When Apple employees interviewed for jobs at OpenAI, the AI startup’s hardware head allegedly asked them to show up with something unusual: components they were working on and unreleased product samples. That’s according to a blockbuster lawsuit filed by Apple, which accuses OpenAI of stealing confidential documents, spying on hardware prototypes, and tricking one of its trusted partners into performing a proprietary product design technique.
Technology
FCC cracks down on robocall reporting violations
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If you are tired of scam calls slipping through the cracks, federal regulators just took a meaningful step. The Federal Communications Commission finalized new penalties aimed at telecom companies that submit false, inaccurate or late information to a key anti-robocall system. The changes go into effect Feb. 5. They strengthen oversight of the Robocall Mitigation Database, which plays a central role in tracking spoofed calls and holding providers accountable.
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What changed and why it matters
Under the new rules, voice service providers must recertify every year that their filings in the Robocall Mitigation Database are accurate and current. The FCC will now back that requirement with real financial consequences.
The FCC is cracking down on robocalls by tightening rules that govern how telecom providers verify and report call traffic. (iStock)
FCC SCRUBS OWN REFERENCE TO ‘INDEPENDENT’ AGENCY FROM WEBSITE AFTER DEM’S TESTY EXCHANGE WITH CHAIRMAN
Here is what the commission approved:
- $10,000 fines for submitting false or inaccurate information
- $1,000 fines for each database entry not updated within 10 business days
- Annual recertification of all provider filings
- The FCC also adopted a $100 filing fee for initial Robocall Mitigation Database submissions and for required annual recertifications.
- Two-factor authentication to protect database access
- A $100 application fee for initial filings and annual recertifications
The FCC also made clear that these violations are considered ongoing until corrected, meaning fines can accrue on a daily basis rather than being treated as one-time penalties.
According to the FCC, many past submissions failed basic standards. Some lacked accurate contact details. Others included robocall mitigation plans that did not describe any real mitigation practices at all.
How the Robocall Mitigation Database works
The Robocall Mitigation Database requires providers to verify and certify the identities of callers that use their networks. Regulators and law enforcement rely on it to trace spoofed calls and illegal robocall campaigns. That task is harder than it sounds. America’s telecom system is vast and fragmented. Calls often pass through multiple networks owned by major carriers like Verizon and AT&T, as well as smaller regional providers and VoIP services. When calls hop between networks, verification can be missed or ignored. For years, the FCC did not closely verify or enforce the accuracy of these filings. That gap raised serious concerns.
Under the updated rules, providers that fail to recertify or correct deficient filings can be referred to enforcement and removed from the database, which can prevent other carriers from carrying their calls at all.
Why inaccurate robocall data hurts consumers
When robocall filings are wrong or outdated, scam calls are more likely to reach your phone. Providers may treat a call as trusted even when it should raise red flags. That gives robocallers more time to operate and makes it harder for regulators to shut them down quickly. The FCC says stronger penalties and tighter oversight are meant to close that gap before consumers pay the price.
New FCC penalties target inaccurate robocall filings that have allowed scam calls to slip through carrier networks. (Kurt “CyberGuy” Knutsson)
Pushback and pressure on the FCC
When the FCC proposed penalties, it asked whether violations should be treated as minor paperwork mistakes or as serious misrepresentations. Telecom trade groups pushed back. They argued that fines should not apply unless providers first get a chance to fix errors or unless the FCC proves the filings were willfully inaccurate.
State attorneys general and the robocall monitoring platform ZipDX urged a tougher stance. They warned that false filings undermine every effort to stop illegal robocalls. The FCC ultimately chose a middle path. It rejected treating violations as harmless paperwork errors. At the same time, it stopped short of imposing the maximum penalties allowed by law.
What this means to you
For everyday consumers, this move matters more than it may seem. Accurate robocall reporting makes it easier to trace scam calls, shut down bad actors and prevent spoofed numbers from reaching your phone. Stronger penalties give telecoms a reason to take these filings seriously instead of treating them as routine compliance chores.
11 EASY WAYS TO PROTECT YOUR ONLINE PRIVACY IN 2025
The FCC also set a firm annual deadline. Providers must recertify their robocall mitigation filings each year by March 1, creating a predictable enforcement checkpoint. While this will not end robocalls overnight, it tightens a weak link that scammers have exploited for years.
