
5 Biggest cyberattacks in history that changed the digital security landscape forever
cyberattacks
in very concrete ways. These cyberattacks can vary from mere disruption to devastating intrusion with economic losses, loss of reputation, and compromised national security.
What is a cyberattack
A cyberattack refers to a deliberate and malicious effort to compromise, harm, disrupt, or steal data from a computer system, network, or device. Such attacks are often conducted by hackers, cybercriminals, or even state actors to realise any number of objectives, including stealing confidential information, causing operational interference, or inflicting monetary damage.
Types of cyber attacks
by Taboola
by Taboola
Sponsored Links
Sponsored Links
Promoted Links
Promoted Links
You May Like
Sulawesi Selatan: AI guru Andrew Ng recommends: Read These 5 Books And Turn Your Life Aroun...
Blinkist: Andrew Ng's Reading List
Undo
The two broad
types of cyberattacks
are those targeting disruption of system and network operations, and those targeting access to sensitive data. An awareness of these types contributes to enhancing defense systems.
Disabling attacks
These are meant to take a computer, network, or system offline, essentially cutting access for those who are authorized to use it. Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) are good illustrations. They overwhelm a network with questionable traffic or requests that leave the system unable to handle it and, in the process, crash. Disruption is their primary goal and not theft of information.
Data theft and data breaches
The second largest category is efforts to steal confidential data. It can be financial data, private data, intellectual property, or state secrets. Phishing, malware, and exploitation of systems are familiar methods used by hackers to acquire unauthorized access to systems. After acquisition, burglars resell looted data or use it for criminal intentions, e.g., identity fraud or corporate espionage.
Common hacker techniques
Hackers employ an array of advanced methods and tools for mounting their cyber attacks. Hackers' favorite means are:
Malware
Malware is an umbrella term that refers to any type of bad code with the potential to infect a system and cause mayhem. Viruses, worms, trojans, ransomware, and spyware are a few of the most common types of malware. Malware can steal data, bring down systems, or even hold information for ransom and demand money for its freedom (in ransomware attacks).
Phishing
Phishing is a social engineering attack in which the attackers pretend to be genuine organizations or entities with a purpose of duping the victims into sharing sensitive information such as passwords, usernames, or financial details. Phishing attacks normally are email or imitation websites in nature, coming across as actual websites but rather made for trapping users' information on being clicked.
Social engineering
In social engineering attacks, people are used by hackers to leak sensitive information. They can also pose as coworkers or supervisors for the purpose of gaining the confidence of an individual and trick the victim into lowering security protocols such as revealing log-in details or clicking on unsafe links.
Group attacks
Large-scale cyberattacks are often launched by well-coordinated groups of hackers. The groups will target high-profile entities or government organizations and apply complex methods, including advanced persistent threats (APTs), in order to acquire persistence over a long period.
Growth of cybercrime
Cybercrime is a quick-growing enterprise. In 2017, it lost 780,000 records daily through various cyberattacks, McAfee's Economic Impact of Cyber Crime recorded. The figures indicate the numbers and volumes of cyberattacks mounting. According to the reports, cybercrime is estimated at $10.5 trillion by 2025.
E-mail is still among the most popular attack vectors despite heightened cybersecurity. CSO research indicates that 92% of malware is transmitted through e-mail, most commonly by a malicious link or an attachment within a phishing e-mail. The attackers take advantage of the human factor by tricking people into opening the mail, which in turn leads to unintentional installation of malware on their systems.
Major cyberattacks in the history
In recent years, there have been a number of high-profile cyberattacks that have hit the headlines, detailing just how sophisticated cyber thugs are getting and what security breaches can entail.
Morris Worm (1988)
The Morris Worm was the very first ever recorded mass cyberattack. Written by Robert Tappan Morris, at the time an academic at the graduate level, the worm infects computers at a rapid pace across the net and infects around 6,000 computers. Estimated loss resulting from this worm is anywhere from $10 million to $100 million, giving rise to the added concern about systems that are vulnerable on the net.
MafiaBoy (2000)
One of these 15-year-old Canadian hackers, MafiaBoy, in 2000 launched a DDoS attack on busy websites such as Amazon, CNN, eBay, and Yahoo!. The attack harvested around $1.7 billion worth of losses. The attack highlighted just how simple it is even for novice hackers to make significant disruption using the international internet network.
Google China (2009)
Google's servers were hacked by the hackers in 2009 to access Chinese human rights activists' e-mails. The hacking was believed to have been carried out by China's government, and thus Google shifted its servers to Hong Kong in 2010 as part of its battle against censorship and surveillance.
