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Palo Alto Networks warns of rising AI threats in schools

Cybersecurity

Earlier reports from cybersecurity company Palo Alto Networks highlighted that artificial intelligence (A) is speeding up online threats across many sectors, including education. The company said its threat intelligence unit Unit 42 continues to identify social engineering as a common entry point for attackers. 

Threat groups are now using generative AI (GenAI) to produce more convincing and personalized messages, including deepfakes.

Palo Alto Networks said the pace of AI-driven attacks shows the need for a shift in how schools teach digital literacy. The company added that helping students recognize and resist AI-enabled manipulation is becoming an essential part of protecting the human factor in security.

With this backdrop, the cybersecurity company partnered with cyber safety and AI education provider Cyberlite to release the AI Safety in the Classroom Toolkit as part of their ongoing education initiatives.

“The materials are intentionally easy to use, making it simple for them to become ‘rock stars’ in lesson delivery and integrate these vital learning resources into the education curriculum,” said Lisa Sim, VP, Marketing, Asia-Pacific and Japan and director, CyberFit Nation of Palo Alto Networks.

The toolkit, available in English and Bahasa Indonesia, builds on the existing partnership between Palo Alto Networks and Cyberlite, which has distributed more than 100,000 “Ready, Get Set, Connect!” cyber safety workbooks to schools across the Asia Pacific region.

“The AI Safety in the Classroom Toolkit is a direct response to the urgent need for practical, accessible resources that empower educators in the classroom, teaching students the critical thinking skills needed to be safe and ethical AI users,” said Michelle Yao, co-founder of Cyberlite.

The toolkit includes 30-minute modular lessons that aim to develop critical thinking skills. Topics include the basics of generative AI and prompt engineering, recognizing bias, detecting deepfakes and digital clones, and understanding how recommendation engines affect privacy and personalization.

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