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Google has added Yoruba and Hausa to the list of languages supported by its AI-powered Search features, AI Overviews, and AI Mode, bringing two of Nigeria’s most spoken primary languages into its search environment. The update allows users to ask questions and receive AI-generated summaries in their native tongues directly within Google Search. The expansion brings Google’s AI Search language support in Africa to 13 languages, including Kiswahili, Wolof, Afrikaans, Kinyarwanda, Akan, Oromoo, Amharic, Somali, Hausa, Afaan, Setswana, isiZulu, Sesotho, and Yoruba. Google said the languages were selected based on search activity across the continent to make its AI-powered search tools accessible to more users. “With the advanced multimodal and reasoning capabilities of our custom version of Gemini in Search, we’ve made huge strides in language understanding, so our most advanced AI search capabilities are locally relevant and useful in each new language we support,” said Taiwo Kola-Ogunlade, Communications & Public Affairs manager for Google West Africa. Nigerians speak over 500 languages. While English is the official language, Hausa and Yoruba are among the most widely used, with a combined 48.7% of speakers across the country. Expanding AI search capabilities into those languages reduces the friction of interacting with complex digital tools, particularly for users who are more comfortable searching or speaking in their mother tongue. Native speakers could type or narrate any question in any supported language on AI Mode within the Search experience in the Google App. This update comes weeks after Google launched WAXAL, an open-source speech database developed in collaboration with African universities. The database was designed to support the development of speech recognition systems and voice assistants. These efforts are part of Google’s broader strategy to localise artificial intelligence tools for African users. “This is about ensuring Nigerians can converse with Search in their mother tongues, making information more helpful for everyone,” said Kola-Ogunlade. Get The Best African Tech Newsletters In Your Inbox Select your country Nigeria Ghana Kenya South Africa Egypt Morocco Tunisia Algeria Libya Sudan Ethiopia Somalia Djibouti Eritrea Uganda Tanzania Rwanda Burundi Democratic Republic of the Congo Republic of the Congo Central African Republic Chad Cameroon Gabon Equatorial Guinea São Tomé and Príncipe Angola Zambia Zimbabwe Botswana Namibia Lesotho Eswatini Mozambique Madagascar Mauritius Seychelles Comoros Cape Verde Guinea-Bissau Senegal The Gambia Guinea Sierra Leone Liberia Côte d’Ivoire Burkina Faso Mali Niger Benin Togo Other Select your gender Male Female Others TC Daily TC Events Next wave Entering Tech Subscribe
Read MoreAs African economies digitise rapidly, cybercrime is evolving just as quickly. Malware that once took skilled programmers weeks or months to build can now be generated in minutes using AI-powered coding tools, enabling cybercriminals to launch cheaper, faster, and large-scale attacks, often targeting businesses and consumers coming online for the first time. The shift is captured in the HP Wolf Security Threat Insights Report, released by the security unit of technology manufacturer HP Inc, which shows attackers shifting from carefully engineered exploits toward a strategy built on speed and volume. By combining AI-assisted coding with modular malware kits, often purchased cheaply on underground forums, cybercriminals can now generate thousands of slightly different malware samples and launch them across the internet within minutes. Rather than investing time in building technically perfect malware, attackers are increasingly relying on large numbers of ‘good enough’ attacks that are inexpensive, automated, and difficult to detect individually. In some cases identified by HP researchers, hackers purchase ready-made malware components for less than $10 and use automated tools to modify them repeatedly. Even if most of these attacks fail, the sheer scale means that a small number of successful infections can still produce significant financial returns. The implications are particularly significant for emerging digital economies. Across Africa, businesses are rapidly adopting cloud services, digital payments, and AI-driven infrastructure. But that rapid digital adoption also expands the region’s cyber-attack surface. According to the HP report, organisations across the continent experience an average of 3,153 cyberattacks weekly—about 60% higher than the global average—suggesting that attackers are actively targeting environments where cybersecurity practices are still maturing. For small and medium-sized enterprises (SMEs), the economic imbalance behind these automated attacks is especially stark. While cybercriminals can assemble malware campaigns for only a few dollars, the damage from a single successful breach can be devastating. Cybercrime is estimated to cost African economies roughly $10 billion annually, and for smaller businesses, the consequences can be existential. In South Africa, for example, a study shows that around 22% of SMEs hit by ransomware attacks ultimately shut down. In this new era of automated cybercrime, the low cost of launching attacks contrasts sharply with the potentially catastrophic cost of defending against them. The shift from precision to scale For many years, the most dangerous cyberattacks were often