The New Face of Social Engineering
The fastest way into an enterprise today isn’t through a firewall. It’s through a human. Attackers don’t need exploits when they can manipulate trust. That’s why phishing, smishing, and vishing attacks are exploding.
Gartner and Deloitte estimate that deepfake-related fraud will cost $40B per year by 2027. At estimated 400-900% growth YoY, it’s the fastest growing cyber security threat vector.
The problem: deepfake fraud does not respect boundaries
Attackers no longer choose just one channel. A phishing email leads to a follow-up text. A deepfake audio call “confirms” new wire instructions. A video meeting seals the deception with a cloned executive face.
Traditional tools see these threats in isolation — one protects email, another scans video, another flags texts. But fraud doesn’t happen in silos. It moves fluidly across video, email, phone, and messaging to trick people into acting before they can verify.
Why single-channel tools fail
Most deepfake detection and protection solutions focus on analyzing surface-level content. They may spot a suspicious email header, or detect AI noise in a video clip. But, by treating each communication stream separately, these tools miss the most critical signals…the inconsistencies that emerge only when data is compared across all channels.
Fraudsters know this. That’s why multi-channel deepfake attacks are rising sharply. An employee trusts what they see on Zoom because it matches what they just read in an email. The “evidence” looks consistent, but only because no system is connecting the dots.
Why this matters for Enterprise security
Deepfakes succeed because people trust what they see and hear. Netarx removes that blind trust by making sure no single channel is taken at face value. Instead, identity is verified across multiple dimensions, instantly and automatically.
This is the only way to protect organizations in a world where fraud doesn’t just attack one door. It tests every entry point at once.
Phishing: The Inbox Trap
Definition: Phishing refers to fraudulent attempts to obtain sensitive information through email. Attackers impersonate trusted organizations, executives, or service providers, luring victims into clicking malicious links or downloading malware.
Key Characteristics:
- Emails often spoof legitimate brands (banks, Microsoft 365, HR portals).
- Messages usually carry urgency: “Your account will be locked in 24 hours.”
- Malicious links lead to credential-harvesting sites or malware downloads.
Recent Example:
In 2024, attackers launched a phishing campaign against Office 365 users, mimicking Microsoft login pages. Thousands of credentials were harvested in just days.
Phishing is the classic email attack. It’s evolved significantly using AI to provide convincing content that isn’t easily detected by a human.
- Spoofed Microsoft 365 logins.
- Fake “secure document” links that look real.
- Emails that look and sound like they come from a real person.
Even with advanced filters, attackers know how to bypass point defenses.
Smishing: Fraud in Your Pocket
Definition: Smishing is SMS-based phishing. Attackers send malicious text messages designed to look like they come from banks, delivery companies, or even government agencies.
Key Characteristics:
- Short messages with links: “Your package is delayed, click here.”
- Sender IDs that mimic legitimate businesses.
- Often contain shortened URLs (bit.ly, tinyurl) to disguise malicious domains.
Recent Example:
A major U.S. bank reported customers receiving fake fraud alerts via SMS. Victims clicked links that redirected them to lookalike banking portals, where credentials were stolen.
Smishing takes the same playbook to SMS and messaging apps.
- “Your account is locked. Reset now.”
- “Package delivery failed. Verify here.”
- Shortened URLs masking malicious sites.
These mobile-first attacks exploit urgency and familiarity.
Vishing: Voices You Can’t Trust
Definition: Vishing (voice phishing) occurs when attackers use phone calls or voice messages to trick individuals into revealing sensitive information. Increasingly, these calls are powered by AI-generated deepfake voices that sound convincingly like real executives or colleagues.
Key Characteristics:
- Caller impersonates authority (CFO, IT helpdesk, law enforcement).
- Urgency is common: “We need you to approve this wire transfer immediately.”
- Deepfake voice cloning makes attacks highly convincing.
Recent Example:
In early 2025, a multinational firm lost over $20 million after employees received vishing calls that mimicked their CFO’s voice, instructing urgent fund transfers
Vishing has become the most dangerous channel. Attackers now use AI voice cloning to impersonate executives, HR, or IT staff.
- “This is the CFO. We need that wire approved immediately.”
- “This is the helpdesk. Verify your credentials now.”
Deepfake voices are convincing and devastating.
The Problem: Multi-Channel Attacks
Here’s the reality: real-world fraud doesn’t attack one channel at a time. A phishing email sets up the smishing text. The smishing text reinforces the vishing call. Attackers combine them into a coordinated strike.
Point solutions that only defend one medium miss the cross-media signals that reveal the fraud. That’s why so many organizations still get blindsided. The average cost for an incident in 2024 was $500K.
The Netarx Difference: metadata and shared awareness
Netarx is the only platform designed from the ground up to fight deepfake threats across all forms of digital communication. We aggregate more than 50 metadata signals from every channel — including location, device, behavior, and timing — and fuse them into ensemble AI models validated by federated consensus.
This approach turns fragmented streams into shared awareness. A phone call from a trusted number is flagged if the device metadata shows impossible travel. A video feed that looks real is questioned when cross-checked against inconsistent email origins. A text message is recognized as fraudulent when compared to historic communication patterns.
How it works
- video: metadata from conferencing platforms (IP, device, geolocation) is analyzed alongside visual patterns to spot anomalies that video-only detectors miss.
- audio / phone: deepfake voiceprints are detected through inconsistencies in call metadata, timing, and behavioral history.
- email: domain, routing, and content are validated not just in isolation, but against simultaneous signals from other channels.
- messaging / sms: message timing and sender metadata are correlated with broader communication context to expose smishing attempts.
At Netarx, we believe trust is the wrong model. Recognition comes from metadata, not surface-level media.
That means:
- In two locations? Flagged.
- Device anomalies? Flagged.
- Cross-media inconsistencies? Flagged.
Attackers may fake a voice, a text, or an email but they cannot fake the entire web of metadata that proves identity.
Stop Attacks Before They Start
Phishing, smishing, and vishing are no longer just nuisances — they’re multi-billion-dollar attack vectors exploiting human behavior. As deepfake technology evolves, these attacks are only becoming more sophisticated.
Organizations need more than email filters or SMS blockers — they need shared awareness across all communication channels to catch fraud attempts before they succeed.
Phishing, smishing, and vishing are no longer isolated threats. They are weapons in coordinated, AI-driven campaigns. The only way to win is to remove trust from the equation and build resilience through shared awareness.
With Netarx, trust is not needed. It’s verified.