Contents

• Our Commitment to Online Safety
• Expanding Our Thorn Partnership
• How the Classifier Works
• Proactively Combating CSAM at Scale

We are excited to announce that Hive’s partnership with Thorn is expanding to include a new CSE Text Classifier API. Offering advanced AI-powered text detection capabilities, this API helps trust and safety teams proactively combat text-based child sexual exploitation at scale.

Our Commitment to Online Safety

Making the internet safer for everyone is at the core of Hive’s mission. Our innovative approach to content moderation and platform integrity has propelled us to become a leading voice in Trust and Safety. 

Over the last several years, we’ve greatly expanded our content moderation product suite. While our content moderation tools reduce human exposure to harmful content across many categories, preventing online child sexual abuse requires specialized expertise and technology.

Last year, we announced our partnership with Thorn, an innovative nonprofit that transforms how children are protected from sexual abuse and exploitation in the digital age. Our enterprise-grade, cloud-based APIs allow us to serve Thorn’s proprietary technology to customers at a large scale.

Expanding Our Thorn Partnership

Under our Thorn partnership, we previously released our CSAM Detection API. This API runs two detection technologies—hash matching and an AI classifier—to detect both known and novel child sexual abuse material (CSAM) across image and video inputs.

Today, we’re expanding this partnership with the CSE (Child Sexual Exploitation) Text Classifier API, which has been highly requested by many of our current Hive customers. This classifier complements our CSAM detection suite by filling a critical content gap for use cases such as detecting text-based child sexual exploitation across user messaging and conversations. With this release, Hive and Thorn can provide customers with even broader detection coverage across text, image, and video.

How The Classifier Works

The CSE Text Classifier API detects suspected child exploitation in both English and Spanish.

Each text sequence submitted is tokenized before being passed into the text classifier. The classifier then returns the text sequence’s scores for each label. There are seven possible labels:

1. CSA (Child Sexual Abuse) Discussion: This is a broad category, encompassing text fantasizing about or expressing outrage toward the subject, as well as text discussing sexually harming children in an offline or online setting.
2. Child Access: Text discussing sexually harming children in an offline or online setting.
3. CSAM: Text related to users talking about, producing, asking for, transacting in, and sharing child sexual abuse material.
4. Has Minor: Text where a minor is unambiguously being referenced.
5. Self-Generated Content: Text where users are talking about producing self-generated content, offering to share their self-generated content with others, or generally talking about self-generated images and/or videos.
6. Sextortion: Text  related to sextortion, which is where a perpetrator threatens to spread a victim’s intimate imagery in order to extort additional actions from them. This encompasses messages where an offender is sextorting another user, users talking about being sextorted, as well as users reporting sextortion either for themselves or on behalf of others.
7. Not Pertinent: The text sequence does not flag any of the above labels.

If any of these labels receive a score that is above their internally set threshold, all scores will be returned in the pertinent_labels section. Below is an example of a pertinent sample response.

A given text sequence might receive high scores across multiple labels. In these cases, it may be helpful to combine the label definitions to better understand the situation at hand and determine what cases are actionable with regard to your moderation team’s specific policies. For instance, text sequences scoring high on both CSAM and Child Access may be from individuals potentially abusing children offline and producing CSAM.

Proactively Combating CSAM at Scale

Safeguarding platforms from CSAM demands scalable solutions. We’re excited to expand our partnership and power more of Thorn’s advanced technology through our enterprise-grade APIs, helping more platforms proactively and comprehensively combat CSAM and CSE text.

If you have further questions or would like to learn more, please reach out to sales@thehive.ai or contact us here.