the most technically sophisticated ones. Highly skilled hackers would craft malware capable of quietly infiltrating networks, stealing sensitive data, or spreading across systems undetected. These attacks required time, expertise, and careful testing. Cybercriminals are adopting a software-like approach to attacks, using automated coding tools to generate, test, and deploy new malware variants within minutes. This speed-over-perfection strategy allows them to launch hundreds or thousands of slightly different attacks, increasing the chance some will bypass defenses. In one HP-identified case, attackers hid malware inside a Scalable Vector Graphic (SVG) image—a file type made of lines and shapes rather than pixels—which browsers open automatically and email filters often trust, letting the malicious code slip past initial security checks. In Nigeria, the average organization now faces roughly 4,701 cyberattacks weekly. Most of these are not highly sophisticated, hand-crafted hacks but automated scripts designed to scan systems and exploit a single weak point. AI-assisted coding accelerates malware development AI-assisted coding tools—often described as “vibe coding”—are becoming a major driver of change in cybercrime. These tools can generate working software code from simple prompts, helping developers build applications faster. But the same capability is now being exploited by cybercriminals to create malicious programs with far less effort than before. In the past, writing malware required advanced technical skills and weeks or months of work to design programs that could infiltrate systems and evade antivirus detection. AI tools have lowered that barrier dramatically. Attackers can now generate key malware components, such as “loaders”—small programs that enter a victim’s computer and download additional malicious software—in just seconds. Even when the AI-generated code is imperfect, attackers can quickly modify it or produce many variations until one works. Each version appears slightly different to security systems, making it harder for traditional antivirus tools that rely on known malware signatures to detect them. This constant variation acts like a digital disguise, allowing some attacks to slip through defenses—something reflected in HP’s findings that 14% of email threats in late 2025 bypassed at least one email security scanner before being stopped. The rise of modular “flat-pack” malware Another trend highlighted in the HP report is the rise of modular malware kits, sometimes called “flat-pack malware.” Instead of building malicious software entirely from scratch, attackers now assemble it from pre-built components available online. These modules can include loaders, credential-stealing tools, ransomware functions, and command-and-control systems. By combining different pieces, cybercriminals can quickly create customised malware packages for specific campaigns. Automated coding tools make this even easier by generating scripts that connect the modules or help disguise them from security systems. This modular approach lowers the technical barrier to launching cyberattacks. People with limited programming knowledge can assemble working malware using components purchased or downloaded from underground forums. As a result, the number of potential attackers is growing rapidly, making the cybersecurity landscape more complex and unpredictable. Brand mimicry and the rise of digital “evil twins” While automated coding helps attackers build malware faster, they still rely heavily on deception to persuade victims to install it. One of the most effective techniques highlighted in the HP report involves brand mimicry. Cybercriminals are becoming increasingly adept at creating fake websites that closely resemble legitimate platforms used by millions of people. Services such as Microsoft Teams, Zoom, and Booking.com are common targets because users trust them and frequently download their software. Attackers replicate these sites with remarkable precision. Logos, colors, layouts, and even the wording used on official pages are copied to create convincing “evil twin” versions of the real websites. In the Microsoft Teams “Piggyback” campaign (2025–2026), hackers used SEO poisoning to manipulate search results so that anyone searching for “download Microsoft Teams” was directed to a fake website that looked
Read MoreBitcoin—and most other digital assets—promise cheap, fast cross-border payments. But there’s a catch: you need a smartphone and internet access to use them. In much of Africa, where millions of people still use feature phones, that design shuts them out. Kgothatso Ngako, a South African software engineer and former Amazon Web Services (AWS) developer, founded Machankura in 2022 to solve this design flaw. The startup allows people to send and receive Bitcoin using the Unstructured Supplementary Service Data (USSD) technology, the same short-code system Africans use to check airtime, transfer mobile money, or query their account balance in traditional banking. Machankura’s mobile-first approach targets Africa’s vast base of feature phone users. In 2024, the continent counted 710 million unique mobile subscribers, yet only 416 million—28% of the population—used mobile internet, according to GSMA’s “The Mobile Economy Africa 2025” report. About 860 million Africans remain offline, constrained by device cost, expensive data, and limited digital skills. This divide persists despite growing smartphone purchases. A