Jonathan James and the U.S. Department of Defense (1999)
Jonathan James, a computer hacker at age 15, infiltrated the U.S. Department of Defense computers and stole sensitive data, including NASA software worth $1.7 million. The breach resulted in damages of $41,000 and demonstrated that even the most secure government networks could be compromised.
Stuxnet (2010)
The Stuxnet worm was an enormously advanced cyberweapon that attacked the nuclear enrichment facilities of Iran. It dismantled almost 1,000 nuclear centrifuges, slowing down Iran's nuclear ambitions. It is believed widely to have been an American Israeli joint effort, the first use of a cyberattack causing physical damage.
Most famous recent cyber attacks
Cyberattacks do not only affect operational and technical aspects, but they also lead to humongous economic loss. For example, the Melissa Virus was a cost of $1.1 billion in damages worldwide. Furthermore, data breaches, such as when Albert Gonzalez hacked millions of credit card numbers in 2009, were part of one of the biggest history-making credit card scams.
Cyberattacks just keep on rolling, and there are new cyberattacks daily. Some of the most famous recent cyberattacks include:
U.S. Treasury Department Incident (2024)
U.S. Treasury Department networks were attacked in December 2024 by a state-sponsored Chinese attacker, who penetrated employee desktops and sensitive data. The incident was ranked as a high event, which illustrated the threat level of state-sponsored cyber tapping and its impact on national security.
North Korean Crypto Hack (2025)
North Korean cyberthieves hacked into a cryptocurrency exchange and stole $1.5 billion worth of digital currency in the largest cyberattack on record in 2025. This hack illustrates the growing necessity of safeguarding digital assets as attacks mount from highly funded and highly advanced cybercrime.
Also Read |
Elon Musk look-alike rejects comparison, calls him 'not a nice person'; reveals his unwanted fame
AI Masterclass for Students. Upskill Young Ones Today!– Join Now

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


Hindustan Times
31 minutes ago
- Hindustan Times
Companies tried using AI to cut costs. Now they're paying humans to fix its errors
When artificial intelligence became the biggest buzzword in tech, companies hoped it would help them slash headcount and save money. Instead, companies that rushed to replace staff with AI are now rehiring humans to fix its mistakes – and spending a fortune in the process. How using AI to cut costs has backfired for some companies (iStock) According to a BBC report, there is a burgeoning industry for software engineers and writers who are being hired to fix the mistakes made by AI. The trouble with AI Take the example of Sarah Skidd. When a content agency reached out to Sarah Skidd in May, they were in a bind. The website copy they had commissioned from a generative AI tool for a hospitality client wasn't up to the mark — and they needed it rewritten urgently. "It was the kind of copy that you typically see in AI copy – just very basic; it wasn't interesting," Skidd explained. "It was supposed to sell and intrigue but instead it was very vanilla." Skidd, a product marketing manager in Arizona who writes for tech and start-up companies, took 20 hours to rewrite the copy from scratch. At her usual rate of $100 an hour, the agency ended up paying $2,000. Skidd isn't worried about AI replacing her. In fact, it's giving her more business. "Maybe I'm being naive, but I think if you are very good, you won't have trouble," she told BBC. The rise of AI She's not alone. Many writers she knows are now being hired not to create new content, but to fix the errors AI-generated text leaves behind. Over the past few years, AI tools like ChatGPT and Google Gemini have become popular in business circles, seen as ways to streamline workflows and cut down costs. A recent survey by the UK's Federation of Small Businesses found that 35% of small firms plan to expand their AI use within two years. But Skidd's experience, and those of others like her, suggests that there may still be a long way to go before AI can match up to human standards. Sophie Warner, co-owner of Hampshire-based digital marketing agency Create Designs, says that in the last six to eight months, there has been an increase in the number of clients who want to fix the mess created by AI. "Before clients would message us if they were having issues with their site or wanted to introduce new functionality," Warner told BBC. "Now they are going to ChatGPT first." But adding code generated by ChatGPT has made some websites prone to crashing and vulnerable to attacks. In one case, a client asked ChatGPT how to update their event page – something Warner says would have taken just 15 minutes manually. But instead, the AI-generated code caused their website to crash, costing the business three days of downtime and about £360 in recovery costs. "We often have to charge an investigation fee to find out what has gone wrong, as they don't want to admit it, and the process of correcting these mistakes takes much longer than if professionals had been consulted from the beginning," said Warner.


