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Cybersecurity awareness: Apple’s cloud-based AI security system - Related to system, deepseek, nearly, flag, mozilla

Cybersecurity awareness: Apple’s cloud-based AI security system

Cybersecurity awareness: Apple’s cloud-based AI security system

The rising influence of artificial intelligence (AI) has many organizations scrambling to address the new cybersecurity and data privacy concerns created by the technology, especially as AI is used in cloud systems. Apple addresses AI’s security and privacy issues head-on with its Private Cloud Compute (PCC) system.

Apple seems to have solved the problem of offering cloud services without undermining user privacy or adding additional layers of insecurity. It had to do so, as Apple needed to create a cloud infrastructure on which to run generative AI (genAI) models that need more processing power than its devices could supply while also protecting user privacy, stated a ComputerWorld article.

Apple is opening the PCC system to security researchers to “learn more about PCC and perform their own independent verification of our states,” the firm presented. In addition, Apple is also expanding its Apple Security Bounty.

What does this mean for AI security going forward? Security Intelligence spoke with Ruben Boonen, CNE Capability Development Lead at IBM, to learn what researchers think about PCC and Apple’s approach.

SI: ComputerWorld reported this story, saying that Apple hopes that “the energy of the entire infosec community will combine to help build a moat to protect the future of AI.” What do you think of this move?

Boonen: I read the ComputerWorld article and reviewed Apple’s own statements about their private cloud. I think what Apple has done here is good. I think it goes beyond what other cloud providers do because Apple is providing an insight into some of the internal components they use and are basically telling the security community, you can have a look at this and see if it is secure or not.

Also good from the perspective that AI is constantly getting bigger as an industry. Bringing generative AI components into regular consumer devices and getting people to trust their data with AI services is a really good step.

SI: What do you see as the pros of Apple’s approach to securing AI in the cloud?

Boonen: Other cloud providers do provide high-security guarantees for data that’s stored on their cloud. Many businesses, including IBM, trust their corporate data to these cloud providers. But a lot of times, the processes to secure data aren’t visible to their end-clients; they don’t explain exactly what they do. The biggest difference here is that Apple is providing this transparent environment for clients to test that plane.

Boonen: Currently, the most capable AI models are very big, and that makes them very useful. But when we want AI on consumer devices, there’s a tendency for vendors to ship small models that can’t answer all questions, so it relies on the larger models in the cloud. That comes with additional risk. But I think it is inevitable that the whole industry will be moving to that cloud model for AI. Apple is implementing this now because they want to give consumers trust to the AI process.

SI: Apple’s system doesn’t play well with other systems and products. How will Apple’s efforts to secure AI in the cloud benefit other systems?

Boonen: They are providing a design template that other providers like Microsoft, Google and Amazon can then replicate. I think it is mostly effective as an example for other providers to say maybe we should implement something similar and provide similar testing capabilities for our customers. So I don’t think this directly impacts other providers except to push them to be more transparent in their processes.

It’s also essential to mention Apple’s Bug Bounty as they invite researchers in to look at their system. Apple has a history of not doing very well with security, and there have been cases in the past where they’ve refused to pay out bounties for issues found by the security community. So I’m not sure they’re doing this entirely out of the interest of attracting researchers, but also in part of convincing their consumers that they are doing things securely.

That being stated, having read their design documentation, which is extensive, I think they’re doing a pretty good job in addressing security around AI in the cloud.

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Nearly a Year Later, Mozilla is Still Promoting OneRep

Nearly a Year Later, Mozilla is Still Promoting OneRep

In mid-March 2024, KrebsOnSecurity revealed that the founder of the personal data removal service Onerep also founded dozens of people-search companies. Shortly after that investigation was published, Mozilla expressed it would stop bundling Onerep with the Firefox browser and wind down its partnership with the business. But nearly a year later, Mozilla is still promoting it to Firefox clients.

The ink on that partnership agreement had barely dried before KrebsOnSecurity ’s Belarusian CEO and founder Dimitiri Shelest launched dozens of people-search services since 2010, including a still-active data broker called Nuwber that sells background reports on people. This seemed to contradict Onerep’s stated motto, “We believe that no one should compromise personal online security and get a profit from it.”.

