Scammers Are Using FaceTime to Pose As Apple Support Reps 69%

By Jake Peterson31%

7/16/2026, 12:00:00 PM

BS Summary: This article contains 19 faulty reasoning types, including Hasty Generalization, Indoctrination, and Biased Writer Voice, with Ambiguity (Equivocation) as the most egregious example at 19.4% saturation with 108 hits. Analysis detected 1,028 faulty-reasoning hits from 556 analyzed words, generating a BS Score of 61.8% and a BS Rank of 69% (6,955 of 21,887 articles). This article is worse (more manipulative) than 68.20% of the article peer group.

Scam calls are nothing new. 
They've gotten so bad, in fact, that many of us simply refuse to answer unrecognized phone calls. 
But FaceTime calls are a bit different—while a phone call can come from any device that knows your number, FaceTime calls (both video and audio calls) require an Apple device to know your FaceTime contact details, which could be either your phone number or email address. 
In short, FaceTime feels more personal than a phone call, which is probably why many of our guards fall a bit when we get a call that way. 
However, that probably shouldn't be the case, if a new scam is anything to go by. 
Don't trust strange FaceTime calls 
As spotted by Malwarebytes Labs, Apple is now warning users to be skeptical of strange FaceTime calls. 
It comes as an update to Apple's guide on recognizing phishing schemes, which details the many ways hackers try to trick you into handing over sensitive information or financial data. 
That might have something to do with the uptick in scams involving FaceTime calls. 
These calls may come from contacts purporting to be "Apple Support," which can be indistinguishable from legitimate phone calls on the surface. 
In addition, some scammers text victims directly, including their contact info in the message. 
These calls may run the gamut of schemes: The scammer may say the victim has experienced credit card fraud, or an issue with their device, or an authentication request for an account. 
Maybe they have a refund offer for you to take advantage of, or a limited-time deal you need to claim now. 
Whatever the case, the situation will likely put pressure on you to act fast, reducing the chance you'll see through the act. 
The point of the FaceTime call may be to lure users into a false sense of security, since, as I've said, victims may be less skeptical of a FaceTime call, especially from "Apple Support." 
However, it may also give hackers an advantage during the scheme: After starting via a FaceTime audio call, scammers can request to switch to a video call, and have the victim share their screen. 
Scammers often employ the use of video calling or sharing apps to walk victims through specific steps on their device. 
And while many convince users to install remote control software on their devices, FaceTime lets users request to control the other caller's screen remotely. 
Malwarebytes says that scammers have successfully emptied bank accounts with these schemes. 
How to protect yourself from FaceTime scams 
Scams are everywhere these days, but that doesn't mean they're inevitable. 
The best defense here is to follow some simple cybersecurity best practices. 
That involves assuming every call (FaceTime or otherwise) from someone other than a trusted contact is suspicious—even if the call says it's from an organization like Apple. 
If on a call, never share private information, especially any that could be used to access your accounts or finances. 
And while FaceTime scams don't necessarily rely on security vulnerabilities, it's helpful to install the latest security patches to plug any known holes in your defenses. 
Apple even invites you to report FaceTime calls you suspect of being malicious. 
If you receive one, take a screenshot of the caller ID, and send that image to reportfacetimefraud@apple.com. 
