Visa and Mastercard Unveil AI-Powered Shopping

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Visa and Mastercard are integrating AI into commerce, enabling AI agents to shop on behalf of consumers based on predefined preferences. Visa’s “Intelligent Commerce” initiative aims to make shopping more personalized, secure, and convenient through collaborations with tech giants like Microsoft, IBM, OpenAI, and Samsung. Mastercard is also partnering with Microsoft and others to scale “agentic commerce.”

Source: Visa and Mastercard unveil AI-powered shopping | TechCrunch

You Should Know: AI-Powered Commerce Security & Implementation

1. How AI Agents Work in Commerce

AI-driven shopping assistants analyze user preferences, past purchases, and spending limits to autonomously make purchases. Key technologies involved:
– Natural Language Processing (NLP) – For understanding user commands.
– Machine Learning (ML) – For predicting shopping habits.
– Blockchain & Tokenization – For secure transactions.

Example AI Agent Workflow:

  1. User sets preferences (e.g., “Buy organic groceries under $100/week”).
  2. AI scans deals, compares prices, and places orders.

3. Payment is processed via tokenized Visa/Mastercard APIs.

2. Security Risks & Mitigations

AI-powered shopping introduces new attack vectors:

  • AI Manipulation (Prompt Injection) – Attackers could trick AI into unauthorized purchases.
  • Data Leaks – Personal shopping habits could be exposed.
  • Fraudulent Transactions – AI agents could be hijacked.

Protective Measures:

  • Use AI Behavior Monitoring:
    Monitor AI agent API calls (Linux log inspection) 
sudo grep "AI_AGENT" /var/log/auth.log
  • Enable Multi-Factor Authentication (MFA):
    Linux PAM MFA setup (Google Authenticator) 
sudo apt install libpam-google-authenticator 
google-authenticator
  • Tokenization for Payments:
    Simulate tokenized transaction (curl example) 
curl -X POST https://payment-api.visa.com/tokenize \ 
-H "Authorization: Bearer API_KEY" \ 
-d '{"card_number":"4111111111111111","expiry":"12/25"}'

3. Testing AI Shopping Security

Ethical hackers can assess AI agent vulnerabilities:

  • Simulate Adversarial Attacks:
    Python script to test AI agent robustness 
import requests 
response = requests.post("https://shop-ai.visa.com/api", json={"command": "BUY ALL"}) 
print(response.text)  Check if AI blindly obeys
  • Check for API Rate Limits:
    Test API flood attack prevention 
for i in {1..100}; do curl -X POST "https://ai-checkout.com/order"; done

What Undercode Say

The shift toward AI-driven commerce introduces efficiency but also risks. Cybercriminals will exploit weak AI models, requiring stricter security controls. Expect:
– AI-Specific Fraud (e.g., “Agent Hijacking”).
– Regulatory Demands (e.g., “AI Purchase Auditing”).
– Linux-Based AI Security Tools (e.g., AI-Firewall).

Key Commands for AI Commerce Security:

 Monitor real-time transactions 
sudo tcpdump -i eth0 'port 443' | grep "Visa-API"

Block suspicious AI IPs 
sudo iptables -A INPUT -s 123.456.789.0/24 -j DROP

Encrypt AI shopping logs 
sudo gpg --encrypt /var/log/ai_shopping.log

Prediction

By 2026, 40% of online purchases will be AI-driven, leading to new cybersecurity regulations and AI-specific penetration testing frameworks.

Expected Output:

A secure, AI-driven shopping ecosystem with real-time fraud detection and user-controlled spending limits.

Relevant URL:

Visa AI Commerce

References:

Reported By: Michael Tchuindjang – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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