Simple steps you can take right now to reduce robocalls
Even with tougher FCC enforcement, scam calls will not disappear overnight. Here are a few smart steps you can take today to reduce your risk.
- Do not answer unknown calls. If it is important, a legitimate caller will leave a voicemail.
- Never press buttons or say yes to robocall prompts. That confirms your number is active and can trigger more scam calls.
- Report scam calls to your carrier. Most major carriers let you report robocalls directly through their call log or app.
- Register your number with the National Do Not Call Registry at donotcall.gov/. It will not stop scammers, but it can reduce legitimate telemarketing calls.
- Block repeat offenders. If the same number keeps calling, block it so your phone stops ringing altogether.
- Be cautious with callback numbers. Scammers often spoof local area codes to look familiar.
The FCC says accurate robocall reporting by telecoms helps carriers identify and shut down scam traffic faster, but consumer habits still matter.
Pro tip: remove your personal data at the source
Robocalls do not come out of nowhere. Many start with your personal information being sold or shared by data brokers. These companies collect phone numbers, addresses, emails and even family details from public records, apps, purchases and online activity. Scammers and shady marketers buy that data to build call lists. Removing your data from data broker sites can reduce the number of robocalls you receive over time. You can try to do this manually by finding individual data broker websites and submitting removal requests one by one. The process is time-consuming and often needs to be repeated.
Some people choose to use a data removal service to automate this process and continuously monitor for re-posting. That can help limit how often your phone number circulates among marketers and scammers. Less exposed data means fewer opportunities for robocallers to target you. Cutting off robocalls often starts long before your phone rings.
Check out my top picks for data removal services and get a free scan to find out if your personal information is already out on the web by visiting Cyberguy.com.
Get a free scan to find out if your personal information is already out on the web: Cyberguy.com.
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By strengthening oversight and accountability, the FCC aims to shut down illegal robocalls before they ever reach your phone. (Kurt “CyberGuy” Knutsson)
Kurt’s key takeaways
Robocalls thrive when accountability breaks down. By adding meaningful fines, stronger security, annual recertification and filing fees, the FCC is signaling that accuracy is no longer optional. Because penalties can continue to build until problems are fixed, telecoms now face real consequences for ignoring or delaying corrections. This rule forces providers to own their role in stopping illegal calls instead of passing the blame along the network chain. Real progress will depend on enforcement, but this is one of the clearest signs yet that regulators are closing gaps scammers rely on.
Do you think stricter penalties will finally push telecoms to take robocall prevention seriously, or will scammers just find the next loophole? Let us know by writing to us at Cyberguy.com.
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Copyright 2026 CyberGuy.com. All rights reserved.
Microsoft is testing a cleaner version of the Windows 11 search menu that strips it of recommended content and ads. In a blog post on Monday, Microsoft announced that it’s rolling out the decluttered Search Box to Windows Insiders in the Experimental channel as the company looks to regain trust with users and fix Windows.
One of the biggest changes is a revamped search homescreen that displays only your recent searches. Currently, when you open the search menu, it shows your recent searches alongside several distracting tiles on the right pane, containing things like the image of the day, daily quizzes, trending searches, and game recommendations.
Microsoft is cleaning up web results, too, as the search menu will surface the “most relevant answer” first, rather than showing “related products and promotions.”
Aside from doing some decluttering, Microsoft is testing other notable improvements to its search menu. It will more clearly show metadata, along with a preview of the file in the pane on the right side of the search menu, making it easier to figure out where the result came from. The Windows 11 search system will also prioritize results from your local files, apps, and settings, which will “more reliably appear” ahead of web and Microsoft Store recommendations. Testers can now turn off web and Store recommendations entirely from the Settings menu.
There are a few quality-of-life updates, too, as Microsoft says the search system it’s piloting can better handle typos, extra letters, and partial words, while offering some performance improvements.
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Your data broker profile can expose more than most of us realize. It may include your current address, old addresses, relatives, phone numbers and public records that were never tied to a phishing link or hacked password. That is what makes this so frustrating. Strong passwords, two-factor authentication and smart online habits all help protect your accounts. However, they do not stop data brokers from collecting public records and commercial sign-up data.
