Stop QR Code Attacks with Intent Analysis

Problem

Beyond the Link: How QR Codes Evade Legacy Email Security

QR codes are everywhere—single sign-on (SSO), multi-factor authentication (MFA), password resets, vendor payments, and account verification. Threat actors weaponize these workflows by embedding malicious links within QR codes. These “quishing” attacks evade traditional detection technology, directing users to credential-harvesting sites or malware downloads.

These attacks exploit trust—as QR codes feel routine and harmless, often associated with secure platforms like Okta, Duo, and Microsoft Authenticator—and provide a built-in means of obfuscation, since any destination remains hidden until the user scans the code.

Legacy email security, and human employees, simply cannot successfully analyze QR codes, which is why it has become an ideal delivery vector for phishing, ransomware, and account takeovers.

Problem^AI

QR Code Phishing + AI = Attack Obfuscation at Scale

Generative AI iteration capitalizes on the obfuscation-by-design that's inherent to QR codes, taking QR-based phishing (quishing) to new heights, enabling threat actors to launch exponentially more scalable, precise, and highly evasive campaigns.

This isn’t just an evolution—it’s an arms race.

Scale

AI-driven phishing platforms generate thousands of unique QR code attacks in seconds, with customized URLs for different targets. Attackers now deliver phishing campaigns at global scale with unprecedented reach.

Precision

Gen AI ensures that QR code attacks perfectly mimic trusted business communications. Whether it's a fake Okta MFA request, a DocuSign reminder, or a vendor invoice code, the messaging is hyper-relevant, and user-targeted.

Variance

Gen AI iteration evades signature-based defenses by modifying phrasing, QR image structures, and sender details. AI even adjusts tone, urgency, and formatting based on the target’s role and past interactions.

Solution^AI

Stop QR Code Attacks Without Chasing the QR Code

Legacy defenses rely on extracting and following QR code links—a flawed approach, as attackers use common evasion techniques like link redirection, shorteners, and cloaking to bypass detection.

NACE^TM takes a fundamentally different approach.

Rather than flawed link-chasing, NACE^TM analyzes the intent of the email itself—its semantics, tone, and context—to identify malicious behavior regardless of the QR Code destination. This eliminates reliance on payload analysis and ensures protection against even the most evasive QR Code phishing techniques.

NACE^TM understands intent to fundamentally change QR code phishing detection.

Intent-Based Detection

Instead of relying on QR Code link reputation, NACE^TM performs deep semantic and thematic analysis of the email itself to find intent, and stop threats before they reach employees. OCR scanning of the QR Code is performed to gather auxiliary information, but the URL is not pursued.

Pre-Trained Classifier

NACE^TM is fine-tuned on thousands of QR Code phishing campaigns, recognizing the linguistic patterns commonly paired with QR code attacks, making it immune to evasions like redirection, shorteners, and cloaking.

Thematic Analysis

NACE^TM provides thematic insights by generating a structured representation of topics, phrases, and subtopics. This identifies the underlying themes, even when variations occur, adding an extra layer of detection for Gen AI iteration.

Zero-Shot Classification

Generative AI can introduce semantic variations of emails while keeping the same intent. By harnessing the power of LLMs, NACE^TM identifies new attack variants in real-time, even if the QR code structure or message style has never been seen before.

Similarity Analysis

NACE^TM computes semantic embeddings for every message and compares them to pre-stored threat actor patterns—using cosine similarity to detect social engineering specifically for QR Code tactics designed to manipulate victims into unsafe actions.

Why Inception Cyber for QR Code Phishing

AI-powered threats demand AI-powered defense.

InceptionCyber is leading the way in stopping the next generation of QR Code attacks—before they reach your employees' inboxes.

Intent-Based Analysis

NACE^TM does not rely on the final landing phishing page or malicious URLs. Instead, it conducts semantic and thematic analysis of emails to understand the intent behind them. By evaluating the contextual relationship between the intent, auxiliary information from QR Codes, and SMTP headers, NACE^TM can detect OR Code attempts and malicious call-to-action URLs before they reach employees.

0-day and Known Malicious URLs, Phishing

Eliminating the reliance on malicious payloads means that NACE^TM is uniquely able to detect 0-day, and known phishing pages as well as malicious call to action URLs.

Proactive Threat Neutralization

By stopping phishing at the email layer, NACE^TM prevents phishing links from ever reaching the endpoint, reducing the risk of users opening the links.

Immune to Evasion Techniques

Because NACE^TM doesn’t rely on chasing URLs behind QR Codes, Inception Cyber is less affected by evasion techniques designed to hide, change, or obfuscate malicious URLs.

10 Minutes to Value

Since we don't need to build deep employee datasets—which take other vendors 30 days or more—our NACE^TM pre-trained model begins stopping threats as soon as it is deployed.

Read how NACE^TM is Stopping QR Code Attacks

See our walkthroughs and step-by-step breakdowns of real-world QR Code attacks, and how Inception Cyber NACE^TM stops them when other technologies can't.

From Voicemail to Compromised: How a Tiny HTM File Packs a Big Threat

Threat Research

Kalpesh Mantri, Principal Research Engineer

Quick Read: Phishing Method: Uses a HTM attachment containing a redirector script. Evasions Redirects to a fake login page, requiring CAPTCHA verification. Detection Evasion: HTM ...

Kalpesh Mantri, Principal Research Engineer

Deceptive Yet Detected: NACE Exposes SVG-Attachment Based Phishing Campaign

Threat Research

Kalpesh Mantri, Principal Research Engineer

Quick Read: Phishing Strategy: Threat actors are leveraging SVG files embedded with JavaScript to bypass email security technologies and deliver phishing payloads directly to ...

Kalpesh Mantri, Principal Research Engineer

3 + 1 = G-Suite Credential Phishing

Threat Research

Kalpesh Mantri, Principal Research Engineer

v2 DocuSign-Themed Phishing Campaign Exploits Trust in Legitimate Platforms Quick Read:

Kalpesh Mantri, Principal Research Engineer

Why Inception Cyber Stands Apart in Email Security

Phishing

Bill Mann, Co-founder and CEO

This week, we published two blogs highlighting real-world email attacks caught by our platform. One attack targeted a CFO with a credential phishing attempt, while another ...

Bill Mann, Co-founder and CEO

DocuSign-Themed Phishing Campaign Exploits Trust in Legitimate Platforms

Threat Research

Kalpesh Mantri, Principal Research Engineer

Quick Read: Phishing Strategy: Impersonation of DocuSign through email and PDF attachment. Tactics Observed: No “To:” header in the email, leveraging SMTP envelope for delivery. ...

Kalpesh Mantri, Principal Research Engineer

See What QR Code Attacks Your Tools are Missing

Whether you're looking to add defense in depth, replace a legacy secure email gateway, or just see whether employee behavior-based tools are actually as good as they promise, we welcome every chance to go head-to-head with the previous generations of email security.

See what QR Code threats are slipping through your defenses with our free assessment.

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Intent-Based Protection Against QR Code Phishing Attacks