QR Code Attacks | Abnormal AI

QR Code Attacks

Stop image-based attacks that use QR codes to trick your end users.

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Award-Winning Recognition

Trusted by more than 3,000 customers—including 20% of the Fortune 500

Problem

The Rising Threat of Quishing Attacks

Attackers are now using malicious QR codes in credential phishing and invoice payment fraud attacks. In fact, Abnormal customer data shows that 17% of all attacks bypassing native security controls contain a QR code. These malicious QR codes often link to what appears to be a legitimate website, such as Google or Microsoft login pages, and prompt recipients to enter their login credentials, which are then exploited by the attacker.

Solution

How Abnormal Detects Malicious QR Codes

Parses links embedded in images such as QR codes and feeds the extracted signals to the AI-native detection engine.
Employs NLP/NLU to detect fraudulent topics, tone, and sentiment, including urgency and formality, which are commonly associated with QR code-based attacks.
Detects unusual behavioral signals by understanding normal business relationships and communication patterns.

Why abnormal

An Abnormal Approach to Stopping QR Code Attacks

Learns the behavior of every identity in the organization by analyzing tens of thousands of contextual signals to establish a baseline.
Deploys AI models to detect novel attacks by identifying abnormal behavior and QR codes that lead to malicious links.
Automatically remediates QR code attacks before employees can view or engage with them.

Read the Blog

Learn how attackers are exploiting QR codes to execute quishing attacks.

Source: Verizon DBIR

Take the Self-Guided Product Tour

View the product tour to see how Abnormal stops real-world QR code attacks.

Source: Verizon DBIR

Read the Press Release

Discover how Abnormal’s enhanced detection capabilities stop quishing attacks.

Source: Verizon DBIR

OUR IMPACT

With our previous SEG, the features got shinier, the knobs turned a bit differently, but the core technology had been the same for quite some time. Abnormal’s AI is constantly learning and retraining, getting updates in near real-time, with auto-remediation and automation we can trust. We went from 12 FTEs for email security to 1/4 FTEs with Abnormal.”

— Director of Information Security, Fortune 50 Retailer

Why Enterprises Choose Abnormal

OUR IMPACT

We have every SEG known to man, but threat actors are targeting manufacturing more, and we never want to lose factory availability. Approximately 50-60% of those attacks are initiated through phishing, but traditional SEGs can’t look at the context of what’s in an email to block them…The only way to combat that social engineering is with a product like Abnormal that uses AI to understand email content and context.”

— Jeff Deakins, Director, Information Security and Infrastructure at Marmon Holdings

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OUR IMPACT

The realization of value [with Abnormal] was almost immediate—real-time visibility into attacks going on in the environment that are bypassing the traditional defenses. Abnormal provides the ability for us to scale with confidence, because we know that we’re going to get the same quality of protection at one person as at 28,000.”

— Ryan Fritts, CISO at ADT

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OUR IMPACT

From day one, Abnormal has made it simple. They have been consultative and proactive, showed quick value upon integration, and the decision to switch was easy when we realized the time savings and greater protection we got from a better partner.”

— CISO, Fortune 200 FinTech

See the AI Automation

OUR IMPACT

Abnormal provided a clear improvement over Proofpoint in both detection and cost savings. The transition was smooth, and the results speak for themselves.”

—CISO, F1000 Manufacturer

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Discover How It All Works

See How Abnormal AI Protects Humans