DevConf.IN 2026

In early 2024, a finance officer at the global engineering firm Arup wired $25 million to scammers after joining what appeared to be a legitimate video call with his CFO and colleagues. None of them were real. Every face and voice on that call was AI-generated, a deepfake ensemble so convincing it bypassed every human instinct for suspicion.

(Source: https://www.theguardian.com/world/2024/feb/05/hong-kong-company-deepfake-video-conference-call-scam)

The same AI tools that write your code, documentation and summarise your meetings and Slack threads are now being used to deceive, clone, and exploit at industrial scale. This isn’t just another evolution of hacking, it’s the democratization of deception.

Generative AI has reshaped the threat landscape - automating phishing, creating synthetic identities, generating polymorphic malware, and scaling disinformation campaigns.
Reports from Google’s Threat Intelligence Group, Microsoft’s Digital Defense Report, and Mandiant all confirm this trend: AI has lowered the barrier to entry for sophisticated deception, enabling faster, smarter, and more targeted attacks.

This session exposes the anatomy of AI-enabled threat activity, tracing how criminal and state actors are using LLMs and diffusion models in the wild. It also outlines a defense playbook, behavioral anomaly detection, AI-aware phishing simulations, and governance models for responsible internal AI use.

Because the future of cybersecurity won’t be won by whoever builds the bigger model, it’ll be won by those who recognise deception faster than machines can fabricate it.

Key Takeaways

Understand how AI is transforming the tactics of modern cyber adversaries.
Learn to detect linguistic, behavioural, and media-based AI deception.
Apply a practical mitigation framework combining AI governance, behavioral analytics, and security awareness.