Portrait of a Victim 2026: Not Randomness, but Targeted Selection. How Leaked Data Maps Digital Vulnerabilities.

[Professor]

Victim Profile: Who and Why Do Systems and Carders Target? A Leak Data Analysis​

Victim selection in modern carding and fraud isn't a lottery. It's a process based on data analysis, profiling, and risk assessment on both sides: by automated carding systems and retailers' anti-fraud algorithms. Massive data leaks have given cybercriminals unprecedented opportunities for microtargeting, turning each of us into a set of parameters with a cost/risk assessment.

How Carders Choose Their Victims: Criteria for the "Ideal" Target​

Based on an analysis of leaked databases (Colonial Pipeline, AdultFriendFinder, Russian databases) and forum practices, a profile of the priority target can be developed.

1. Demographics and financial solvency:

• Age: 35-55. The sweet spot: already has a stable income and credit history, but is less digitally literate than Generation Z.
• Geography: Residents of the United States, Western Europe, Canada, and Australia. Reason: high income levels, developed e-commerce, and liberal return policies from retailers (making refunds easier).
• Credit score: "Good" and "Excellent" (FICO 670+). These people have higher credit limits, loan approvals, and appear more reliable to store fraud detection systems.
• Profession and income: Leaked data allows filtering by salary, employer, and job title. The target is people with above-average incomes, but not the super-rich (whose protections are complex).

2. Digital behavior and the "vulnerable" footprint:

• Purchase patterns: Active buyers in certain categories — electronics, luxury clothing, and home goods. Their accounts are "warm," which reduces anti-fraud suspicions.
• Use of "convenient" features: People who save cards in store accounts, use one-time passwords (SMS 2FA), have simple passwords found in leaks.
• Presence in multiple leaks: If a person's email and password appear in 3-5 different leaked databases, this indicates poor digital hygiene and a high probability of successful phishing or account hacking.

3. Social and psychological markers (identified through OSINT):

• Social media activity: A large number of posts and photos revealing lifestyle, work schedule, and vacations (convenient for BEC attacks).
• Contact publication: Open phone number, email.
• Mentions of older relatives or children: Makes a person a potential target for shimming (fraud with relatives).

How anti-fraud systems "select" victims (for increased scrutiny)​

Paradoxically, security systems also create a "victim profile" — a user at high risk of fraud. These are the people who fall under the following filters:

• "Cold" accounts: New user, recently registered.
• Inconsistent data: Young age but high income; address in a poor area but purchases luxury goods.
• Risky patterns: Using VPN/proxy, anti-detection browsers (systems are learning to detect them), quickly changing profile data.
• Chargeback history: Even one chargeback in the past dramatically increases the risk score.

Leaked Data Analysis: What's Valuable for Targeting?​

Leaks aren't just a list of passwords. They're the raw material for building multidimensional profiles.

• Credit bureau databases (like Experian, Equifax): the Holy Grail. They contain SSN/TIN, credit history, addresses, employment information, and account numbers. They allow you to fully reconstruct a person's financial identity for loans or high-limit cards.
• Retailer databases:Purchase history, preferences, sizes, delivery addresses. Allows:
  1. Imitate a legitimate buyer when carding, making orders that are typical for this person.
  2. Conduct targeted phishing ("Dear customer, we have a problem with your order from [date]...").
• Social networks and dating services: Photos, interests, connections, intimate preferences. Used for blackmail, extortion, and deep phishing.
• Medical databases: Disease and insurance data. Ideal for medical and insurance fraud.

The modern process of victim selection (using carding as an example)​

1. Primary screening: The carder goes to a specialized forum and buys a dump of "fresh" fullz, filtered by the criteria: country=US, credit_score>700, age=30-50.
2. Verification and enrichment: Using OSINT (social media search by first/last name/city), it verifies whether a person is "alive" and enriches their profile. It also searches for their phone number (often in the same leaks).
3. "Ease" check: A card checker (card checker) silently checks whether a card is active and what its limit is. Methods used are invisible to the bank (for example, micro-donations).
4. Contextualization for the attack: A store and product are selected based on a specific person and their card. If the leaked history shows they purchased expensive electronics, the order is made for a MacBook, not children's toys. The delivery address is chosen as close as possible to the victim's actual address (from credit bureau leaks).

Who is NOT a priority victim (relatively safe)?​

• People with a low credit score or no credit history. They have low limits and are more likely to be rejected.
• Residents of countries with strict anti-fraud policies and weak logistics (many countries in Asia and Africa). Low margins.
• "Digital ascetics": People with a minimal online presence, who don't use online banking or store their cards in stores. They are simply difficult to find and attack remotely.
• The super-rich and public figures: They are being attacked, but not by mass carders, but by targeted groups (APTs). The protection is too strong.

Conclusion: We are all data in an Excel spreadsheet on a dark forum.​

The 2026 victim profile is a statistical model, not a specific person. Carders aren't looking for individuals, but rather for sets of parameters with the highest probability of success and return on investment.

The key takeaway for the average person: Your security isn't determined by "why someone specifically wants you," but by how well your digital profile matches the "optimal" attack parameters. The more "statistically average" you are in a developed country, the more active you are online, and the wealthier you are, the higher the likelihood that you'll be targeted by an automated or semi-automated attack.

Defense, therefore, isn't about "hiding," but rather about making your profile unprofitable for attack:

1. Use a password manager and unique passwords for each service (so that a leak in one doesn't compromise all).
2. Enable two-factor authentication (2FA) wherever possible, using authenticator apps or hardware keys instead of SMS.
3. Minimize your digital footprint: Don't disclose your income on social media, don't use a public phone number, and limit your friend list.
4. Freeze your credit with a bureau (in the US, it's called a Credit Freeze) to prevent anyone from opening a new loan in your name without your knowledge.

Ultimately, the victim profile is a mirror of our digital behavior. The more convenient we are for digital services (saving data, buying with one click), the more convenient we become for those who decide to deceive them. Security is a conscious choice between convenience and risk, and in 2026, the cost of this choice is higher than ever.