Those details can then show up on people-search sites. Even worse, scammers can use them to make a fake call, text or email sound personal and believable. Here is where data broker profiles get their information, why careful online behavior alone falls short and what steps can help reduce what strangers can find about you.
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Join us Wednesday, July 22, at 1 PM ET for a free CyberGuy Live class that will help you cut down on robocalls, spam texts, junk email and other unwanted messages. Kurt “CyberGuy” Knutsson will walk you step by step through simple ways to filter spam, clean up your inbox and recognize the messages that could put your personal information at risk. No technical experience is needed. You’ll also receive our spam-stopping checklist, and every registrant will get a link to the class recording afterward.
Reserve your free spot today at CyberGuyLive.com.
FAKE VA SHOE OFFER TARGETS VETERANS
Strong passwords protect your accounts, but they do not stop data brokers from collecting public records and selling personal information to people-search sites. (Chris Ratcliffe/Bloomberg via Getty Images)
Where data broker profiles get your information
Most people assume data brokers get information the same way hackers do, through breaches, weak passwords or phishing links. That can happen. However, a lot of personal information comes from public records and commercial lists.
Data brokers can build profiles from records that may exist even when someone barely uses the internet, including:
- Property deeds and real estate filings
- Voter registration rolls
- Civil and criminal court filings
- Marriage and divorce records
- Bankruptcy filings
- Business registration filings
- Professional license databases
In many U.S. states, these records are public under state or local rules. Data brokers do not need to hack anything to collect them. They can buy, scrape or license the information on an ongoing basis. A home purchase, marriage, divorce or voter registration can create a public record. That record may include a name and address. Once filed, it can become raw material for a data broker profile.
How everyday sign-ups feed data broker profiles
Government records are only one part of the problem. Everyday consumer activity can also feed data broker databases, including:
- Loyalty program sign-ups
- Warranty registrations
- Magazine subscriptions
- Contest and sweepstakes entries
- Real estate transaction data
Commercial aggregators can combine those details with public records to build an enriched consumer profile. Registering the warranty on a dishwasher does not make anyone reckless. Entering a magazine sweepstakes does not make anyone careless. However, both can put personal information into a pipeline built to package and resell it.
How data broker lists can fuel real-world scams
This can sound abstract until a list gets used against real people.
Data broker InfoUSA reportedly sold a list of 19,000 verified elderly sweepstakes players to experienced scam artists. The scammers stole more than $100 million by calling people on the list and pretending to be government or insurance workers. Then they claimed they needed bank account information.
Another case shows the same risk on a larger scale. The Justice Department said Epsilon Data Management sold consumer data to fraud schemes and agreed to pay $150 million to resolve a criminal charge tied to elder fraud. DOJ later said two former Epsilon employees were sentenced after evidence showed they sold targeted lists to a fraudster client who used the data to defraud more than 218,000 victims out of more than $23.7 million.
That should stop you cold. The victims did ordinary things. Their names ended up in marketing databases and lead lists they may never have known existed. Then scammers used those lists to make fraud more targeted, more personal and much harder to spot.
Curious how exposed you already are?
Run a free scan to see where your information is showing up online-results usually land within an hour. Run your free exposure scan. Get a free scan to find out if your personal information is already out on the web: Cyberguy.com
SELLING YOUR HOME THIS SUMMER? YOUR DATA IS ALREADY MOVING
Your address, phone number and relatives may already appear in data broker profiles built from public records and everyday consumer sign-ups. (Ute Grabowsky/Photothek via Getty Images)
Why good online habits do not erase public records
This is the part that can catch a lot of you off guard, especially if you are already careful online. You may skip loyalty cards, avoid sweepstakes and toss warranty cards straight into the trash.
Even so, your information can still show up online because some details come from public records. Property records, vehicle registrations, voter rolls, professional licenses and court filings can all leave a trail with your name attached. In some cases, your profile may also connect you to relatives through someone else’s record.
That means online safety only solves part of the problem. Strong passwords, a password manager and two-factor authentication (2FA) help protect your accounts. However, they do not remove public records that data brokers collect, package and resell.
5 ways to protect your data broker profile now
A few smart moves can help reduce what is already exposed and limit how much new information flows into data broker databases.
1) Search your name on people-search sites
Start by checking what is already public. Search your name on sites like Spokeo, Whitepages and BeenVerified. Look for your address, phone number, relatives and previous locations. This gives you a clearer sense of what scammers, strangers or aggressive marketers may already be able to find.
