Before further digging into smishing scams, a small quiz can be done to self-test whether you’re scam-wise.
Imagine a situation: You receive a text message on your smartphone, saying as below:
“USPS: the arranged delivery for the shipment 1z26054 has been changed. Please confirm here: w7fzc.info/fU1JAWimUB”
That reminds you that you’ve just bought a dress you’ve been expecting for a long time and its package is to arrive recently. You can’t wait to be wearing it. Then, will you click the link in the text message to check the changed delivery date?
Sadly, if you click the link in the text message, you’ll fall for a smishing scam in which scammers hook you to click the malicious link via an evil text message that totally looks like it is from official USPS customer service.
Nowadays, millions of people around the world suffer from economic or personal information losses via smishing scams and the number still keeps rising. Fortunately, with OpenAI, it’s easy to spot dodgy texts and protect against smishing scams.
How AI Helps Identify Smishing Scams?
The term “smishing” is a combination of the words “SMS” (Short Message Service) and “phishing” (a type of online scam). In smishing scams, criminals send text messages that appear to be from a legitimate source, such as a bank, government agency, or popular retailer. The messages often contain urgent requests or warnings, urging the recipient to take immediate action, such as clicking on a link or replying with personal information.
AI plays a crucial role in identifying and combating smishing scams, which are fraudulent attempts to deceive individuals through text messages. Below is how AI helps in this context.
Text analysis
AI-powered algorithms analyze the content of text messages to identify potential smishing scams. These algorithms use natural language processing (NLP) techniques to analyze keywords, phrases, and patterns commonly associated with phishing attempts. They can flag suspicious messages based on known scam templates or linguistic indicators of fraudulent intent.
In addition, as AI is used to scan text message content, users won’t need to worry about their privacy leaks since no people or organizations are needed in such an activity. Without the participation of humans, the risk of privacy leaks will be lowered.
Link and URL analysis
AI can analyze the legitimacy and validity of links and URLs embedded in text messages to determine if they lead to malicious websites. AI algorithms can compare the provided link against a database of known phishing URLs or employ machine learning models trained on historical data to identify potential phishing domains. Mostly, the embedded links and URLs look so similar to those from official sources that ordinary people fail to tell them apart. Suspicious links can be flagged, preventing users from clicking on them and falling victim to phishing attacks.
Sender analysis
AI algorithms can assess the credibility of the senders by analyzing various factors like their caller IDs. They may consider the sender’s phone number, message frequency, geolocation, and behavioral patterns. By comparing these factors with known indicators of smishing scams, AI can identify suspicious senders and alert users accordingly.
However, caller ID spoofing may make it difficult for AI alone to identify potential risks. That’s why RealCall Blocklist is established and constantly updated. RealCall Blocklist is a phone number database including risky phone numbers from across carriers, with any area code from any country, together with the reported data from official organizations like FTC. RealCall AI can be referred to as RealCall Blocklist plus AI.
Behavioral analysis
AI systems can learn from users’ interactions and behaviors to detect smishing attempts. By analyzing patterns and anomalies in users’ responses to text messages, AI algorithms can identify potential phishing attempts. For example, if a user suddenly starts receiving a high volume of unsolicited messages containing suspicious content, AI can raise an alert and prompt the user to be cautious.
Collaborative intelligence
AI systems can leverage collective intelligence to improve smishing detection. By using machine learning models, they can aggregate data from multiple sources, such as user reports, security databases, and threat intelligence feeds. This collaborative approach enhances the accuracy and effectiveness of smishing detection systems, allowing them to adapt and respond to emerging smishing techniques.
Real-time protection
AI systems can provide real-time protection by analyzing incoming text messages on users’ devices. With on-device AI models, users can receive immediate warnings about potential smishing scams. This proactive approach helps users avoid clicking on malicious links or providing sensitive information to scammers.
Overall, AI enhances the capabilities of security systems to detect and prevent smishing scams by analyzing text content, URLs, sender information, and user behavior and leveraging collective intelligence. It contributes to creating a safer digital environment by alerting users to potential risks and helping them make informed decisions when interacting with text messages.
What Type of Smishing Scam Types Can AI Identify?
AI can identify various types of smishing scams based on their characteristics and patterns. Here are some common types of smishing scams that AI can help detect:
Financial Services Smishing
Financial service smishing refers to a specific type of smishing scam that targets individuals through text messages purporting to be from financial service providers, such as banks, credit card companies, or investment firms. The messages may ask for personal information, such as account numbers, passwords, or social security numbers, under the guise of updating security protocols preventing fraud, or even reminding you to change account information for more online privacy protections.
