Guest Blog: Securing the Human Layer – Social Engineering and Identity-Based Impersonation

Enterprise security programs have long been designed around a familiar perimeter involving networks, endpoints, applications, and data. Even modern Zero Trust architectures, while eliminating implicit trust, still assume that the human initiating an action is authentic once identity checks are satisfied. This is how identities and access to enterprise resources have been handled to date in most environments.

Deepfakes represent a pretty significant shift in how identities are managed in the context of an enterprise. Rather than attacking systems, they attack the trust humans place in familiar voices, faces, and communication channels. As a result, the enterprise attack surface has expanded into a new human layer domain. This layer operates above credentials and cryptography, yet below human decision-making, where social engineering is most effective.

Deepfakes as a Tool for Social Engineering

Traditional phishing relied on deception at scale including poorly worded emails, suspicious links, and generic lures to bad websites. Deepfake-enabled social engineering is different. It is targeted, contextual, and quite persuasive. By cloning an executive’s voice or synthesizing a familiar face in real time, for example, attackers can bypass not only technical controls, but human skepticism as well.

From a security perspective, this is a form of identity-based phishing where the attacker does not impersonate an account, but rather, they impersonate a person. The psychological authority of a known executive or trusted colleague dramatically lowers resistance, especially when the request aligns with normal business activity. The result is a new class of cyber-attack that is both low-friction and high-impact.

Real-World Impersonation Scenarios

Recent incidents illustrate how quickly this threat has moved from theory to practice. Enterprises have reported videoconference sessions where synthetic executives appeared on screen, giving urgent financial or operational instructions. In parallel, highly accurate voice clones have been used to authorize wire transfers, reset credentials, or pressure finance teams into bypassing controls during time-sensitive moments.

What makes these new types of attack scenarios particularly dangerous is their plausibility. Collaboration platforms such as Zoom, Teams, and Webex are now primary venues for executive and management decision-making. They were designed for convenience and productivity, not for adversarial identity verification. Deepfakes exploit that gap with remarkable efficiency.

Multi-Dimensional Risk

The consequences of deepfake-driven impersonation extend beyond traditional information security concerns. Financial fraud is the most immediate risk, but regulatory exposure follows closely behind, particularly in sectors with strict controls over authorization, disclosure, and fiduciary responsibility. A successful impersonation can easily trigger reporting obligations, audit findings, or enforcement actions.

Equally damaging is the reputational harm that can come from a successful deepfake attack. Stakeholders may not, for example, distinguish between a real executive misstep and a synthetic one. Public disclosure of a deepfake-enabled incident can erode trust in leadership, governance, and operational discipline, and these are costs that are difficult to quantify but painfully real.

Emerging Defenses

Encouragingly, new commercial defensive capabilities such as from GetReal Security, are beginning to emerge. Real-time deepfake detection technologies can analyze voice characteristics, facial micro-expressions, and signal artifacts during live communications. When integrated properly into enterprise operations, these tools can flag suspicious interactions before humans act on them.

More importantly, our team at TAG is now seeing the early stages of continuous identity protection for collaboration environments. Rather than verifying identity only at login, these approaches assess authenticity throughout a session, adapting controls when synthetic risk indicators appear. This is a critical technology evolution, as deepfake threats are dynamic and context dependent.

Protecting Executive and Workforce Identities

Executives and high-privilege employees are the most attractive targets, but the broader workforce is equally exposed. Any role with authority, access, or influence can be weaponized through impersonation. Protecting digital identity must therefore extend across the organization, encompassing onboarding, collaboration, customer interaction, and third-party engagement.

From a governance standpoint, achieving good security defense from deepfakes requires acknowledging that identity assurance does not end with credentials. It must include ongoing validation of the human presence behind digital interactions, especially in enterprise environments where visual and audio cues drive trust decisions. And increasingly, this is most business environments.

Call to Action

The core message we offer here for enterprise management and cybersecurity leaders should be clear. Specifically, we recommend strongly that identity protection strategies must evolve to include communications and collaboration platforms. Treating deepfake detection and continuous identity verification as optional security capabilities is no longer a defensible management decision.

Enterprise security teams should start by mapping where trust is implicitly granted based on voice or video. They should also work with vendors like GetReal Security to identify high-risk workflows and evaluate technologies that can bring identity assurance into these human-centric channels. The enterprises that act early will not only reduce fraud and regulatory exposure but also preserve the trust that underpins modern digital business.

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