2) Replace easy-to-guess security answers
If a bank, email account or financial app asks for your mother’s maiden name, birth city, first school or old street name, assume that answer may already appear in a data broker profile. Replace it with a made-up answer and store it in a password manager. The answer does not have to be true. It just has to be consistent and hard for someone else to guess.
3) Limit what you give away going forward
Be more selective with loyalty programs, warranty cards, sweepstakes and online forms. Use only the required fields when possible. Consider using a separate or alias email address for sign-ups, and avoid handing over your phone number unless it is truly needed. Small choices like this can reduce the amount of new data flowing into broker databases.
4) Talk to older relatives before a scammer does
Older relatives are often the final target, reached through a profile built from public records, family connections or past sign-ups. Set a family code word for emergency calls or texts. If someone claims there is an accident, arrest, hospital bill or urgent money problem, the code word gives your family a fast way to know whether the call is real.
5) Use a data removal service for ongoing cleanup
A data removal service can help remove your personal information from data broker and people-search sites without forcing you to chase every listing yourself. These services contact data brokers on your behalf, request removal of your information and keep checking when your data reappears.
That ongoing follow-up is important because data broker profiles can come back when databases refresh or when your information gets pulled from another source. Look for a service that covers hundreds of data broker and people-search sites, offers recurring removals and lets you request cleanup from specific sites where your personal information appears.
I also recommend considering coverage for your whole household. Family members can be linked together in data broker profiles, so removing only one person’s information may leave other exposed details behind. A family plan can help protect addresses, relatives, phone numbers and other personal information across everyone in your home.
Check out my top picks for data removal services and get a free scan to find out if your personal information is already out on the web by visiting Cyberguy.com
FTC CHIEF ACCUSES DEMOCRATS OF ‘TRYING TO PROTECT THE FRAUDSTERS’ BY WITHHOLDING DATA FROM TRUMP ADMIN
Data brokers compile personal information from public records, loyalty programs and commercial databases, making scams more convincing and harder to detect. (Nikolas Kokovlis/NurPhoto via Getty Images)
Kurt’s key takeaways
What concerns me most about data broker profiles is how little of this comes from a mistake you made online. You can use strong passwords, avoid phishing emails and turn on two-factor authentication, yet your address, old addresses and family connections may still appear on people-search sites. That gives scammers a head start. A fake call or text sounds more believable when it includes real details about you or someone you love. The best move is to treat data broker cleanup as part of your regular privacy routine. Search your own name, change easy-to-guess security answers, limit what you share on forms and consider using a data removal service that keeps checking when your information comes back.
What personal detail would worry you most if it showed up on a people-search site: your address, phone number, relatives or something else? Let us know by writing to us at CyberGuy.com
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The lawsuit primarily revolves around the alleged actions of three people:
- Tang Tan, a 24-year Apple veteran who recently served as the vice president of the Apple Watch. In 2024, Tan left to work on Jony Ive’s hardware company, io, which was acquired by OpenAI last year. OpenAI then appointed Tan as chief hardware officer.
- Chang Liu: A former Apple employee who worked as a systems electrical engineer on the iPhone for over eight years. Liu joined OpenAI in January 2026 as a member of technical staff.
- Yu-Ting “Alyssa” Peng: A former Apple employee who joined OpenAI in April 2026.
They’re accused of being part of an ongoing scheme to steal Apple’s secrets as OpenAI plans its first AI hardware device, which is supposed to be coming next year.
Here are the most surprising claims in Apple’s 41-page filing.
Liu allegedly kept an Apple-owned computer, allowing him to download dozens of confidential files
After announcing plans to leave Apple, Liu allegedly didn’t respond to requests to sign a confidentiality reminder, schedule an exit interview, or confirm that he returned company-owned devices, as is standard with departures at Apple. Instead, Apple claims Liu “failed to return at least one Apple-owned computer,” and told another employee, Peng, that he still has “another computer.”
Liu also allegedly accessed Apple’s cloud-based network storage weeks after he left the company, using an authentication vulnerability that Apple didn’t know about. “Mr. Liu celebrated his find with Ms. Peng and set about exploiting it: ‘LOL, I found out I can access the
[network storage], so funny,’” Apple claims. “Ms. Peng’s response was immediate: “‘I’m ready.’”
