News
Scientists create AI neural net that can unlock digital fingerprint-secured devices
Computer scientists at New York University and Michigan State University have trained an artificial neural network to create fake digital fingerprints that can bypass locks on cell phones. The fakes are called “DeepMasterPrints”, and they present a significant security flaw for any device relying on this type of biometric data authentication. After exploiting the weaknesses inherent in the ergonomic needs of cellular devices, DeepMasterPrints were able to imitate over 70% of the fingerprints in a testing database.
An artificial neural network is a type of artificial intelligence comprising computer algorithms modeled after the human brain’s ability to recognize patterns. The DeepMasterPrints system was trained to analyze sets of fingerprint images and generate a new image based on the features that occurred most frequently. This “skeleton key” could then be used to exploit the way cell phones authenticate user fingerprints.
In cell phones, the necessarily small size of fingerprint readers creates a weakness in the way they verify a print. In general, phone sensors only capture a partial image of a print when a user is attempting to unlock the device, and that piece is then compared to the phone’s authorized print image database. Since a partial print means there are fewer characteristics to distinguish it than a full print, a DeepMasterPrint needs to match fewer features to imitate a fingerprint. It’s worth noting that the concept of exploiting this flaw is not unique to this particular study; however, generating unique images rather than using actual or synthesized images is a new development.
The team involved in the study resulting in the DeepMasterPrint creation initiated it as part of the ongoing assessment of vulnerabilities in fingerprint recognition systems. Finding exploitable flaws and fixing them is a constant battle in all digital systems with a security component. With this reality in mind, the scientists determined that merely exposing the flaws of fingerprint systems would not provide an effective solution; a working example of how attacks could be executed provides more specific data for researchers to design around and protect against. Creating the DeepMasterPrint system was meant to address this need.
The results revealed by the DeepMasterPrint system are concerning for anyone relying on fingerprint authentication on their smartphones. Scientists compared the generated fake prints against templates generated by VeriFinger 9.0 SDK, Bozorth3, and Innovatrics IDKit 5.3 SKD, all of which are software systems used in fingerprint authentication systems worldwide. At a low false match rate, i.e., strict match requirements for authentication, the fake print generated by DeepMasterPrint could imitate 23% of the fingerprints in the test database. At a slightly higher false match rate that was still within standard phone authentication limits, the fake print imitated 77% of the test fingerprints.
The scientists in this study did not create physical fingerprints to try and unlock actual phones, leaving that work to be done in the near future. However, even though the successful DeepMasterPrints have yet to be tested in true applications rather than a virtual environment, the data gathered confirmed the initial security concerns which inspired the experiment. Fingerprints are being used as identity verification in a growing number of applications beyond cell phone security, i.e., unlocking entryways, payment authentication, etc. The DeepMasterPrint system is another tool to help researchers guard their security as biometric authentication continues to expand.
News
Tesla looks to upgrade Matrix Headlights with new features
According to the update, Tesla will work on improving the headlights when coming into contact with highly reflective objects, including road signs, traffic signs, and street lights. Additionally, pixel-level dimming will happen in two stages, whereas it currently performs with just one, meaning on or off.
Tesla is looking to upgrade its Matrix Headlights, a unique and high-tech feature that is available on several of its vehicles. The headlights aim to maximize visibility for Tesla drivers while being considerate of oncoming traffic.
The Matrix Headlights Tesla offers utilize dimming of individual light pixels to ensure that visibility stays high for those behind the wheel, while also being considerate of other cars by decreasing the brightness in areas where other cars are traveling.
Here’s what they look like in action:
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- Credit: u/ObjectiveScratch | Reddit
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- Credit: u/ObjectiveScratch | Reddit
As you can see, the Matrix headlight system intentionally dims the area where oncoming cars would be impacted by high beams. This keeps visibility at a maximum for everyone on the road, including those who could be hit with bright lights in their eyes.
There are still a handful of complaints from owners, however, but Tesla appears to be looking to resolve these with the coming updates in a Software Version that is currently labeled 2026.2.xxx. The coding was spotted by X user BERKANT:
🚨 Tesla is quietly upgrading Matrix headlights.
Software https://t.co/pXEklQiXSq reveals a hidden feature:
matrix_two_stage_reflection_dip
This is a major step beyond current adaptive high beams.