Shelest released a lengthy statement (PDF) wherein he acknowledged maintaining an ownership stake in Nuwber, a consumer data broker he founded in 2015 — around the same time he started Onerep.

Shelest maintained that Nuwber has “zero cross-over or information-sharing with Onerep,” and stated any other old domains that may be found and associated with his name are no longer being operated by him.

“I get it,” Shelest wrote. “My affiliation with a people search business may look odd from the outside. In truth, if I hadn’t taken that initial path with a deep dive into how people search sites work, Onerep wouldn’t have the best tech and team in the space. Still, I now appreciate that we did not make this more clear in the past and I’m aiming to do enhanced in the future.”.

When asked to comment on the findings, Mozilla revealed then that although customer data was never at risk, the outside financial interests and activities of Onerep’s CEO did not align with their values.

“We’re working now to solidify a transition plan that will provide clients with a seamless experience and will continue to put their interests first,” Mozilla noted.

“While we continue to evaluate vendors, finding a technically excellent and values-aligned partner takes time,” Mozilla wrote. “While we continue this search, Onerep will remain the backend provider, ensuring that we can maintain uninterrupted services while we continue evaluating new potential partners that align more closely with Mozilla’s values and user expectations. We are conducting thorough diligence to find the right vendor.”.

Asked for an modification, Mozilla noted the search for a replacement partner continues.

It’s a win-win for Mozilla that they’ve received accolades for their principled response while continuing to partner with Onerep almost a year later. But if it takes so long to find a suitable replacement, what does that say about the personal data removal industry itself?

Onerep appears to be working in partnership with another problematic people-search service: Radaris, which has a history of ignoring opt-out requests or failing to honor them. A week before breaking the story about Onerep, KrebsOnSecurity -founders of Radaris were two native Russian brothers who’d built a vast network of affiliate marketing programs and consumer data broker services.

Lawyers for the Radaris co-founders threatened to sue KrebsOnSecurity unless that story was retracted in full, claiming the founders were in fact Ukrainian and that our reporting had defamed the brothers by associating them with the actions of Radaris. Instead, we -up investigation which showed that not only did the brothers from Russia create Radaris, for many years they issued press releases quoting a fictitious CEO seeking money from investors.

Several readers have shared emails they received from Radaris after attempting to remove their personal data, and those messages show Radaris has been promoting Onerep.

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Experts Flag Security, Privacy Risks in DeepSeek AI App

Experts Flag Security, Privacy Risks in DeepSeek AI App

New mobile apps from the Chinese artificial intelligence (AI) corporation DeepSeek have remained among the top three “free” downloads for Apple and Google devices since their debut on Jan. 25, 2025. But experts caution that many of DeepSeek’s design choices — such as using hard-coded encryption keys, and sending unencrypted user and device data to Chinese companies — introduce a number of glaring security and privacy risks.

the upstart Chinese AI firm had managed to match the abilities of cutting-edge chatbots while using a fraction of the specialized computer chips that leading AI companies rely on. As of this writing, DeepSeek is the third most-downloaded “free” app on the Apple store, and #1 on Google Play.

DeepSeek’s rapid rise caught the attention of the mobile security firm NowSecure, a Chicago-based corporation that helps clients screen mobile apps for security and privacy threats. In a teardown of the DeepSeek app , NowSecure urged organizations to remove the DeepSeek iOS mobile app from their environments, citing security concerns.

NowSecure founder Andrew Hoog expressed they haven’t yet concluded an in-depth analysis of the DeepSeek app for Android devices, but that there is little reason to believe its basic design would be functionally much different.

Hoog told KrebsOnSecurity there were a number of qualities about the DeepSeek iOS app that suggest the presence of deep-seated security and privacy risks. For starters, he mentioned, the app collects an awful lot of data about the user’s device.

“They are doing some very interesting things that are on the edge of advanced device fingerprinting,” Hoog showcased, noting that one property of the app tracks the device’s name — which for many iOS devices defaults to the customer’s name followed by the type of iOS device.

The device information shared, combined with the user’s Internet address and data gathered from mobile advertising companies, could be used to deanonymize people of the DeepSeek iOS app, NowSecure warned. The findings notes that DeepSeek communicates with Volcengine, a cloud platform developed by ByteDance (the makers of TikTok), although NowSecure presented it wasn’t clear if the data is just leveraging ByteDance’s digital transformation cloud service or if the declared information share extends further between the two companies.

