AI fuels new wave of global security breaches

Global corporations are under growing threat from increasingly sophisticated cyber attacks as AI tools boost the capabilities of malicious actors.

Allianz Life recently confirmed a breach affecting most of its 1.4 million North American customers, adding to a string of high-profile incidents this year.

Microsoft is also contending with the aftermath of a wide-scale intrusion, as attackers continue to exploit AI-driven methods to bypass traditional defences.

Cybersecurity firm DeepStrike reports that over 560,000 new malware samples are detected daily, underscoring the scale of the threat.

Each month in 2025 has brought fresh incidents. January saw breaches at the UN and Hewlett-Packard, while crypto lender zkLend lost $9.5 million to hackers in February.

March was marked by a significant attack on Elon Musk’s X platform, and Oracle lost six million data records.

April and May were particularly damaging for retailers and financial services. M&S, Harrods, and Coinbase were among the prominent names hit, with the latter facing a $20 million ransom demand. In June, luxury brands and media companies, including Cartier and the Washington Post, were also targeted.

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AI startup Daydream revolutionises online fashion search

Online shopping for specific items like bridesmaid dresses can be challenging due to overwhelming choices. A new tech startup, Daydream, aims to simplify this. It uses AI to let users search for products by describing them in natural language, making the process easier and more intuitive.

For instance, a user could ask for a ‘revenge dress to wear to a party in Sicily in July,’ or ‘a summer bag to carry to work and cocktails after.’

Daydream, with staff based in New York and San Francisco, represents the latest venture in a growing trend of tech companies utilising AI to streamline and personalise online retail.

Consumer demand for such tools is evident: an Adobe Analytics survey of 5,000 US consumers revealed that 39% had used a generative AI tool for online shopping last year, with 53% planning to do so this year. Daydream faces competition from tech giants already active in this space.

Meta employs AI to facilitate seller listings and to target users with more relevant product advertisements. OpenAI has launched an AI agent capable of shopping across the web for users, and Amazon is trialling a similar feature.

Google has also introduced various AI shopping tools, including automated price tracking, a ‘circle to search’ function for identifying products in photos, and virtual try-on options for clothing.

Despite the formidable competition, Daydream’s CEO, Julie Bornstein, believes her company possesses a deeper understanding of the fashion and retail industries.

Bornstein’s extensive background includes helping build Nordstrom’s website as its vice president of e-commerce in the early 2000s and holding C-suite positions at Sephora and Stitch Fix. In 2018, she co-founded her first AI-powered shopping startup, The Yes, which was sold to Pinterest in 2022.

Bornstein asserts, ‘They don’t have the people, the mindset, the passion to do what needs to be done to make a category like fashion work for AI recommendations.’ She added, ‘Because I’ve been in this space my whole career, I know that having the catalogue with everything and being able to show the right person the right stuff makes shopping easier.’

Daydream has already secured $50 million in its initial funding round, attracting investors such as Google Ventures and model Karlie Kloss, founder of Kode With Klossy. The platform operates as a free, digital personal stylist.

Users can input their desired products using natural language, eliminating the need for complex Boolean search terms, thanks to its AI text recognition technology, or upload an inspiration photo.

Daydream then presents recommendations from over 8,000 brand partners, ranging from budget-friendly Uniqlo to luxury brand Gucci. Users can further refine their search through a chat interface, for example, by requesting more casual or less expensive alternatives.

As users interact more with the platform, it progressively tailors recommendations based on their search history, clicks, and saved items.

When customers are ready to purchase, they are redirected to the respective brand’s website to complete the transaction, with Daydream receiving a 20% commission on the sale.

Unlike many other major e-commerce players, Bornstein is deliberately avoiding ad-based rankings. She aims for products to appear on recommendation pages purely because they are a suitable match for the customer, not due to paid placements.

Bornstein stated, ‘As soon as Amazon started doing paid sponsorships, I’m like, ‘How can I find the real good product?’ She emphasised, ‘We want this to be a thing where we get paid when we show the customer the right thing.’

A recent CNN test of Daydream yielded mixed results. A search for a ‘white, fitted button-up shirt for the office with no pockets’ successfully returned a $145 cotton long-sleeve shirt from Theory that perfectly matched the description.

