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The 2026 Singapore Consensus on Global AI Safety Research Priorities

July 7, 2026
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Singapore AI Safety Red Teaming Challenge 2026 Report

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The Singapore AI Safety Red Teaming Challenge 2026 convened participants from 14 countries across Asia-Pacific to test Gen AI apps for data leakage risks in English and regional languages, to understand how these risks manifest across linguistic contexts. The report summarises key challenge takeaways, including inconsistent security behaviour and inadequate multilingual protections across Gen AI apps.

An Evaluation of Data Leakage Risks in Tool-Using LLM Agents in Realistic Scenarios

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AI agents are increasingly granted access to sensitive information and external tools to perform tasks on behalf of users, increasing data leakage risks. This report presents a joint evaluation by the SG and KR AISI examining whether agents can complete routine workflows without leaking data. Across 12 realistic tasks spanning areas such as enterprise productivity and customer service, the evaluation finds that agents may successfully complete tasks while still exhibiting data-handling failures, suggesting that task correctness alone is insufficient to assess agent safety. This report is a more detailed follow-up to an earlier blog post on this topic.

Testing AI Agents for Data Leakage Risks in Realistic Tasks

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Korea and Singapore AISIs jointly tested how AI agents behave in real-world tasks. The exercise examined whether agents can complete multi-step tasks in common settings such as customer service and enterprise productivity without leaking sensitive data. This blogpost shares the key findings, evaluation challenges, and methodological learnings.