Most organizations consider social engineering an email-based attack vector that can be resolved with secure email gateways, an annual phishing assessment, and DMARC records. In this blog, we aim to debunk that theory so that you are up to speed with the latest research, findings, and tools.

Your security stack was built to defend systems. But attackers have moved on to your employees. This blog traces the reconnaissance-to-exploitation chain behind executive impersonation and deepfake fraud, detailing how your leadership gets profiled, mimicked, and weaponized. We also cover the protection strategy that closes the gap your perimeter was never designed to see.

In this blog, we review the 10 best deepfake detection tools of 2026, benchmark them against the detection signals that actually matter in production, and explain why the organizations getting this right are treating deepfake detection software as trust infrastructure. This guide is written for security, fraud, trust and safety, and identity teams evaluating deepfake detection software for real business workflows, not for casual users looking to check one image or video.

In January 2024, a Hong Kong-based finance employee at global engineering firm Arup authorised a wire transfer of HK$200 million to fraudsters during a video call. Fraudsters used AI-generated video and audio to impersonate senior Arup figures on the call. This article reconstructs how the attack was built, why every layer of Arup’s control architecture failed, and what the forensic signals were that could have interrupted it before a single transfer was authorised.

In this blog, we break down how deepfake detection actually works across six method families, map each to the attack type it catches and the conditions under which it fails, and show why every detection method has a half-life and why the right stack is the only defensible posture in 2026.

In this blog, we break down the definition of social engineering, map the anatomy of a modern social engineering attack across its four operational phases, and give your security and executive teams a defence playbook built for the AI-accelerated threat environment your organisation is operating in today.

By the time a fake audio or video is flagged by AI fraud detection systems in an enterprise environment, the damage may already be done. That is why deepfake defense for enterprise environments is a crucial security workflow.

Attackers exploited a GitHub Actions workflow flaw to publish a malicious version of element-data — a Python package with over one million monthly downloads — to PyPI and Docker. Version 0.23.3 remained active for approximately 12 hours, harvesting cloud credentials, SSH keys, API tokens, and .env secrets from every environment where it ran. CI/CD pipelines were the primary target: high-privilege, broadly accessible, and rarely treated as an active threat surface.