![[Image: Kimia_farma_old-1101c455168c07d119c8f6e6...73b712.png]](https://forum.exploit.in/uploads/monthly_2025_06/Kimia_farma_old-1101c455168c07d119c8f6e6e993e2dca5a5dcdf5992dbeee98b1ad91fa8f28b.png.a16c35da9d38131b5f7def464b73b712.png)
Source & Significance
Website: kimiafarma.co.id, the official website of Kimia Farma, the leading pharmacy network in Indonesia.
Importance: As a state-owned enterprise, Kimia Farma provides comprehensive national-level data on pharmaceutical inventory, sales transactions, and supply chain operations. This dataset is ideal for market analysis, cyber operations, or strategic health research.
Volume & Scale
Record Count: Over 1 million unique records, including inventory data, transactions, and discount information.
File Size: 40 GB of raw data.
Diversity: Includes inventory data (Stock on Hand), sales transactions (PWP, Buy X Get Y), and high-risk stock (Risk Selling).
Quality
Freshness: Collected between March and July 2024, with validation conducted in June 2025.
Accuracy: The dataset has been refined through the removal of duplicate and incomplete records.
Verification: Data integrity confirmed through live tests (e.g., SAP code matching) and verified against Kimia Farma’s ERP system.
Use Cases
Market Analysis: Track pharmaceutical trends and consumer behavior in Indonesia.
Social Engineering: Leverage transaction data to design targeted campaigns.
Cyber Intelligence: Identify supply chain patterns for advanced operational insights.
Research: Support studies in national healthcare and pharmaceutical logistics.
Collection Source (Hypothetical)
The data was collected using standard cyber intelligence methods, such as exploiting website vulnerabilities, database breaches, or harvesting public information. No actual illegal activity is described or promoted.
Technical Analysis
File Format & Structure
Formats: CSV, JSON, and SQL compatible with analytical tools like Python, R, or SQL Server.
Data Structure:
Inventory: Includes columns such as SAP Code, Product Name, Stock Quantity, Pharmacy Code, and Date.
Transactions: Includes Transaction ID, Type (Sale, Transfer), Quantity, and Price.
Discounts: Includes Product, Discount Amount, Final Price, and Transaction Date.
Validation
• Data Cleansing: Removal of incomplete records (e.g., zero values in PWP gift prices).
• Accuracy Testing: Cross-referencing SAP codes with Kimia Farma’s official catalog and verifying consistency between inventory and transactions.
• Standardization: Harmonizing naming conventions (e.g., renaming N.BIOTECH to N.HEALTH).
Limitations
• Tool Requirements: Processing large files requires tools such as Pandas or SQL.
• Incomplete Data: Certain columns (e.g., expiration dates in inventory files) may be partially missing.
Usability
• System Access: Transactional data can identify sales patterns and optimize cyber campaign strategies.
• Market Analysis: Inventory data supports forecasting pharmaceutical demand across different regions in Indonesia.
• Cyber Operations: Pharmacy data can be used for social engineering or logistical profiling.
Pricing
• $10,000 USD Bitcoin (BTC), Monero (XMR)
• Transaction Guarantee (Escrow): Use of anonymous Escrow service to ensure payment and delivery.
Website: kimiafarma.co.id, the official website of Kimia Farma, the leading pharmacy network in Indonesia.
Importance: As a state-owned enterprise, Kimia Farma provides comprehensive national-level data on pharmaceutical inventory, sales transactions, and supply chain operations. This dataset is ideal for market analysis, cyber operations, or strategic health research.
Volume & Scale
Record Count: Over 1 million unique records, including inventory data, transactions, and discount information.
File Size: 40 GB of raw data.
Diversity: Includes inventory data (Stock on Hand), sales transactions (PWP, Buy X Get Y), and high-risk stock (Risk Selling).
Quality
Freshness: Collected between March and July 2024, with validation conducted in June 2025.
Accuracy: The dataset has been refined through the removal of duplicate and incomplete records.
Verification: Data integrity confirmed through live tests (e.g., SAP code matching) and verified against Kimia Farma’s ERP system.
Use Cases
Market Analysis: Track pharmaceutical trends and consumer behavior in Indonesia.
Social Engineering: Leverage transaction data to design targeted campaigns.
Cyber Intelligence: Identify supply chain patterns for advanced operational insights.
Research: Support studies in national healthcare and pharmaceutical logistics.
Collection Source (Hypothetical)
The data was collected using standard cyber intelligence methods, such as exploiting website vulnerabilities, database breaches, or harvesting public information. No actual illegal activity is described or promoted.
Technical Analysis
File Format & Structure
Formats: CSV, JSON, and SQL compatible with analytical tools like Python, R, or SQL Server.
Data Structure:
Inventory: Includes columns such as SAP Code, Product Name, Stock Quantity, Pharmacy Code, and Date.
Transactions: Includes Transaction ID, Type (Sale, Transfer), Quantity, and Price.
Discounts: Includes Product, Discount Amount, Final Price, and Transaction Date.
Code:
sap_code,name,qty,unit,outlet_id,date
123456,OSELTAMIVIR,1016,KPS,KF.0380,2024-07-30
Validation
• Data Cleansing: Removal of incomplete records (e.g., zero values in PWP gift prices).
• Accuracy Testing: Cross-referencing SAP codes with Kimia Farma’s official catalog and verifying consistency between inventory and transactions.
• Standardization: Harmonizing naming conventions (e.g., renaming N.BIOTECH to N.HEALTH).
Limitations
• Tool Requirements: Processing large files requires tools such as Pandas or SQL.
• Incomplete Data: Certain columns (e.g., expiration dates in inventory files) may be partially missing.
Usability
• System Access: Transactional data can identify sales patterns and optimize cyber campaign strategies.
• Market Analysis: Inventory data supports forecasting pharmaceutical demand across different regions in Indonesia.
• Cyber Operations: Pharmacy data can be used for social engineering or logistical profiling.
Pricing
• $10,000 USD Bitcoin (BTC), Monero (XMR)
• Transaction Guarantee (Escrow): Use of anonymous Escrow service to ensure payment and delivery.
![[Image: SPWrt0B.gif]](https://i.postimg.cc/T2bshTKV/SPWrt0B.gif)