9to5Mac⁠75%

Security Bite Podcast: Why scammers love FaceTime now ⁠58%

By Arin Waichulis⁠71%

8/7/2026, 3:00:00 AM

BS Summary: This article contains 11 faulty reasoning types, including Framing Effect, Indoctrination, and Appeal to Authority, with Negativity Bias as the most egregious example at 59.3% saturation with 73 hits. Analysis detected 258 faulty-reasoning hits from 123 analyzed words, generating a BS Score of 46.5% and a BS Rank of ⁠58% (13,028 of 30,584 articles). This article is worse (more manipulative) than 57.40% of the article peer group.

Apple recently issued a warning to iPhone users in a support article, noting that scammers are increasingly using FaceTime to impersonate banks and steal user data. 
In this episode, I’m joined by Clayton LiaBraaten, Senior Executive Advisor at Truecaller, to break down how these impersonation scams actually develop, why a live video call feels so trustworthy, and what we can all do to stop them. 
Links 
‘Screen Unknown Senders’ iOS 27 filters your Messages for spam 
Call screening in iOS 27 screens unknown numbers 
Check out Truecaller’s free scam checker tool 
Follow Clayton LiaBraaten on LinkedIn 
Follow Arin on X and LinkedIn 
Subscribe to the show 
Apple Podcasts 
Spotify 
Amazon Music 
Pocket Casts 
RSS Feed 
Article reasoning-pattern comparisonThis article: 0.0%Arin Waichulis: 2.3%9to5Mac: 2.9%Confirmation Bias0.0%This article: 0.0%Arin Waichulis: 0.7%9to5Mac: 1.9%Anchoring Bias0.0%This article: 12.2%Arin Waichulis: 3.1%9to5Mac: 2.8%Availability Heuristic12.2%This article: 0.0%Arin Waichulis: 0.8%9to5Mac: 0.9%Representativeness Heuristic0.0%This article: 0.0%Arin Waichulis: 0.8%9to5Mac: 0.3%Hindsight Bias0.0%This article: 0.0%Arin Waichulis: 4.8%9to5Mac: 2.5%Overconfidence Bias0.0%This article: 31.7%Arin Waichulis: 5.5%9to5Mac: 4.2%Framing Effect31.7%This article: 0.0%Arin Waichulis: 0.6%9to5Mac: 1.1%Loss Aversion0.0%This article: 8.1%Arin Waichulis: 0.9%9to5Mac: 0.6%Status Quo Bias8.1%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.1%Sunk Cost Effect0.0%This article: 14.6%Arin Waichulis: 1.1%9to5Mac: 3.2%Optimism Bias14.6%This article: 0.0%Arin Waichulis: 1.4%9to5Mac: 1.8%Pessimism Bias0.0%This article: 59.3%Arin Waichulis: 6.6%9to5Mac: 3.6%Negativity Bias59.3%This article: 0.0%Arin Waichulis: 1.7%9to5Mac: 1.0%Self-Serving Bias0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.4%Fundamental Attribution Error0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Actor-Observer Bias0.0%This article: 0.0%Arin Waichulis: 0.6%9to5Mac: 0.2%In-Group Bias0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.1%Out-Group Homogeneity Bias0.0%This article: 0.0%Arin Waichulis: 1.9%9to5Mac: 2.7%Halo Effect0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Horn Effect0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Arin Waichulis: 0.5%9to5Mac: 1.5%Recency Bias0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.3%Primacy Effect0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Blind-Spot Bias0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.1%Ad Hominem0.0%This article: 0.0%Arin Waichulis: 0.9%9to5Mac: 0.1%Straw Man0.0%This article: 21.1%Arin Waichulis: 4.5%9to5Mac: 2.8%Appeal to Authority21.1%This article: 0.0%Arin Waichulis: 1.7%9to5Mac: 1.2%False Dilemma0.0%This article: 0.0%Arin Waichulis: 0.9%9to5Mac: 0.5%Slippery Slope0.0%This article: 0.0%Arin Waichulis: 0.1%9to5Mac: 0.1%Circular Reasoning0.0%This article: 8.1%Arin Waichulis: 6.5%9to5Mac: 4.5%Hasty Generalization8.1%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.1%Red Herring0.0%This article: 3.3%Arin Waichulis: 3.6%9to5Mac: 0.6%Bandwagon3.3%This article: 0.0%Arin Waichulis: 4.8%9to5Mac: 1.6%Appeal to Emotion0.0%This article: 0.0%Arin Waichulis: 0.1%9to5Mac: 0.5%Begging the Question0.0%This article: 0.0%Arin Waichulis: 0.9%9to5Mac: 1.5%Post Hoc (False Cause)0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Tu Quoque0.0%This article: 0.0%Arin Waichulis: 1.2%9to5Mac: 0.4%Burden of Proof0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Appeal to Nature0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.2%Composition/Division0.0%This article: 0.0%Arin Waichulis: 5.6%9to5Mac: 2.6%Anecdotal0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%No True Scotsman0.0%This article: 0.0%Arin Waichulis: 1.9%9to5Mac: 1.6%Ambiguity (Equivocation)0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.1%Middle Ground0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.2%Personal Incredulity0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.1%Special Pleading0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Genetic Fallacy0.0%This article: 0.0%Arin Waichulis: 0.5%9to5Mac: 2.1%Unattributed Quote0.0%This article: 0.0%Arin Waichulis: 0.1%9to5Mac: 0.3%Quote-first Misdirection0.0%This article: 6.5%Arin Waichulis: 6.2%9to5Mac: 5.2%Biased Writer Voice6.5%This article: 31.7%Arin Waichulis: 2.8%9to5Mac: 1.6%Indoctrination31.7%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Politically Left Leaning Bias0.0%This article: 0.0%Arin Waichulis: 0.0%9to5Mac: 0.0%Politically Right Leaning Bias0.0%This article: 13.0%Arin Waichulis: 11.5%9to5Mac: 13.4%Attempt to Sell a Product or S…13.0%

123 words analyzed.

Speakers

4speakers36%attributed speech79writer words
Selected voice

Apple

100%flagged-word coverage
26 attributed words59% of attributed speech99% writer coverage
0%25.0%50.0%Indoctrination-49.4 ptsWriter: 49.4%Apple: 0.0%0.0%Attempt to Sell a Product -11.4 ptsWriter: 11.4%Apple: 0.0%0.0%Biased Writer Voice-10.1 ptsWriter: 10.1%Apple: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.