Rupert Marais is a leading specialist in endpoint and device security, bringing years of practical experience in network management and cybersecurity strategy to the table. As an expert in identifying emerging vulnerabilities, he focuses on how modern communication channels can be hardened against increasingly sophisticated digital threats. In this conversation, we explore the overlooked risks of live audio, the limitations of traditional security stacks, and the urgent need for a proactive approach to voice channel protection.
Unlike email or cloud logs, live audio often leaves no searchable trail for traditional monitoring tools. How do deepfake voices complicate the threat landscape for IT help desks, and what specific technical hurdles prevent standard SIEM or DLP systems from detecting these real-time manipulations?
The primary challenge is that live audio is ephemeral and largely invisible to the modern security stack, which was built to parse structured data and text. When a deepfake voice targets a help desk, it exploits the fact that voice rarely generates searchable logs or structured data in the way an email or a chat message does. Traditional tools like SIEMs or DLPs are designed to flag keywords or known malicious file hashes, but they offer almost zero visibility into the fluid, contextual nature of a live conversation. This creates a massive blind spot where high-impact social engineering can occur without leaving a digital footprint for these legacy systems to analyze.
Social engineering attacks over voice happen in seconds, often before a post-incident review can even begin. Why is manual monitoring unable to scale for platforms like Discord or Zoom, and how can organizations measure the ROI of implementing preventative, in-line voice controls over reactive investigations?
Manual monitoring is fundamentally a reactive exercise, and in the fast-moving world of platforms like Discord or Zoom, it simply cannot keep pace with the volume of interactions. By the time a human moderator or a post-incident review team identifies a breach, the damage—whether it is a fraudulent transfer of millions of dollars or a serious reputational hit—has already been done. We measure the ROI of in-line controls by looking at the reduction in incident volume and the prevention of user churn, which is far more cost-effective than the “clean-up” costs of a successful attack. Organizations are starting to realize that stopping an attack in real-time is much cheaper than investigating a disaster after the users have already disengaged.
Governance frameworks are increasingly scrutinizing the duty of care for platforms hosting live interactions. What unique compliance risks arise when voice channels involve vulnerable users, and how should security teams justify the cost of real-time safeguards to regulators who traditionally focus only on stored data?
We are seeing a shift where regulators are moving beyond just stored data to examine the “duty of care” during live interactions, especially when minors or vulnerable populations are involved. The compliance risk here is that an inability to intervene in real-time could be viewed as a failure to provide reasonable safeguards against preventable harm. Security teams must justify these costs by demonstrating that as voice becomes a core communication pillar, it must be held to the same safety standards as text-based systems. It is no longer enough to say that the data wasn’t saved; the harm happened in the moment, and that is where the regulatory scrutiny is now landing.
When users feel unsafe on a communication platform, the resulting churn can be immediate and permanent. Beyond direct financial loss, how does a voice-based breach fundamentally alter user trust, and what steps can leadership take to integrate voice security into a broader brand protection strategy?
Voice-based breaches are deeply personal and visceral, often leaving users feeling violated in a way that a standard data leak might not, which leads to immediate and permanent churn. When a user is targeted by a deepfake or a voice scam on a platform they trust, that foundational trust is shattered, and they often view the platform as complicit in their negative experience. Leadership needs to move voice security from the “out of scope” category and integrate it directly into their brand protection strategy by treating audio as a primary attack vector. This involves adopting tools that can monitor for abuse and manipulation as it happens, ensuring that the voice experience remains as secure as the rest of the digital environment.
What is your forecast for voice channel security?
I believe we are currently at a “phishing moment” for voice, similar to how email was once viewed as a simple productivity tool before it became the primary vector for business email compromise. In the near future, we will see a mandatory shift toward in-line, real-time audio monitoring as organizations realize they can no longer afford to leave this channel unmonitored. The sophistication of deepfake technology will force a total redesign of how we verify identity over the phone or on digital calls. Eventually, real-time voice protection will be as standard as the spam filter is for our inboxes today, as the cost of ignoring this blind spot becomes too high for any reputable brand to bear.