report by Omdia, a global research firm, found that smartphones accounted for 55% of all mobile handset shipments in 2025, leaving feature phones at about 45%. For hundreds of millions of Africans who can dial a short code but not download an app, smartphone-built digital asset platforms remain out of reach. Using Machankura, a user dials a local code from any phone—feature or smartphone. A text-based menu appears. They can create a wallet linked to their phone number, check their balance, or send Bitcoin, without needing an app or internet connection. The ambition is to do for Bitcoin what M-PESA did for payments: embed it into a technology that hundreds of millions of Africans already use daily, Noelyne Sumba, Machankura’s Director of Operations, said in an interview with TechCabal. “USSD is already familiar,” she said. “People use it every day for financial services. We are extending that to Bitcoin.” Who uses Machankura and how Machankura operates in Côte d’Ivoire, South Africa, Kenya, Ghana, Malawi, Zambia, Nigeria, Namibia, Tanzania, and Uganda. In each country, users dial a local USSD code to access their wallet. The service is now connected to over 39,000 phones, including feature devices, according to Sumba. Yet, the user base is not evenly distributed. Adoption is concentrated in urban and peri-urban areas, and primarily among younger, digitally-aware users, aged 35 and below, who understand crypto but may lack the devices or data to use conventional wallets. “It’s the young people who are mostly tech-savvy, but because either they cannot afford internet connectivity, or most of them have feature phones, it’s very easy for us to onboard them,” said Sumba. “I’ll be more than happy to get to the older generations, but it will take a while.” Beyond peer-to-peer (P2P) transfers, Machankura users spend Bitcoin through a network of partner platforms connected via the Lightning Network. In Kenya, users can send Bitcoin from their Machankura wallet to Tando, which converts it into M-PESA credit, allowing them to pay for goods and services at zero transaction fees on Tando’s end. In South Africa, MoneyBadger, a local off-ramp partner, has integrated the Lightning Network into its point-of-sale (PoS) system; through a recent partnership with Scan to Pay, it now covers over 650,000 merchant locations, including major retailers like Pick n Pay. Users can also purchase airtime, data, and digital vouchers through services like Bitrefill. Sumba cites examples of daily use: In Kisii, a town in western Kenya, members of Bitcoin Chama use feature phones to transact in Bitcoin for everyday purchases. In Kibera, Nairobi’s largest informal settlement, the Afribit project has onboarded 2,600 residents into a similar circular economy where merchants accept Bitcoin and participants earn satoshis through community work programmes. In South Africa’s Mossel Bay, Bitcoin Ekasi pays all staff salaries entirely in Bitcoin and has onboarded local shops to accept it. “These are the circular economies we’re building for,” said Sumba. “We want that local mama mbogas [female vegetable sellers] to be able to say, ‘You know what, you can still pay me in Bitcoin.’” Since its launch, the startup has processed over 19 Bitcoins (BTC) in total transaction volume across its markets, according to Sumba. At current market prices, that’s over $1.2 million in routed value. How Machankura works Machankura sits between two distinct infrastructure layers: Africa’s telecom networks and the Bitcoin Lightning Network. On the telecom side, when a user dials the Machankura code, the request travels through the mobile network to Africa’s Talking, a communications application programming interface (API) provider that offers USSD connectivity across African mobile operators. Africa’s Talking routes the session to Machankura’s servers. The user then interacts with a real-time, session-based text menu limited to 160 characters per prompt and timed to 20 seconds per response. For most of its markets—Ghana, Kenya, Malawi, Namibia, Nigeria, and Zambia—Machankura uses Africa’s Talking as its aggregator. In Côte d’Ivoire, Tanzania, and Uganda, local providers handle the USSD integration due to regulatory constraints. “They [Africa’s Talking] were very open to working with us,” said Sumba. “Thanks to Africa’s Talking, we were able to have the service in as many countries as possible. Even when we kicked off operations, we started with all the countries we could integrate into.” USSD infrastructure carries real costs. In Nigeria, acquiring a USSD code through Africa’s Talking costs ₦200,000 ($145), with a monthly maintenance fee of ₦70,000 ($51) plus value-added tax (VAT); per-session charges vary by carrier. In Kenya, a Safaricom setup runs KES 145,000 ($1,122) with KES 70,000 ($542) monthly maintenance. These are fixed costs that Machankura bears regardless of transaction volume, an important consideration for a startup processing micro-value transactions. For users with smartphones and internet access but limited technical skills, Machankura also offers a WhatsApp-based interface as an alternative channel. On the Bitcoin side, Machankura connects to the Lightning Network, a second-layer protocol built on top of the Bitcoin blockchain. Lightning allows near-instant, low-cost transactions by routing payments through channels between nodes, rather than recording every small transfer directly on the base chain. Machankura runs
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