Perhaps more concerning, NowSecure expressed the iOS app transmits device information “in the clear,” without any encryption to encapsulate the data. This means the data being handled by the app could be intercepted, read, and even modified by anyone who has access to any of the networks that carry the app’s traffic.

“The DeepSeek iOS app globally disables App Transport Security (ATS) which is an iOS platform level protection that prevents sensitive data from being sent over unencrypted channels,” the investigation observed. “Since this protection is disabled, the app can (and does) send unencrypted data over the internet.”.

Hoog expressed the app does selectively encrypt portions of the responses coming from DeepSeek servers. But they also found it uses an insecure and now deprecated encryption algorithm called 3DES (aka Triple DES), and that the developers had hard-coded the encryption key. That means the cryptographic key needed to decipher those data fields can be extracted from the app itself.

There were other, less alarming security and privacy issues highlighted in the study, but Hoog stated he’s confident there are additional, unseen security concerns lurking within the app’s code.

“When we see people exhibit really simplistic coding errors, as you dig deeper there are usually a lot more issues,” Hoog noted. “There is virtually no priority around security or privacy. Whether cultural, or mandated by China, or a witting choice, taken together they point to significant lapse in security and privacy controls, and that puts companies at risk.”.

Apparently, plenty of others share this view. Axios reported on January 30 that [website] congressional offices are being warned not to use the app.

“[T]hreat actors are already exploiting DeepSeek to deliver malicious software and infect devices,” read the notice from the chief administrative officer for the House of Representatives. “To mitigate these risks, the House has taken security measures to restrict DeepSeek’s functionality on all House-issued devices.”.

Italy and Taiwan have already moved to ban DeepSeek over security concerns. Bloomberg writes that The Pentagon has blocked access to DeepSeek. CNBC says NASA also banned employees from using the service, as did the [website] Navy.

Beyond security concerns tied to the DeepSeek iOS app, there are indications the Chinese AI corporation may be playing fast and loose with the data that it collects from and about clients. On January 29, researchers at Wiz stated they discovered a publicly accessible database linked to DeepSeek that exposed “a significant volume of chat history, backend data and sensitive information, including log streams, API secrets, and operational details.”.

“More critically, the exposure allowed for full database control and potential privilege escalation within the DeepSeek environment, without any authentication or defense mechanism to the outside world,” Wiz wrote. [Full disclosure: Wiz is currently an advertiser on this website.].

KrebsOnSecurity sought comment on the study from DeepSeek and from Apple. This story will be updated with any substantive replies.

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Market Impact Analysis

Market Growth Trend

2018201920202021202220232024
8.7%10.5%11.0%12.2%12.9%13.3%13.4%
8.7%10.5%11.0%12.2%12.9%13.3%13.4% 2018201920202021202220232024

Quarterly Growth Rate

Q1 2024 Q2 2024 Q3 2024 Q4 2024
12.5% 12.9% 13.2% 13.4%
12.5% Q1 12.9% Q2 13.2% Q3 13.4% Q4

Market Segments and Growth Drivers

Segment Market Share Growth Rate
Network Security26%10.8%
Cloud Security23%17.6%
Identity Management19%15.3%
Endpoint Security17%13.9%
Other Security Solutions15%12.4%
Network Security26.0%Cloud Security23.0%Identity Management19.0%Endpoint Security17.0%Other Security Solutions15.0%

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity:

Innovation Trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity AI/ML Blockchain VR/AR Cloud Mobile

Competitive Landscape Analysis

Company Market Share
Palo Alto Networks14.2%
Cisco Security12.8%
Crowdstrike9.3%
Fortinet7.6%
Microsoft Security7.1%

Future Outlook and Predictions

The Security Cybersecurity Awareness landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:

Year-by-Year Technology Evolution

Based on current trajectory and expert analyses, we can project the following development timeline:

2024Early adopters begin implementing specialized solutions with measurable results
2025Industry standards emerging to facilitate broader adoption and integration
2026Mainstream adoption begins as technical barriers are addressed
2027Integration with adjacent technologies creates new capabilities
2028Business models transform as capabilities mature
2029Technology becomes embedded in core infrastructure and processes
2030New paradigms emerge as the technology reaches full maturity

