Learn about Security Risks
In the Learn section, you’ll explore a wide range of online security risks, from phishing and malware to AI-driven threats and data privacy concerns. As our digital lives grow more complex, staying informed is your first line of defense. Use the sections below to dive into each topic, empowering yourself with knowledge to protect your personal information, devices, and digital identity.
Click each section below to learn more.
Human-Driven Threats
Phishing
- It is a type of cyberattack where attackers impersonate legitimate organizations or individuals to trick people into revealing sensitive information, such as passwords, credit card numbers, or personal details.
- Phishing is by far one of the most common threats we face in the online world. This is often done through deceptive emails, messages, or fake websites that appear trustworthy and can lead to identity theft, financial loss, or unauthorized access to accounts. The most common method phishers use to access your data is through links in emails or messages. Clicking on such links allow hackers to immediately infiltrate your device and steal all of your personal data. Such emails often come in the form of asking you to reset a password with a link to do so, references to finance and payments, or a subject line of “Request”, “Follow up”, or “Urgent”. The email itself will ask for private information such as your Social Security Number, house address, credit card details, or login details to a site/service.
Cyberbullying
- It is a form of bullying that takes place online. Unlike traditional bullying, cyberbullying can happen 24/7, and usually anonymously.
- It can occur on any online platform, such as social media, gaming communities, or any other online spaces. Cyberbullying often involves harassment, sending hateful or threatening comments or messages, spreading rumors, sharing embarrassing content of another person with the intent to shame, and excluding other from online groups and conversations, all of which can harm a person’s mental and emotional wellbeing.
Online predators
- They are individuals who use the internet to sexually exploit and manipulate others, often targeting minors.
- They are typically found on social media, gaming platforms, and chat rooms under fake profiles made to build trust with their victims by hiding and lying about their identity. Through tactics like grooming, flattery, and gift-giving, predators form connections with their targets; once trust is established, they exploit minors by pressuring them into sending sexually explicit photos or videos of themselves, which are then used as blackmail. This form of predation in specific is known as sextortion, where predators will use that blackmail material to force the victim to comply to future demands such as meeting in person or giving them personal information like addresses, phone numbers, and passwords, all of which they can then use for stalking or further exploitation, not just of the victim but also their family and friends.
Doxing
- It is the internet practice of revealing a person’s private information online.
- It is usually done with the intent to intimidate, get revenge or retaliate, or harass the victim, and can lead to damages to the person’s reputation, or more severe consequences like identity theft, stalking, or physical harm. Doxers gather information to expose people through social media, public records, phishing, and data breaches.
Identity theft
- It occurs when someone steals and uses your personal information, such as your name, address, Social Security Number, banking information, etc., for online activity like opening new accounts on different platforms, use your existing accounts, commit financial fraud, or impersonate you online.
- Cybercriminals can obtain such information through both online methods and in person. Online thieves can steal your information through phishing emails, cyberstalking, public Wi-Fi network attacks, or data breaches; in-person criminals resort to stealing purses and wallets to get IDs and credit cards, going through trash to find bank statements and tax documents, or install skimmers, devices attached to ATMs and other card readers to steal card details.
Social engineering
- It is a type of cyberattack that doesn’t rely on hacking software but instead uses psychological tricks to manipulate you into giving away personal information.
- Attackers pretend to be someone you trust—a friend, a teacher, a tech support agent, or even a representative from a company you know—and use that trust to convince you to share passwords, security codes, or other private details. They might create a sense of urgency by claiming your account is at risk or pressure you to act quickly so you don’t have time to think or ask questions. These tactics are designed to lower your guard and make you feel comfortable handing over information you normally wouldn’t share. Social engineering can happen through phone calls, text messages, emails, or social media messages, and it’s a leading way hackers gain access to accounts without needing to crack passwords.
Technical Threats
Keylogging
- It is short for keystroke logging, is a type of cyberattack where a malicious program or device records every keystroke a user types on their keyboard.
