Citation:

Piyush Ranjan, Akhil Khunger, Chalamayya Batchu Veera Venkata Satya, Sumit Dahiya, 2022. "Threat Modeling and Risk Assessment of APIs in Fintech Applications" ESP Journal of Engineering & Technology Advancements  2(2): 44-61.

Abstract:

The proliferation of Fintech applications has dramatically transformed the financial services industry, offering unprecedented levels of convenience, efficiency, and accessibility to consumers and businesses alike. This transformation is largely driven by the extensive use of Application Programming Interfaces (APIs), which enable seamless integration and communication between diverse financial systems and services. However, the increased reliance on APIs has concurrently introduced significant security challenges, necessitating a deeper examination and robust approach to securing these critical interfaces. This paper presents a comprehensive framework for threat modeling and risk assessment specifically tailored to APIs in Fintech applications. We delve into the unique security risks inherent to Fintech APIs, such as data breaches, unauthorized access, injection attacks, and denial of service (DoS) attacks, and examine the evolving threat landscape that poses continual challenges to financial data security. Through a methodical analysis of current threats and vulnerabilities, we propose effective mitigation strategies, including technical controls like encryption, multi-factor authentication, and rate limiting, alongside organizational measures such as security policies, employee training, and incident response planning. The paper incorporates detailed case studies, such as the Capital One data breach and the Plaid API vulnerability, to illustrate the real-world implications of API security failures and the necessity of rigorous security practices. Empirical analysis further underscores the critical importance of implementing robust API security measures to protect sensitive financial information and maintain consumer trust. By systematically identifying and addressing potential threats, this framework aims to enhance the security posture of Fintech applications, ensuring their resilience against cyber-attacks and fostering a secure environment for financial transactions. In conclusion, as Fintech continues to innovate and expand, the imperative for strong API security becomes ever more crucial to safeguard financial data and uphold the integrity and reliability of financial services in the digital age.

References:

[1] Jha, A., & Sharma, R. A risk assessment of fintech adoption in the Indian financial services industry. Developments and trends in the banking and finance sector, 66.

[2] The Importance of API Security for Protecting Financial Cloud Apps, fintechweekly, online. https://www.fintechweekly.com/magazine/articles/the-importance-of-api-security-for-protecting-financial-cloud-apps

[3] Fintech API: Everything You Need to Know, yellow systems, online. https://yellow.systems/blog/fintech-apis

[4] Chakraborty, S. (2018). Fintech: Evolution or Revolution, Business analytics research lab India.

[5] OWASP. (2020). OWASP API Security Top 10. Online. https://owasp.org/www-project-api-security/

[6] Shostack, A. (2014). Threat modeling: Designing for security. John Wiley & Sons.

[7] Microsoft. (2005). The STRIDE Threat Model. Online. https://docs.microsoft.com/en-us/previous-versions/commerce-server/ee823878(v=cs.20)

[8] National Institute of Standards and Technology (NIST). (2012). NIST SP 800-30: Guide for Conducting Risk Assessments. Online. https://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-30r1.pdf

[9] International Organization for Standardization (ISO). (2022). ISO/IEC 27005: Information Security Risk Management. Online. https://www.iso.org/standard/80585.html

[10] Capital One. (2019). Cyber Incident. Online. https://www.capitalone.com/facts2019/

[11] What Is Threat Modeling?, cisco, online. https://www.cisco.com/c/en/us/products/security/what-is-threat-modeling.html

[12] Protecting FinTech APIs, Salt, online. https://content.salt.security/rs/352-UXR-417/images/SaltSecurity-SolutionBrief-ProtectingFinTechAPIs.pdf

[13] Threat Modeling, fortinet, online. https://www.fortinet.com/resources/cyberglossary/threat-modeling

[14] Xiong, W., & Lagerström, R. (2019). Threat modeling–A systematic literature review. Computers & Security, 84, 53-69.

[15] Shevchenko, N., Chick, T. A., O’Riordan, P., Scanlon, T. P., & Woody, C. (2018). Threat modeling: a summary of available methods. Software Engineering Institute| Carnegie Mellon University.

[16] Saini, V., Duan, Q., & Paruchuri, V. (2008). Threat modeling using attack trees. Journal of Computing Sciences in Colleges, 23(4), 124-131.

[17] Threat Modeling Methodology: STRIDE, iriusrisk, online. https://www.iriusrisk.com/resources-blog/threat-modeling-methodology-stride

[18] DREAD Threat Modeling: An Introduction to Qualitative Risk Analysisk, ECcouncil cybersecurity-Exchange, online. https://www.eccouncil.org/cybersecurity-exchange/threat-intelligence/dread-threat-modeling-intro/

[19] Threat Identification, warditsecurity, online. https://warditsecurity.com/threat-identification/

[20] Fintech risk management: Strategies for success, BPM, online. https://www.bpm.com/insights/fintech-risk-management/

[21] Risk Management And Financial Technology: Strategies for Success, dashdevs, online. https://dashdevs.com/blog/risk-management-in-fintech-strategies-for-success-dashdevs/

[22] Matt High, Threat identification: cybersecurity and user experience, 2020. Online. https://fintechmagazine.com/venture-capital/threat-identification-cybersecurity-and-user-experience

Keywords:

Fintech, Apis, Threat Modeling, Risk Assessment, Cybersecurity, Financial Services, API Security, Mitigation Strategies, Consumer Trust.