Genetic portrait of an operation: How analysts learn to identify carder "schools" based on attack style

[Professor]

Idea: An art history analogy. How threat intelligence specialists see patterns in phishing emails, vulnerability selection, and cash-out methods, thereby identifying entire groups.

Introduction: Forensics in the Digital World​

In a quiet museum hall, an art historian bends over a painting. Without looking at the signature, he says, "This is undoubtedly a Van Gogh. See these brushstrokes, this palette, this play of light? It's his signature." In another room, lit by the cold glow of monitors, a threat analyst studies an attack log. He sees the structure of a phishing email, the code of a malicious script, the pattern of network activity, and says, "This is the Fin7 group. See this domain template, this evasion technique, this data collection server? It's their signature."

Welcome to the world of digital art history, where instead of paintings there are cyberattacks, and instead of artists there are carding gangs. Each of them, like a talented or untalented but unique creator, leaves their mark, their style, their genetic code at the scene of the "crime." The ability to read this code is the highest art of threat intelligence analytics, transforming the chaos of incidents into a clear map of a hostile landscape.

Chapter 1: The Anatomy of a "Signature" – What Makes Up a Band's Style​

A carder's signature style isn't random. It's the sum of a group's technical capabilities, cultural background, experience, and even its internal economics. Just as an artist has favorite colors and themes, a carder has preferences.

1. Technical "brush": tools and codes.

• Phishing constructors: One group uses a ready-made "A" kit, another writes their own scripts from scratch, and a third adapts open-source projects. An analyst examining the HTML code of a fake page can find unique comments, specific file paths, or errors specific to a particular tool.
• Malware: Trojan families (e.g., Carbanak, Anunak) have unique signatures, encryption algorithms, and methods of communicating with the command and control (C&C) server. It's like a recognizable drawing style.
• Infrastructure: Preferred hosting providers, domain registrars, proxy server geolocations. Some groups prefer Turkish hosting, others prefer Panamanian hosting, and still others use clouds in the Netherlands.

2. Composition and plot: attack scenario.

• Phishing legend: One "school" always pretends to be bank security, threatening to block your account. Another pretends to be Netflix tech support, offering a refund. A third sends "delivery notifications." The subject matter, vocabulary, and tone of the email — all reflect the author's style.
• Multi-step: A sequence of actions. First, do they steal cookies, then logins, then a test translation, and only then the main one? Or do they work in a rush? This is the plotline by which the author can be identified.

3. Aesthetics of execution: details that the master gives away.

• Quality of the fake (UX/UI): Some groups create perfect, pixel-perfect replicas of bank websites. Others create crude fakes, designed to appeal to the inattentive. Still others specialize in mobile versions.
• Errors and typos: Ironically, unique grammatical errors in an email or on a phishing page can become a signature feature. It's like an artist having a favorite, slightly crooked letter.
• Timing and rhythm: Does the group attack during business hours Moscow time? Or at night GMT? Do they send out mass emails once a week or conduct targeted attacks every day? This is the rhythm and temporality of their signature.

Chapter 2: Schools of Digital Art: Examples of Unique Styles​

Let's consider hypothetical, but based on real observations, "schools.

" "School of Engineering Elegance" (Conventionally: "Architects").

• Signature Style: Proprietary, well-written tools. Minimal noise. Attacks target systems, not people (for example, exploiting vulnerabilities in banking APIs). Phishing, if present, is characterized by impeccable design and technically sound, emotionless copy.
• "Genetic marker": A debug line containing a humorous comment or pop culture reference may be left in the malware's code, acting as a kind of author's signature.
• Analogy in art: High Renaissance. Raphael. Technical perfection, clarity of concept, harmony.

"School of Social Theatre" (Conventionally: "Playwrights").

• Handwriting: The main weapon is social engineering. Call center scripts are written like plays, with dialogue, pauses, and plot twists. Phishing emails create a strong sense of urgency or greed.
• "Genetic Marker": Unique turns of phrase and cover stories. For example, they always introduce themselves as "an employee of the Federal Financial Monitoring Service" or play out a scenario of "a child's card being blocked abroad."
• Analogy in art: Baroque. Caravaggio. Emotionality, theatricality, play on the contrasts of light and shadow (fear and hope).

"School of the Industrial Conveyor Belt" (Conventionally: "Factory Workers").

• The style: Mass production and automation. They use readily available phishing kits, purchase databases, and launch large waves of attacks. The execution quality is average, but the scale compensates for this.
• "Genetic marker": Similar, serial second-level domains (for example, bank-support[number].com), template email texts, purchased in bulk.
• Analogy in art: Pop Art. Andy Warhol. Serial production, circulation, use of ready-made templates.

Chapter 3: How a Crime Lab Works: From Sign to Portrait​

Threat Intelligence analysts act like detectives, collecting evidence.

1. Collecting artifacts: Any element of an attack — a file, an email, an IP address, a hash — is “evidence.”
2. Clustering and matching: Using systems (such as MITRE ATT&CK), artifacts are categorized by tactics and techniques. If two different attacks on different banks use the same rare technique (for example, a specific traffic obfuscation method) and the same phishing template, this indicates a single author.
3. Hypothesis building (Threat Actor Profile): Based on the clusters, a hypothetical profile is formed: probable geography (by operating time, error language), level of technical training, goals (card theft, access to transactions), possible connections with known groups.
4. Open-source intelligence (OSINT): Verifying hypotheses through analysis of leaks from hacker forums, domain registration data, and social media activity.

The result is not simply the statement "there was an attack," but a precise statement: "This was a targeted attack by group X, using tools Y, with infrastructure Z, and they are likely planning their next action N." This allows us to move from defense to prediction.

Chapter 4: Why? From Tactics to Strategy​

Defining a "school" isn't an academic exercise. It's key to effective defense.

• Proactive Defense: Knowing the group's pattern allows us to predict its next steps and build a proactive defense. If the "Playwrights" group is active, we strengthen call center training specifically on their scenarios. If the "Architects" group is active, we patch specific API vulnerabilities.
• Operational response (Hunting): You can search your networks not for abstract threats, but for specific indicators of compromise (IoC) specific to a given group.
• Enforcement and Deterrence: Clear attribution allows law enforcement to target specific groups and their infrastructure.
• Understanding Threat Evolution: By observing how a group's signature style changes (for example, the Fabricants begin using more sophisticated tools), one can understand general trends in cybercrime.

Conclusion: Every stroke tells a story​

Karting isn't a faceless stream of evil. It's a landscape populated by vibrant, recognizable characters, each with their own story, ambitions, and methods. The ability to see this human (or group) factor behind soulless code and automated messaging is the highest form of cybersecurity mastery.

An analyst reading the genetic portrait of an operation is simultaneously an art historian, a forensic scientist, and a strategist. They understand that every attack is a message — a message about weaknesses others have identified. And their task is not simply to read this message, but to understand the language it's written in, so they can craft their own, impenetrable defense in response.

Thus, carder "schools" teach us the most important thing: in a digital confrontation, the winner is not the one with more resources, but the one who understands the enemy better. Who sees in the attack not chaos, but structure. Not an anonymous threat, but a familiar signature. And in this deep understanding is born not only security, but also a kind of respect for the complexity and ingenuity of that very dark digital art, which, whether we like it or not, is part of our shared technological history.