Article reasoning-pattern comparisonThis article: 0.0%Jake Peterson: 1.4%Lifehacker: 2.4%Confirmation Bias0.0%This article: 0.0%Jake Peterson: 0.3%Lifehacker: 2.2%Anchoring Bias0.0%This article: 11.2%Jake Peterson: 3.1%Lifehacker: 3.1%Availability Heuristic11.2%This article: 0.0%Jake Peterson: 0.8%Lifehacker: 1.0%Representativeness Heuristic0.0%This article: 0.0%Jake Peterson: 0.4%Lifehacker: 0.2%Hindsight Bias0.0%This article: 2.2%Jake Peterson: 3.1%Lifehacker: 2.6%Overconfidence Bias2.2%This article: 9.9%Jake Peterson: 3.8%Lifehacker: 4.9%Framing Effect9.9%This article: 8.5%Jake Peterson: 2.9%Lifehacker: 2.2%Loss Aversion8.5%This article: 0.0%Jake Peterson: 0.5%Lifehacker: 0.9%Status Quo Bias0.0%This article: 0.0%Jake Peterson: 0.1%Lifehacker: 0.1%Sunk Cost Effect0.0%This article: 4.7%Jake Peterson: 4.2%Lifehacker: 4.3%Optimism Bias4.7%This article: 9.9%Jake Peterson: 1.6%Lifehacker: 1.3%Pessimism Bias9.9%This article: 12.9%Jake Peterson: 3.3%Lifehacker: 4.5%Negativity Bias12.9%This article: 0.0%Jake Peterson: 1.9%Lifehacker: 1.2%Self-Serving Bias0.0%This article: 0.0%Jake Peterson: 0.2%Lifehacker: 0.4%Fundamental Attribution Error0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.1%Actor-Observer Bias0.0%This article: 0.0%Jake Peterson: 0.6%Lifehacker: 0.6%In-Group Bias0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.1%Out-Group Homogeneity Bias0.0%This article: 0.0%Jake Peterson: 1.8%Lifehacker: 4.0%Halo Effect0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Horn Effect0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Dunning-Kruger Effect0.0%This article: 11.5%Jake Peterson: 0.9%Lifehacker: 1.0%Recency Bias11.5%This article: 0.0%Jake Peterson: 0.3%Lifehacker: 0.3%Primacy Effect0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.1%Blind-Spot Bias0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Ad Hominem0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Straw Man0.0%This article: 7.6%Jake Peterson: 2.7%Lifehacker: 3.7%Appeal to Authority7.6%This article: 5.8%Jake Peterson: 1.6%Lifehacker: 1.7%False Dilemma5.8%This article: 0.0%Jake Peterson: 0.4%Lifehacker: 0.6%Slippery Slope0.0%This article: 6.1%Jake Peterson: 0.2%Lifehacker: 0.1%Circular Reasoning6.1%This article: 18.2%Jake Peterson: 4.3%Lifehacker: 5.4%Hasty Generalization18.2%This article: 0.0%Jake Peterson: 0.1%Lifehacker: 0.1%Red Herring0.0%This article: 0.0%Jake Peterson: 0.7%Lifehacker: 0.8%Bandwagon0.0%This article: 0.0%Jake Peterson: 2.1%Lifehacker: 2.3%Appeal to Emotion0.0%This article: 0.0%Jake Peterson: 0.3%Lifehacker: 0.4%Begging the Question0.0%This article: 11.5%Jake Peterson: 1.4%Lifehacker: 1.2%Post Hoc (False Cause)11.5%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Tu Quoque0.0%This article: 0.0%Jake Peterson: 0.4%Lifehacker: 0.3%Burden of Proof0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.1%Appeal to Nature0.0%This article: 0.0%Jake Peterson: 0.1%Lifehacker: 0.1%Composition/Division0.0%This article: 11.7%Jake Peterson: 3.9%Lifehacker: 3.2%Anecdotal11.7%This article: 0.0%Jake Peterson: 0.1%Lifehacker: 0.1%No True Scotsman0.0%This article: 19.4%Jake Peterson: 2.1%Lifehacker: 2.6%Ambiguity (Equivocation)19.4%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Gambler’s Fallacy0.0%This article: 2.2%Jake Peterson: 0.2%Lifehacker: 0.2%Middle Ground2.2%This article: 0.0%Jake Peterson: 0.1%Lifehacker: 0.1%Personal Incredulity0.0%This article: 0.0%Jake Peterson: 0.2%Lifehacker: 0.2%Special Pleading0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Genetic Fallacy0.0%This article: 0.0%Jake Peterson: 0.9%Lifehacker: 1.1%Unattributed Quote0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.2%Quote-first Misdirection0.0%This article: 14.2%Jake Peterson: 6.1%Lifehacker: 9.2%Biased Writer Voice14.2%This article: 14.6%Jake Peterson: 6.8%Lifehacker: 6.2%Indoctrination14.6%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Politically Left Leaning Bias0.0%This article: 0.0%Jake Peterson: 0.0%Lifehacker: 0.0%Politically Right Leaning Bias0.0%This article: 3.1%Jake Peterson: 4.6%Lifehacker: 13.3%Attempt to Sell a Product or S…3.1%

556 words analyzed.

Speakers

3speakers7.6%attributed speech514writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 46 words • 0.0% coverageWriter's voice • 28 words • 100.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 5 words • 100.0% coverageMalwarebytes Labs • 17 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 32 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 34 words • 100.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageMalwarebytes • 12 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 27 words • 100.0% coverageWriter's voice • 20 words • 100.0% coverageWriter's voice • 26 words • 0.0% coverageApple • 13 words • 0.0% coverageWriter's voice • 17 words • 100.0% coverage
Selected voice

Malwarebytes

100%flagged-word coverage
12 attributed words29% of attributed speech81% writer coverage
0%10.0%20.0%Indoctrination-15.8 ptsWriter: 15.8%Malwarebytes: 0.0%0.0%Biased Writer Voice-15.4 ptsWriter: 15.4%Malwarebytes: 0.0%0.0%Attempt to Sell a Product -3.3 ptsWriter: 3.3%Malwarebytes: 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.