Now: Efficiently moderate content and ensure DSA compliance Learn how
Manage and orchestrate the entire Trust & Safety operation in one place - no coding required.
Take fast action on abuse. Our AI models contextually detect 14+ abuse areas - with unparalleled accuracy.
Every user deserves to be protected - and every Trust & Safety team deserves the right tools to handle abuse.
The threat landscape is dynamic. Harness an intelligence-based approach to tackle the evolving risks to users on the web.
Don't wait for users to see abuse. Proactively detect it.
Prevent high-risk actors from striking again.
For a deep understanding of abuse
To catch the risks as they emerge
Disrupt the economy of abuse.
Mimic the bad actors - to stop them.
Online abuse has countless forms. Understand the types of risks Trust & Safety teams must keep users safe from on-platform.
Stop online toxic & malicious activity in real time to keep your video streams and users safe from harm.
The world expects responsible use of AI. Implement adequate safeguards to your foundation model or AI application.
Implement the right AI-guardrails for your unique business needs, mitigate safety, privacy and security risks and stay in control of your data.
Our out-of-the-box solutions support platform transparency and compliance.
Keep up with T&S laws, from the Online Safety Bill to the Online Safety Act.
Protect your brand integrity before the damage is done.
From privacy risks, to credential theft and malware, the cyber threats to users are
GenAI tools, and the Large Language Models (LLMs) that underpin them – are impacting the day-to-day lives of billions of users across the globe. But can these technologies be trusted to keep users safe?
This report examines how this new technology can be used by bad actors and vulnerable users to create dangerous content. By testing LLM responses to risky prompts, we are able to assess their relative safety, identify weaknesses, and, most importantly – define actionable steps to improve LLM safety.
In this first independent benchmarking report into the LLM safety landscape, ActiveFence’s subject-matter experts put LLMs to the test. We ran over 20,000 prompts to analyze the responses of six leading LLMs in seven major languages, across four high-risk abuse areas:
The results offer important data for teams to understand their LLM’s relative strengths and weaknesses, and understand where resource allocation is required.