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Phishing Quiz

Phishing Quiz - Free Cyber Threat Awareness Test - FreudlyTake a free phishing quiz to identify fraudulent emails. Quick, no sign-up needed. Start now!en
With 16 practical scenarios and a 10-minute completion time, this phishing quiz explores how well you recognize suspicious messages, links, requests, and account prompts. Your result highlights what you identify confidently and which response habits may need attention, offering a focused opportunity for safer decisions in everyday digital communication.
Questions: 1610 minutes
Phishing Quiz: situation and reply bubbles
July 22, 2026July 22, 2026Material has been updatedJuly 22, 2026Material has been published
8,787 views
719 completions
659 likes
Daniel HallPsychologist · Test reviewer
659 likes
Scale Explorer

How the Scales are Structured

Phishing KnowledgePK
Measures how well you recognize common phishing indicators in emails, links, attachments, and urgent requests.
example score10/16
10/16Developing detectionexample score
0 – 6Foundational awareness
7 – 12Developing detection
13 – 16Strong awareness
A score of 10 indicates developing detection, meaning you notice many warning signs but may benefit from more practice spotting domains, spoofing cues, and appropriate response steps.
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DATA-BASED USER COHORTS

Who Usually Takes This Test?

Office and remote workers
41%OF USERS
People who handle lots of email at work and want to avoid clicking bad links, opening risky attachments, or falling for urgent requests.
Students and new hires
34%OF USERS
Learners starting school or a new job who want to build basic cyber awareness and understand common phishing tricks.
Personal email users
25%OF USERS
Everyday users who want to protect their accounts, money, and private information from scam messages that look legitimate.
BASED ON AGGREGATED, ANONYMIZED DATA FROM TENS OF THOUSANDS OF FREUDLY USERS.
Benchmarking

See How You Compare

Once you complete the test, your results are compared with real-world data from people in your country.
Below is a preview of how scores are typically distributed across each scale.
Shaded area — where most people score
Dot — the average
You — your score lands on each curve after the test— your score, after the test
Phishing KnowledgePK
You?
Average10.4
Typical rangeTypical8 – 12.8
Possible0 – 16
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SAMPLE QUESTIONS

Example Questions From the Test

    • Transport encryption
    • Email list tracking
    • Use of a legitimate corporate subdomain
    • Typosquatting with a look-alike domain
    • The bank has necessarily outsourced its email service
    • The message is encrypted because two identities are shown
    • The email definitely contains a malicious attachment
    • A familiar display name does not prove who sent the message
    • The destination URL associated with the link
    • The wording displayed as the clickable text
    • The sender's displayed name
    • The company logo beside the link
WHAT THE TEST MEASURES

Phishing Quiz - Description and methodology of the test

People who handle email, workplace messages, or online account alerts can use this phishing quiz to practise recognizing pressure, impersonation, deceptive links, and unsafe requests. It suits anyone who wants a clearer picture of current detection habits, whether learning independently or reviewing everyday security decisions. An employee-focused quiz about phishing can also support focused awareness discussions without treating one score as a complete measure of behavior.

What This Assessment Measures

Scenarios assess whether a respondent can separate deceptive signals from ordinary communication and choose a safer next step. They cover links, files, payment requests, login pages, sender identity, multifactor prompts, QR codes, and urgency. The result reflects applied knowledge in these situations, not a fixed trait or guarantee of future performance.

The questions and answers about phishing emphasize three result areas:

  • Phishing Knowledge (0-16) shows how consistently the respondent applies detection principles: Foundational awareness (0-6), Developing detection (7-12), or Strong awareness (13-16).
  • Link and identity checks show whether destinations, domains, sender details, and security signals are inspected rather than trusted at face value.
  • Urgency and response decisions show whether unusual requests are verified, credentials are protected, and suspicious activity is reported.

Methodology and Evidence Base

Each item presents a brief scenario with four response options. The safest or most accurate choice is scored, so the total reflects performance across these decisions rather than a clinical classification. It does not prove that a message is legitimate.

The approach is conceptually consistent with Phish Scale (Steves et al., 2020), which considers message cues and audience-context fit in detection difficulty; this questionnaire is not an adaptation of that scale. NIST guidance adds a practical lens for cues, premise alignment, and task difficulty. Here, those ideas organize realistic judgments, not a standardized version of either source.

Ribeiro, Guedes, and Cardoso linked phishing susceptibility with interacting influences, including detection self-efficacy in their study. That evidence supports reading this result as one indicator among factors shaping behavior. A quiz with answers about phishing can make reasoning visible and guide practice in checking destinations, protecting credentials, and reporting suspicious activity.

Because the questionnaire is brief and non-normed, scores should be interpreted in context. Workload, urgency, prior training, attention, and honest self-report can change performance; the result cannot guarantee protection or diagnose susceptibility.

Literature:
  • Steves, Michelle, Kristen Greene, and Mary Theofanos. "Categorizing human phishing difficulty: a Phish Scale." Journal of Cybersecurity 6, no. 1 (2020): tyaa009. 10.1093/cybsec/tyaa009
  • Dawkins, Shanee, and Jody Jacobs. NIST Phish Scale User Guide. NIST Technical Note 2276. Gaithersburg, MD: National Institute of Standards and Technology, 2023. 10.6028/NIST.TN.2276
  • Ribeiro, Liliana, Ines Sousa Guedes, and Carla Sofia Cardoso. "Which factors predict susceptibility to phishing? An empirical study." Computers & Security 136 (2024): 103558. 10.1016/j.cose.2023.103558

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