However, recommendations are not always flawless. A query for a ‘mother of the bride dress for a summer wedding in California’ presented several slinky slip dresses, some in white, alongside more formal styles, appearing more suitable for a bachelorette party.

Bornstein confirmed that the company continuously refined its AI models and gathered user feedback. She noted, ‘We want data on what people are doing so we can focus and learn where we do well and where we don’t.’

Part of this ongoing development involves training the AI to understand nuanced contextual cues, such as the implications of a ‘dress for a trip to Greece in August’ (suggesting hot weather) or an outfit for a ‘black-tie wedding’ (implying formality).

Daydream’s web version launched publicly last month, and it is currently in beta testing, with plans for an app release in the autumn. Bornstein envisions a future where AI extends beyond shopping, assisting with broader fashion needs like pairing new purchases with existing wardrobe items.

She concluded, ‘This was one of my earliest ideas, but I didn’t know the term (generative AI) and I didn’t know a large language model would be the unlock.’

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Delta Air Lines rolls out AI for personalised airfare

Delta Air Lines is shifting the landscape of airfare by leveraging AI to personalise ticket prices. Moving beyond fixed fares, Delta aims to tailor prices closely to each traveller.

Instead of static prices, the system now analyses customer habits, booking history, and even the time of day to predict an individual’s potential willingness to pay. By the end of the current year, Delta aims to set 20% of its ticket prices using AI dynamically.

The goal represents a significant, sevenfold increase from just twelve months prior. Such a high-tech approach could result in more advantageous deals or elevated costs, depending on a passenger’s unique circumstances and shopping behaviour.

It is crucial to understand how this system operates, Delta’s motivations, and its implications for consumer finances. Traditional ticket pricing has long relied on ‘fare buckets,’ where customers are categorised based on their booking method and timing.

Delta’s new AI ticket pricing system fundamentally shifts away from these static rates. It analyses real-time information to calculate precisely what a specific customer will likely spend on a seat for any given flight.

Glen Hauenstein, Delta’s President, describes this as a complete re-engineering of pricing. He characterises AI as a ‘super analyst’ working continuously, 24/7, to identify the optimal price for every traveller, every time.

The airline has collaborated with Fetcherr, which provides the underlying technological infrastructure and supports other global airlines. Airlines do not adopt advanced, high-tech pricing systems to reduce revenue.

Delta reports that initial results from its AI-driven pricing indicate ‘amazingly favourable’ revenues. The airline believes AI will maximise profits by more accurately aligning fares with each passenger’s willingness to pay.

However, this is determined by a vast array of data inputs, ranging from individual booking history to prevailing market trends. Delta’s core strategy is straightforward: to offer a price available for a specific flight, at a particular time, to you, the individual consumer.

Consumers who have previously observed frequent fluctuations in airfare should now anticipate even greater volatility. Delta’s new system could present a different price to one person compared to another for the same seat, with the calculation performed in real-time by the AI.

Passengers might receive special offers or early discounts if the AI identifies a need to fill seats quickly. However, discerning whether one is securing a ‘fair’ deal becomes significantly more challenging. The displayed price is now a function of what the AI believes an individual will pay, rather than a universal rate applicable to all.

The shift has prompted concerns among some privacy advocates. They worry that such personalised pricing could disadvantage customers who lack the resources or time to search extensively for the most favourable deals.

Consequently, those less able to shop around may be charged the highest prices. Delta has been approached for comment, and a spokesperson stated: ‘There is no fare product Delta has ever used, is testing, or plans to use that targets customers with individualised offers based on personal information or otherwise.

Various market forces have driven the dynamic pricing model used in the global industry for decades, with new tech streamlining this process. Delta always complies with regulations around pricing and disclosures.’

Delta’s openness regarding this significant policy change has attracted considerable national attention. Other airlines are already trialling their AI fare systems, and industry experts widely anticipate that the rest of the sector will soon follow suit.

Nevertheless, privacy advocates and several lawmakers are vocalising strong objections. Critics contend that allowing AI to determine pricing behind the scenes is akin to airlines ‘hacking our brains’ to ascertain the maximum price a customer will accept, as described by Consumer Watchdog.

