Phishing

Phishing consistently stands as the most popular attack type, accounting for 72% of all advanced email threats. While phishing emails of the past were often easy to spot, that’s no longer the case. Today’s threat actors can use free AI tools to generate messages with perfect spelling, grammar, and syntax that can trick even the most eagle-eyed employee into divulging private information.

Phishing by the Numbers

298,878

Number of phishing incidents reported to FBI IC3.

Source: FBI IC3 Report

$4.48M

Average cost of a data breach caused by phishing.

Source: IBM Cost of a Data Breach Report, 2024

261

Average days required to resolve breach resulting from phishing attack.

Source: IBM Cost of a Data Breach Report, 2024

AI technologies offer threat actors the perfect bar for mixing malicious cocktails that are targeted, unique, and generated at scale—think spear phishing and business email compromise attacks on steroids.”

— Osterman Research

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Anatomy of a Phishing Attack

Real-World Example of a Phishing Attempt

How Phishing Works

A standard credential phishing attack has two key characteristics:

Attackers pose as a legitimate service or organization, often mimicking familiar interfaces or domains to deceive users into believing the email is genuine.
They create a sense of urgency or necessity, prompting users to enter sensitive information by leveraging pretexts like account verification, suspicious activity, or urgent updates.

What Phishing Looks Like

Designed to appear as a message sent via Adobe Acrobat Sign, this phishing email claims the employee's signature is needed on a non-disclosure agreement. The notification appears legitimate—using the address adobesign@acrobatsign[.]us[.]com, actual Adobe branding, and personalized content. However, the embedded button links to a phishing site, and any information provided will be stolen. This email can easily bypass a traditional email security solution and trick an unsuspecting target.

Source: Adobe Acrobat Sign Impersonators Use Customized Phishing Pages in Email Attacks

See more examples of real phishing attacks

Recognizing Top Phishing Techniques

Stay ahead by staying informed

Discover how to spot every type of phishing threat

PROBLEM

Generative AI Makes Phishing More Effective and Scalable
91% of security professionals reported experiencing AI-enabled cyberattacks in the past six months.

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Generative AI enables scammers to craft unique email content quickly, making detection difficult for traditional security software.

AI simplifies the creation of sophisticated social engineering threats, empowering even novice cybercriminals to up-level their attacks.

Malicious AI tools like WormGPT and FraudGPT are designed specifically for criminal activities, enabling attackers to convincingly compose deceptive content.

See examples of real email attacks generated by AI

PROBLEM

How to Defend Against Phishing

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Asana Projects Contain Sensitive Data

Support a Culture of Healthy Skepticism

Because attackers have an untold number of strategies for deceiving your workforce, employees should be encouraged to approach some requests with a reasonable level of suspicion. They should also feel comfortable pursuing external verification via means other than email.
Foster an environment where the unofficial cybersecurity motto is “Better safe than sorry.”

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Perform Social Engineering Penetration Testing

Assess workforce susceptibility to common social engineering attacks by sending emails that leverage the same tactics real-world attackers use and observe whether employees engage.
Social engineering penetration testing enables you to evaluate the effectiveness of your security awareness training, compliance with security policies and protocols, and the strength of your company's network security controls.

Traditional Solutions Fall Short

Implement the Right Technology

The most effective way to protect your workforce is to invest in modern technology that proactively blocks attacks.
Unlike a SEG, an API-based security solution uses AI-native detection engines to ingest, analyze, and cross-correlate behavioral signals to spot anomalies in email patterns that indicate a potential attack. It then automatically remediates malicious emails to prevent end-user engagement.