The fraudulent messages may also urge the recipient to click on a link or call a phone number to resolve an urgent issue, such as a suspicious transaction or account lockdown. These links and phone numbers may lead to fake websites or automated phone systems that are designed to collect personal and financial information from unsuspecting victims.
Gift Card Smishing
Are you crazy about gift cards? If you’re, you’re unfortunately risky to fall for scams.
After all, scammers favor gift cards.
Gift card smishing is a type of smishing scam that preys on individuals’ desire to receive free or discounted gift cards from popular retailers or restaurants. In these scams, individuals receive unsolicited text messages or emails that appear to be from legitimate companies offering free or discounted gift cards in exchange for personal information or participation in surveys.
The messages may instruct recipients to click on a link to claim their gift card or to reply with personal information such as their name, address, phone number, or credit card details. In some cases, the link may lead to a fake website that looks like a legitimate retailer’s website but is designed to collect personal and financial information from victims.
Once the scammers obtain this information, they can use it for identity theft, financial fraud, or selling it on the dark web.
Invoice or Order Confirmation Smishing
Invoice or order confirmation smishing is a type of smishing scam that targets businesses and individuals who make online purchases. In these scams, individuals receive unsolicited text messages or emails that appear to be from legitimate companies confirming a recent purchase or invoice payment.
The messages may instruct the recipients to click on a link or download an attachment to view the invoice or order confirmation. In some cases, the link or attachment may lead to a fake website or malware that is designed to steal personal and financial information from the victim’s device.
Once the scammers obtain this information, they can use it for identity theft, financial fraud, or selling it on the dark web.
Customer or Tech Support Smishing
Customer or tech support smishing is a type of smishing scam that targets individuals by posing as customer support representatives from legitimate companies. In these scams, individuals receive unsolicited text messages or emails that appear to be from a legitimate company’s customer support team, asking for personal or account information.
The messages may instruct the recipient to click on a link to verify their account or to provide sensitive information such as their login credentials, social security number, or credit card details. In some cases, the link may lead to a fake website that looks like a legitimate company’s website but is designed to collect personal and financial information from victims.
How to Use AI to Protect Against Smishing Scams?
To use AI effectively in protecting against smishing scams, consider the following steps:
Choose AI-powered security solutions
Look for mobile security apps or messaging platforms that incorporate AI-based anti-phishing and smishing protection features. These solutions utilize AI algorithms to analyze text messages, links, sender information, and user behavior for detecting and preventing smishing scams.
RealCall AI, powered by GPT-4 by OpenAI, provides the optimal solution for identifying and blocking spam and scam calls and texts. Moreover, it’s also the world’s first blocking solution with AI.
Enable AI-powered filtering
Make sure to enable spam filters or anti-phishing settings provided by your messaging app or mobile device. These filters leverage AI algorithms to automatically identify and filter out potential smishing messages before they reach your inbox.
Stay updated
Keep your mobile apps, operating systems, and security software up to date. AI algorithms often evolve to address new smishing techniques, and software updates typically include security patches to protect against emerging threats. Regularly check for updates and install them promptly.
Report suspicious messages
If you receive a smishing message, report it to your mobile service provider and forward the message to the appropriate authorities, such as your local law enforcement or anti-fraud organizations. Reporting helps in tracking and taking action against scammers.
Be cautious of unfamiliar senders
Be skeptical of text messages from unknown or unfamiliar senders. AI algorithms can assist in analyzing sender information, such as phone numbers or behavioral patterns, to determine their credibility. If in doubt, refrain from responding or taking any action until you can verify the legitimacy of the message through other means.
Avoid clicking on suspicious links
Be cautious when encountering links in text messages, especially from unknown or suspicious sources. AI algorithms can help analyze links or URLs to identify potentially malicious websites. If you are unsure about the legitimacy of a link, refrain from clicking on it and consider verifying its authenticity through other trusted channels.
Educate yourself
Stay informed about the latest smishing techniques and scams. Familiarize yourself with common characteristics and red flags of smishing messages. AI-powered security blogs, websites, or forums can provide valuable insights and tips to help you recognize and protect yourself against smishing scams. Bookmark RealCall Blog and follow RealCall AI Twitter and RealCall AI Facebook to get the latest scam alert and avoidance tips.
Be vigilant and trust your instincts
Even with AI protection, it’s essential to remain vigilant and trust your instincts when encountering text messages. If something seems too good to be true, asks for sensitive information, or raises suspicion, it’s better to err on the side of caution and refrain from engaging further.
Remember, while AI can enhance your protection against smishing scams, it’s crucial to adopt a multi-layered security approach that combines AI technology with personal awareness, education, and best practices to stay safe from fraudulent activities.