The legal ramifications of this approach are still unfolding. While price variation based on demand or timing is not novel, the use of AI for ultra-personalised pricing raises uncomfortable questions about potential discrimination and fairness, particularly given prior research suggesting that economically disadvantaged customers frequently receive less favourable deals.

Delta’s AI pricing system personalises every airfare, making each search and price specific to the user. Universal ticket prices are fading as AI analyses booking habits and market conditions. This technology can quickly offer special deals to fill seats or raise prices if demand is detected.

Conversely, the price can increase if the system senses a greater willingness to pay. Shopping around is now an absolute necessity. Utilising a VPN can help outsmart the system by masking location and IP address, which prevents airlines from tracking searches and adjusting prices based on geographic region.

Making quick decisions might result in savings, but procrastination could lead to a price increase. Privacy is paramount; the airline gains insights into a user’s habits with every search. A digital footprint directly influences fares. In essence, consumers now possess both increased power and greater responsibility.

Being astute, flexible, and constantly comparing before purchasing is vital. Delta’s transition to AI-driven ticket pricing significantly shifts how consumers purchase flight tickets.

While offering potential for enhanced flexibility and efficiency, it simultaneously raises substantial questions concerning fairness, privacy, and transparency.

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Crypto hacks hit $3.1 billion by mid-2025

Cyberattacks and scams have already cost the crypto sector more than $3.1 billion in 2025, marking one of the most damaging years. Hacken’s mid-year report reveals that access control failures and social engineering tactics remain the primary culprits.

The most significant single incident occurred in Q1, when Bybit suffered a $1.5 billion breach, accounting for 83% of all Q1 losses. Access control weaknesses were responsible for around $1.83 billion, or 59% of funds lost across both DeFi and CeFi platforms.

Decentralised finance projects were hit particularly hard, with $300 million drained in Q2 alone. Smart contract vulnerabilities contributed to $263 million in losses, including a $223 million hit in the Cetus exploit.

Meanwhile, phishing scams reached new heights, with one incident in April involving a $330 million Bitcoin theft.

Q2 had fewer access breaches than Q1, but single leaks caused rapid, large-scale losses. Hacken’s report concludes that improved cybersecurity is essential for building trust and protecting innovation in the growing blockchain space.

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Allianz breach affects most US customers

Allianz Life has confirmed a major cyber breach that exposed sensitive data from most of its 1.4 million customers in North America.

The attack was traced back to 16 July, when a threat actor accessed a third-party cloud system using social engineering tactics.

The cybersecurity breach affected a customer relationship management platform but did not compromise the company’s core network or policy systems.

Allianz Life acted swiftly by notifying the FBI and other regulators, including the attorney general’s office in Maine.

Those impacted are offered two years of credit monitoring and identity theft protection. The company has begun contacting affected individuals but declined to reveal the full number involved due to an ongoing investigation.

No other Allianz subsidiaries were affected by the breach. Allianz Life employs around 2,000 staff in the US and remains a key player within the global insurer’s North American operations.

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Viasat launches global IoT satellite service

Viasat has unveiled a new global connectivity service designed to improve satellite-powered internet of things (IoT) communication, even in remote environments. The new offering, IoT Nano, supports industries like agriculture, mining, transport with reliable, low-data and low-power two-way messaging.

The service builds on Orbcomm’s upgraded OGx platform, delivering faster message speeds, greater data capacity and improved energy efficiency. It maintains compatibility with older systems while allowing for advanced use cases through larger messages and reduced power needs.

Executives at Viasat and Orbcomm believe IoT Nano opens up new opportunities by combining wider satellite coverage with smarter, more frequent data delivery. The service is part of Viasat’s broader effort to expand its scalable and energy-efficient satellite IoT portfolio.

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UK enforces age checks to block harmful online content for children

The United Kingdom has introduced new age verification laws to prevent children from accessing harmful online content, marking a significant shift in digital child protection.

The measures, enforced by media regulator Ofcom, require websites and apps to implement strict age checks such as facial recognition and credit card verification.

Around 6,000 pornography websites have already agreed to the new regulations, which stem from the 2023 Online Safety Act. The rules also target content related to suicide, self-harm, eating disorders and online violence, instead of just focusing on pornography.