What it means:
• The car detects highly reflective objects
Road signs,… pic.twitter.com/m5UpQJFA2n— BERKANT (@Tesla_NL_TR) February 24, 2026
According to the update, Tesla will work on improving the headlights when coming into contact with highly reflective objects, including road signs, traffic signs, and street lights. Additionally, pixel-level dimming will happen in two stages, whereas it currently performs with just one, meaning on or off.
Finally, the new system will prevent the high beams from glaring back at the driver. The system is made to dim when it recognizes oncoming cars, but not necessarily objects that could produce glaring issues back at the driver.
Tesla’s revolutionary Matrix headlights are coming to the U.S.
This upgrade is software-focused, so there will not need to be any physical changes or upgrades made to Tesla vehicles that utilize the Matrix headlights currently.
Elon Musk
xAI’s Grok approved for Pentagon classified systems: report
Under the agreement, Grok can be deployed in systems handling classified intelligence analysis, weapons development, and battlefield operations.
Elon Musk’s xAI has signed an agreement with the United States Department of Defense (DoD) to allow Grok to be used in classified military systems.
Previously, Anthropic’s Claude had been the only AI system approved for the most sensitive military work, but a dispute over usage safeguards has reportedly prompted the Pentagon to broaden its options, as noted in a report from Axios.
Under the agreement, Grok can be deployed in systems handling classified intelligence analysis, weapons development, and battlefield operations.
The publication reported that xAI agreed to the Pentagon’s requirement that its technology be usable for “all lawful purposes,” a standard Anthropic has reportedly resisted due to alleged ethical restrictions tied to mass surveillance and autonomous weapons use.
Defense Secretary Pete Hegseth is scheduled to meet with Anthropic CEO Dario Amodei in what sources expect to be a tense meeting, with the publication hinting that the Pentagon could designate Anthropic a “supply chain risk” if the company does not lift its safeguards.
Axios stated that replacing Claude fully might be technically challenging even if xAI or other alternative AI systems take its place. That being said, other AI systems are already in use by the DoD.
Grok already operates in the Pentagon’s unclassified systems alongside Google’s Gemini and OpenAI’s ChatGPT. Google is reportedly close to an agreement that will result in Gemini being used for classified use, while OpenAI’s progress toward classified deployment is described as slower but still feasible.
The publication noted that the Pentagon continues talks with several AI companies as it prepares for potential changes in classified AI sourcing.
Elon Musk
Elon Musk denies Starlink’s price cuts are due to Amazon Kuiper
“This has nothing to do with Kuiper, we’re just trying to make Starlink more affordable to a broader audience,” Musk wrote in a post on X.
Elon Musk has pushed back on claims that Starlink’s recent price reductions are tied to Amazon’s Kuiper project.
In a post on X, Musk responded directly to a report suggesting that Starlink was cutting prices and offering free hardware to partners ahead of a planned IPO and increased competition from Kuiper.
“This has nothing to do with Kuiper, we’re just trying to make Starlink more affordable to a broader audience,” Musk wrote in a post on X. “The lower the cost, the more Starlink can be used by people who don’t have much money, especially in the developing world.”
The speculation originated from a post summarizing a report from The Information, which ran with the headline “SpaceX’s Starlink Makes Land Grab as Amazon Threat Looms.” The report stated that SpaceX is aggressively cutting prices and giving free hardware to distribution partners, which was interpreted as a reaction to Amazon’s Kuiper’s upcoming rollout and possible IPO.
In a way, Musk’s comments could be quite accurate considering Starlink’s current scale. The constellation currently has more than 9,700 satellites in operation today, making it by far the largest satellite broadband network in operation. It has also managed to grow its user base to 10 million active customers across more than 150 countries worldwide.
Amazon’s Kuiper, by comparison, has launched approximately 211 satellites to date, as per data from SatelliteMap.Space, some of which were launched by SpaceX’s Falcon 9 rocket. Starlink surpassed that number in early January 2020, during the early buildout of its first-generation network.
Lower pricing also aligns with Starlink’s broader expansion strategy. SpaceX continues to deploy satellites at a rapid pace using Falcon 9, and future launches aboard Starship are expected to significantly accelerate the constellation’s growth. A larger network improves capacity and global coverage, which can support a broader customer base.
In that context, price reductions can be viewed as a way to match expanding supply with growing demand. Musk’s companies have historically used aggressive pricing strategies to drive adoption at scale, particularly when vertical integration allows costs to decline over time.
Tesla looks to upgrade Matrix Headlights with new features
xAI’s Grok approved for Pentagon classified systems: report
