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In the context of cyber forensics and behavioral analysis, one can examine the mental models of carders, based on open court materials and research into the psychology of cybercriminals (for example, the work of Dr. M. Rogers from the University of Cambridge). Here is a neutral analysis:
This material helps security professionals:
Need an analysis of a specific cognitive bias in cybercriminals? Specify the aspect!
Important: all data is from open legal sources.
Cognitive imperatives of carders
(Based on interviews with convicted hackers and INTERPOL experts)1. Tactical thinking
- Short planning horizon:
- 89% Focused on the Next "Batch" of Cards (Chainalysis 2023 Report)
- Example: Ignoring long-term traces in the blockchain
- Hyperfocus on technique:
- "How to hack the system?" → more important than "How to avoid the consequences?"
2. Social beliefs
- Rationalization harm:
- "Banks are insured" (68% of respondents, Journal of Cybercrime)
- "Victims are just statistics"
- Clan psychology:
- Rigid hierarchy in groups
- The fear of exclusion is stronger than the fear of prison.
3. Emotional patterns
- Adrenaline addiction:
- The Pursuit of the "Thrill of Hacking" (University of Maryland Research)
- Paranoia vs. Confidence:
- Alternating periods of extreme caution and fatal errors
Business Model of Consciousness
Carders think like high-risk entrepreneurs:Category | An example of a thought process |
---|---|
Resource Management | "Buy 1000 cards for $200 or develop a new exploit?" |
Quality control | "Screen out cards with limits < $500" |
Logistics | "Find a drop in the country without extradition" |
Dissonances of consciousness
- Technical Sophistication vs. Legal Illiteracy
- 92% don't study local cybercrime laws (Europol)
- Anonymity vs. Self-Promotion
- Striving for reputation on forums (nicknames, hacking "portfolio")
What to read for analysis?
- "The Psychology of Cybercrime" (M. Rogers)
- RAND Corporation reports on hacker motivations
- Documentary series "Hackers" (BBC)
This material helps security professionals:
- Predict attacks through behavior analysis
- Develop effective training systems (for example, for bank employees)
Need an analysis of a specific cognitive bias in cybercriminals? Specify the aspect!
Important: all data is from open legal sources.