Hindustan Times
31 minutes ago
- Hindustan Times
ChatGPT image generation guide: 5 common mistakes to avoid for AI photo editing
ChatGPT, the powerful AI-powered chatbot, has gained several new capabilities over the years, and one of the most hyped features is AI image generation. The chatbot utilises the new GPT-4o model to generate or edit AI images based on user prompts. Recently, we also saw ChatGPT's image generation trends like Ghibli-style art, Pixar characters, and baby images getting viral on the internet. While the tool is fun and useful for creative professionals, many are unaware of the right ways to utilise ChatGPT's image generation capabilities. Therefore, we have listed five common mistakes to avoid while editing images using ChatGPT's image generation model. Here are 5 mistakes to avoid while generating or editing images using ChatGPT's image generation tool.(AP) Also read: ChatGPT now lets you download Deep Research reports as PDFs - here's how 5 mistakes to avoid while editing images on ChatGPT ChatGPT's image generation tool is quite intuitive, but sometimes it generates unusual visuals, which can be frustrating. There are several instances when ChatGPT confuses numbers with fingers, analyses texts, or simply generates inconsistent backgrounds that do not look pleasing. While it can be a part of AI hallucination, the user prompt also plays a greater role in AI to analyse and generate the desired images. Therefore, if you want to generate high-quality images with desired animations and greater accuracy, then avoid these 5 listed mistakes when using ChatGPT's image generation tool for photo editing: 1. If you are editing any image, avoid using vague prompts like 'make the background better' or 'make the object cooler.' The best way of image generation is to be specific with prompts. Provide ChatGPT when what changes you want, such as ' Add soft and golden-pink sunset to the background and make it look cinematic.' 2. Make sure to add image resolution, as it gives ChatGPT a better idea. If you are generating images for Instagram, YouTube, or any other social media, then make sure to provide resolutions. Simply add 'Generate a 1200×628 horizontal image' to your prompt. Also read: How to use ChatGPT to colourise old black-and-white images: Step-by-step guide 3. Do not avoid visual elements, as they play a key role in making your image look pleasing. Adding visual cues to prompts such as photorealistic, 3D style, bokeh background, colour tones, and others could refine AI image generation and will also add depth to your image. 4. ChatGPT does not generate celebrity or brand logos or any copyrighted form of image. Therefore, you have to be clever with prompts. Therefore, you have to be imaginative with prompts and avoid giving ChatGPT a direct prompt to any movie scene or celebrity name. 5. Focus on refinements of the AI-generated image by making follow-up prompts, as many tend to avoid minor edits. Play with your imagination, add facial expressions, additional objects, cinematic backgrounds, and others to make the image look visually appealing. Mobile Finder: Oppo Reno 14 Pro LATEST specs, features, and price


Time of India
31 minutes ago
- Time of India
Foxconn second quarter revenue rises 15.82% on year
Taiwan's Foxconn , the world's largest contract electronics maker, reported record second-quarter revenue on strong demand for artificial intelligence products but cautioned about geopolitical and exchange rate headwinds. Revenue for Apple 's biggest iPhone assembler jumped 15.82% year-on-year to T$1.797 trillion, Foxconn said in a statement on Saturday, beating the T$1.7896 trillion LSEG SmartEstimate, which gives greater weight to forecasts from analysts who are more consistently accurate. Robust AI demand led to strong revenue growth for its cloud and networking products division, said Foxconn, whose customers include AI chip firm Nvidia. Smart consumer electronics, which includes iPhones, posted 'flattish' year-on-year revenue growth affected by exchange rates, it said. June revenue roses 10.09% on year to T$540.237 billion, a record high for that month. Foxconn said it anticipates growth in this quarter from the previous three months and from the same period last year but cautioned about potential risks to growth. "The impact of evolving global political and economic conditions and exchange rate changes will need continued close monitoring," it said without elaborating. U.S. President Donald Trump said he had signed letters to 12 countries outlining the various tariff levels they would face on goods they export to the United States, with the "take it or leave it" offers to be sent out on Monday. The Chinese city of Zhengzhou is home to the world's largest iPhone manufacturing facility, operated by Foxconn. The company, formally called Hon Hai Precision Industry, does not provide numerical forecasts. It will report full second quarter earnings on August 14. Foxconn's shares jumped 76% last year, far outperforming the 28.5% rise for the Taiwan market, but are down 12.5% so far this year, reflecting broader pressure on tech stocks rattled by Trump's tumultuous trade policy. The stock closed down 1.83% on Friday ahead of the revenue data release, compared with a 0.73% drop for the benchmark index.