will continue adding new signals as it learns more about how these networks operate.

Another new tool is a “red-teaming AI agent” that tests Meta’s own safety measures. It looks for weaknesses that bad actors could use to get around the company’s protections. Meta said this could help it find new methods of abuse before they become more common.

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