CVE-2019-9864 in Amazon Affiliate Store
Summary
by MITRE
PHP Scripts Mall Amazon Affiliate Store 2.1.6 allows Parameter Tampering of the payment amount.
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Analysis
by VulDB Data Team • 08/17/2023
The vulnerability identified as CVE-2019-9864 affects PHP Scripts Mall Amazon Affiliate Store version 2.1.6, representing a critical parameter tampering issue that directly impacts financial transaction integrity. This flaw resides in the payment processing mechanism where the application fails to properly validate or sanitize user-supplied parameters, specifically those related to payment amounts. The vulnerability stems from insufficient input validation and inadequate parameter handling within the affiliate store's payment processing pipeline, creating an attack surface where malicious actors can manipulate transaction values without proper authorization. Such parameter tampering represents a significant security weakness that undermines the trust and integrity of financial transactions within the platform.
The technical implementation of this vulnerability allows attackers to modify payment amount parameters during the checkout process, potentially enabling unauthorized financial gain through methods such as reducing payment amounts or redirecting funds to attacker-controlled accounts. The flaw occurs when the application accepts user input for payment calculations without proper sanitization or cryptographic verification, making it susceptible to manipulation through direct parameter modification in web requests. This type of vulnerability typically falls under CWE-20, which describes improper input validation, and can be categorized as a form of injection attack that affects the integrity of financial data processing. The vulnerability may also be classified under ATT&CK technique T1555.003, which covers credentials from password files, particularly when the tampering affects authentication tokens or transaction parameters that validate payment legitimacy.
The operational impact of this vulnerability extends beyond simple financial loss, potentially compromising the entire affiliate marketing ecosystem built around the platform. Attackers could manipulate transaction values to receive unauthorized commissions, redirect payments to their own accounts, or create fraudulent transactions that would be difficult to trace through traditional audit mechanisms. The vulnerability affects the trust relationship between merchants, affiliates, and customers, as it undermines the reliability of payment processing and could lead to significant financial losses for legitimate business partners. Organizations using this software may face regulatory compliance issues, as the vulnerability creates potential exposure to fraud and financial irregularities that could violate payment card industry standards and financial auditing requirements. The impact is particularly severe for e-commerce platforms where transaction integrity is paramount, as this vulnerability essentially allows for unauthorized financial modification during the payment lifecycle.
Mitigation strategies for CVE-2019-9864 should focus on implementing robust parameter validation, input sanitization, and cryptographic verification mechanisms within the payment processing flow. Organizations should deploy proper parameter validation routines that ensure all transaction values are verified against expected ranges and formats before processing. The implementation of server-side validation controls, including cryptographic signatures for payment parameters, would prevent unauthorized modifications to transaction data. Additionally, organizations should consider implementing transaction logging and monitoring systems that can detect unusual parameter modifications or payment discrepancies. Security patches should be applied immediately to update the software to versions that address the parameter tampering vulnerability, while also implementing network segmentation and access controls to limit exposure. Regular security assessments and penetration testing should be conducted to identify similar vulnerabilities in related systems, as this type of flaw often indicates broader input validation weaknesses that may exist elsewhere in the application architecture.