Apple accuses Liu of downloading dozens of confidential files from its storage system, including documents containing technical specifications, details about unreleased products, and engineering presentations, including one detailing the manufacturing and testing of Apple’s main logic boards.
Peng is accused of siphoning confidential Apple information to Liu
In the months following Liu’s departure, Peng allegedly kept Liu in the loop about Apple’s projects, engineering details, and vendor relationships. “Ms. Peng and Mr. Liu would engage in depth about those confidential projects, while Mr. Liu was working on developing OpenAI’s competing hardware,” Apple claims. “Mr. Liu’s work for OpenAI was informed by a steadily flowing stream of Apple’s trade secret information from Ms. Peng.”
Apple also claims that Liu informed Peng on how to access and copy files from Apple’s devices “to avoid trouble with the security team,” while pointing her to “specific Apple project folders and proprietary engineering data.” Peng departed Apple for OpenAI in April 2026.
OpenAI’s hardware head allegedly digs for confidential Apple projects during interviews
Tan is accused of soliciting Apple’s trade secrets during interviews with OpenAI job candidates — and quizzing them on it. Apple claims Liu told Peng about how another former Apple employee “fumbled” his answers to a question Tan asked about “a top-secret project for an unreleased new Apple product.” Liu then allegedly downloaded “some info” using his access to Apple’s network to help Peng prepare for her interview.
In another instance, Apple claims another former employee began “screenshotting and downloading files relating to a highly confidential Apple project” before an interview with OpenAI. Tan is accused of asking for more information about that same project during the interview. Last year, Tan admitted to receiving confidential information about an AI hardware startup before joining Ive’s io.
Tan asks former Apple employees to share parts and product samples for “show and tell”
Aside from asking for more information about Apple’s secret projects, Tan is accused of telling interviewees to bring hardware components and product samples from their work at Apple for “show and tell sessions:”
For example, messages left on an Apple-issued work device show that Mr. Tan instructed an Apple employee to “bring some parts [she] worked on” such as “Batteries,” “SIP” (Systems-in-Package), “mlb” (multi-layer or main logic boards), and “shields” and that it may “be good to show” other interviewers these Apple components.
Additionally, OpenAI is accused of asking interviewees to prepare “Technical Deep Dive” presentations, with slides revealing confidential information from their work at Apple.
OpenAI allegedly “coached” Apple employees on how to bypass security measures
Apple claims Tan kept an internal document that outlines employee offboarding procedures. OpenAI allegedly used this information to warn employees coming from Apple about the company’s security checks, and “coached” them on how to avoid it.
The AI giant also advised departing Apple workers not to disclose their new employer, and also offered tips on how to avoid a “dreaded walk out,” which would result in their immediate removal from the company, preventing them from accessing Apple’s systems for a standard two weeks, the lawsuit alleges. OpenAI is accused of telling Apple employees not to “sign anything at the exit interview,” and if they’re asked to sign a document, to tell OpenAI “asap.”
In the lawsuit, Apple says that OpenAI’s alleged tactics “appear to be having their desired effect.” Apple claims it has noticed “a recent trend of employees who are leaving Apple for OpenAI and taking steps to evade security measures,” including workers “ignoring outreach by security personnel to schedule exit processes and security reviews.”
Apple accuses OpenAI of stealing its metal-finishing technique
Apple claims OpenAI has used its confidential information to approach its “trusted partners,” including one that carries out a proprietary, multi-step metal-finishing technique for its products. OpenAI allegedly misled Apple’s partner, making the company believe that OpenAI had Apple’s permission to use the metal-finishing technique. “Apple has not given OpenAI or io permission to use or a license to any of Apple’s trade secrets or confidential information, including those it has entrusted with this partner,” Apple says.
Apple also accuses OpenAI of approaching “at least” one other supplier that works with Apple on manufacturing related to power and batteries. OpenAI allegedly used confidential information and internal codenames to ask “targeted questions” about Apple’s components “that would be useful in furthering OpenAI’s hardware ambitions.”
OpenAI spokesperson Drew Pusateri provided this statement to The Verge on Friday: “We have no interest in other companies’ trade secrets. We remain focused on building innovative technology that empowers people everywhere.”
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