- Cybercriminals often use keyloggers to steal sensitive information like passwords, credit card numbers, and personal messages. Keyloggers can be installed through phishing emails, malicious software downloads, or physical hardware devices connected to a computer. The biggest warning signs of keylogging include unusual mouse or keyboard behavior, such as your mouse disappearing or jumping around or your keyboard typing characters you didn’t intend, and system slowdowns and overall performance issues.
Malware/Ransomware
- It it short for “malicious software,” malware is any intrusive software downloaded onto your computer by a cybercriminal, or hacker, with the intent to damage the computer’s system, steal data, or gain unauthorized access into your system.
- Malware can be downloaded through various methods, including:
- Email attachments and links, such as phishing emails
- Infected websites, like fake or compromised sites, that trigger software downloads
- Fake software downloads, such as free or pirated software, games, or apps offered by hackers that contain hidden malware
- Infected online advertisements
- Fake software updates that prompt you to urgently download an update that is actually a hidden malware
- Infected USB devices or other external drives
- There are many different types of malware, the most common types being:
- Viruses, which are programs that attach to files and spread when opened
- Worms, a self-replicating malware that spreads without user interaction
- Trojan Horse, a software disguised to look legitimate to trick users into downloading it
- Ransomware, which encrypts, or prevents access to, your data and demands payment for its release
- Spyware, which secretly monitors your activity and collects information
AI and Emerging Digital Threats
AI Dependency
- As AI usage becomes more and more normalized as a means of searching for information and conducting research, people face an overreliance on AI.
- AI dependency is visible as users accept AI-generated content as true without fact-checking or doing any basic research of their own, leading to gaps in information and errors in the work users are doing solely using AI. This also affects cognitive abilities such as decision making and critical thinking, as people begin to rely on AI to think for them.
- This issue is particularly prevalent among students as they begin to use AI to write essays, complete research projects, and finish day-to-day homework assignments. While at the time it may seem like an easy shortcut to getting work done, the long term impacts of using AI in place of learning will be academically debilitating as students cease developing or completely lose the ability to do higher level thinking, make decisions, and form opinions on their own. Additionally, as we become more trusting towards AI we are left vulnerable to security breaches and privacy risks. Many companies with popularly used AIs lack transparency with their users, failing to inform them about their methods of private data collection or concealing them within complex algorithms.
Deepfakes
- They are images, videos, or audio recordings that have been digitally altered or generated using AI.
- While photo-editing technology and fake images have been around for years, deepfakes pose a greater threat because they can be incredibly realistic, making it difficult, and sometimes nearly impossible, to distinguish them from real media. Today, the majority of people get information about the current world through the internet and use that content to form opinions on various matters. If consumers receive fake content—for example an AI-generated video of a politician delivering a speech and stating made-up claims—they can be seriously mislead, spread misinformation, and allow their opinions and decisions to be influenced by an event that never happened or a statement that was never made.
AI bias
- It occurs when artificial intelligence systems produce unfair or inaccurate outcomes because of the data they are trained on.
- AI systems learn by analyzing massive amounts of data—sometimes millions or even billions of examples—from various sources like websites, books, images, and user interactions. However, if this data reflects existing human biases, stereotypes, or inequalities, the AI can absorb and repeat those same problems. For example, if the training data overrepresents one group or contains prejudiced language, the AI’s decisions may unfairly favor that group while placing others at a disadvantage. Additionally, when the data lacks diversity or only shows limited viewpoints, the AI cannot understand or represent the full range of human experiences. This can cause the AI system to make biased choices in important areas like job hiring, loan approvals, facial recognition, or content recommendations. Because AI relies so heavily on the data it’s given, ensuring that data is varied, balanced, and free from prejudice is critical to building fair and trustworthy AI systems.
Data privacy
- AI systems require hundreds of billions of petabytes of data to be trained, using a mix of public data, licensed or purchased data, user-provided data, and, in some cases, scraped personal data (taken without consent).
- Some companies gather terabytes of data per day from solely user behavior. The issue arises when these companies fail to inform users about when their data is being collected and how it is being used, leaving them unaware of possible threats such as their data being sold. Not only that, but as AI tools become more advanced, they can piece together full detailed profiles of individuals which are frequently shared, sold, or repurposed by companies. This places us at risk of identity theft, targeted scams, and other misuse of our stolen data.