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:

Time / Development Stage Adoption / Maturity Innovation Early Adoption Growth Maturity Decline/Legacy Emerging Tech Current Focus Established Tech Mature Solutions (Interactive diagram available in full report)

Innovation Trigger

  • Generative AI for specialized domains
  • Blockchain for supply chain verification

Peak of Inflated Expectations

  • Digital twins for business processes
  • Quantum-resistant cryptography

Trough of Disillusionment

  • Consumer AR/VR applications
  • General-purpose blockchain

Slope of Enlightenment

  • AI-driven analytics
  • Edge computing

Plateau of Productivity

  • Cloud infrastructure
  • Mobile applications

Technology Evolution Timeline

1-2 Years
  • Technology adoption accelerating across industries
  • digital transformation initiatives becoming mainstream
3-5 Years
  • Significant transformation of business processes through advanced technologies
  • new digital business models emerging
5+ Years
  • Fundamental shifts in how technology integrates with business and society
  • emergence of new technology paradigms

Expert Perspectives

Leading experts in the cyber security sector provide diverse perspectives on how the landscape will evolve over the coming years:

"Technology transformation will continue to accelerate, creating both challenges and opportunities."

— Industry Expert

"Organizations must balance innovation with practical implementation to achieve meaningful results."

— Technology Analyst

"The most successful adopters will focus on business outcomes rather than technology for its own sake."

— Research Director

Areas of Expert Consensus

  • Acceleration of Innovation: The pace of technological evolution will continue to increase
  • Practical Integration: Focus will shift from proof-of-concept to operational deployment
  • Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
  • Regulatory Influence: Regulatory frameworks will increasingly shape technology development

Short-Term Outlook (1-2 Years)

In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing cyber security challenges:

  • Technology adoption accelerating across industries
  • digital transformation initiatives becoming mainstream

These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.

Mid-Term Outlook (3-5 Years)

As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:

  • Significant transformation of business processes through advanced technologies
  • new digital business models emerging

This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.

Long-Term Outlook (5+ Years)

Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:

  • Fundamental shifts in how technology integrates with business and society
  • emergence of new technology paradigms

These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.

Key Risk Factors and Uncertainties

Several critical factors could significantly impact the trajectory of cyber security evolution:

Evolving threat landscape
Skills shortage
Regulatory compliance complexity

Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.

Alternative Future Scenarios

The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:

Optimistic Scenario

Rapid adoption of advanced technologies with significant business impact

Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.

Probability: 25-30%

Base Case Scenario

Measured implementation with incremental improvements

Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.

Probability: 50-60%

Conservative Scenario

Technical and organizational barriers limiting effective adoption

Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.

Probability: 15-20%

Scenario Comparison Matrix

FactorOptimisticBase CaseConservative
Implementation TimelineAcceleratedSteadyDelayed
Market AdoptionWidespreadSelectiveLimited
Technology EvolutionRapidProgressiveIncremental
Regulatory EnvironmentSupportiveBalancedRestrictive
Business ImpactTransformativeSignificantModest

Transformational Impact

Technology becoming increasingly embedded in all aspects of business operations. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.

The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.

Implementation Challenges

Technical complexity and organizational readiness remain key challenges. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.

Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.

Key Innovations to Watch

Artificial intelligence, distributed systems, and automation technologies leading innovation. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.

Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.

Technical Glossary

Key technical terms and definitions to help understand the technologies discussed in this article.

Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.

Filter by difficulty:

encryption intermediate

algorithm Modern encryption uses complex mathematical algorithms to convert readable data into encoded formats that can only be accessed with the correct decryption keys, forming the foundation of data security.
Encryption process diagramBasic encryption process showing plaintext conversion to ciphertext via encryption key

SOC intermediate

interface

platform intermediate

platform Platforms provide standardized environments that reduce development complexity and enable ecosystem growth through shared functionality and integration capabilities.

algorithm intermediate

encryption

API beginner

API APIs serve as the connective tissue in modern software architectures, enabling different applications and services to communicate and share data according to defined protocols and data formats.
API concept visualizationHow APIs enable communication between different software systems
Example: Cloud service providers like AWS, Google Cloud, and Azure offer extensive APIs that allow organizations to programmatically provision and manage infrastructure and services.