Companies failing to comply risk fines of up to £18 million or 10% of global revenue, and senior executives could face criminal charges if they ignore Ofcom’s directives.

Technology Secretary Peter Kyle described the move as a turning point, saying children will now experience a ‘different internet for the first time’.

Ofcom data shows that around 500,000 children aged eight to fourteen encountered online pornography in just one month, highlighting the urgency of the reforms. Campaigners, including the NSPCC, called the new rules a ‘milestone’, though they warned loopholes could remain.

The UK government is also exploring further restrictions, including a potential daily two-hour time limit on social media use for under-16s. Kyle has promised more announcements soon, as Britain moves to hold tech platforms accountable instead of leaving children exposed to harmful content online.

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Agentic AI forces rethink of cloud infrastructure

Cybersecurity experts warn that reliance on traditional firewalls and legacy VPNs may pose greater risks than protection. These outdated tools often lack timely updates, making them prime entry points for cyber attackers exploiting AI-powered techniques.

Many businesses depend on ageing infrastructure, unaware that unpatched VPNs and web servers expose them to significant cybersecurity threats. Experts urge companies to abandon these legacy systems and modernise their defences with more adaptive, zero-trust models.

Meanwhile, OpenAI’s reported plans for a productivity suite challenge Microsoft’s dominance, promising simpler interfaces powered by generative AI. The shift could reshape daily workflows by integrating document creation directly with AI tools.

Agentic AI, which performs autonomous tasks without human oversight, also redefines enterprise IT demands. Experts believe traditional cloud tools cannot support such complex systems, prompting calls to rethink cloud strategies for more tailored, resilient platforms.

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The US push for AI dominance through openness

In a bold move to maintain its edge in the global AI race—especially against China—the United States has unveiled a sweeping AI Action Plan with 103 recommendations. At its core lies an intriguing paradox: the push for open-source AI, typically associated with collaboration and transparency, is now being positioned as a strategic weapon.

As Jovan Kurbalija points out, this plan marks a turning point where open-weight models are framed not just as tools of innovation, but as instruments of geopolitical influence, with the US aiming to seed the global AI ecosystem with American-built systems rooted in ‘national values.’

The plan champions Silicon Valley by curbing regulations, limiting federal scrutiny, and shielding tech giants from legal liability—potentially reinforcing monopolies. It also underlines a national security-first mentality, urging aggressive safeguards against foreign misuse of AI, cyber threats, and misinformation. Notably, it proposes DARPA-led initiatives to unravel the inner workings of large language models, acknowledging that even their creators often can’t fully explain how these systems function.

Internationally, the plan takes a competitive, rather than cooperative, stance. Allies are expected to align with US export controls and values, while multilateral forums like the UN and OECD are dismissed as bureaucratic and misaligned. That bifurcation risks alienating global partners—particularly the EU, which favours heavy AI regulation—while increasing pressure on countries like India and Japan to choose sides in the US–China tech rivalry.

Despite its combative framing, the strategy also nods to inclusion and workforce development, calling for tax-free employer-sponsored AI training, investment in apprenticeships, and growing military academic hubs. Still, as Kurbalija warns, the promise of AI openness may clash with the plan’s underlying nationalistic thrust—raising questions about whether it truly aims to democratise AI, or merely dominate it.

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Women-only dating app Tea suffers catastrophic data leak

Tea, a women-only dating app, has suffered a massive data breach after its backend was found completely unsecured. Over 72,000 private images and more than 13,000 government-issued IDs were leaked online.

Some documents were dated as recently as 2025, contradicting the company’s claim that only ‘old data’ was affected. The data, totalling 59.3 GB, included verification selfies, DMs, and public posts. It spread rapidly through 4chan and decentralised platforms like BitTorrent.

Critics have blamed Tea’s use of ‘vibe coding’, AI-generated code with no proper review, which reportedly left its Firebase database open with no authentication.

Experts warn that relying on AI tools to build apps without security checks is becoming increasingly risky. Research shows nearly half of AI-generated code contains vulnerabilities, yet many startups still use it for core features. Tea users are now urged to monitor their identity and financial data.

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