In a landscape where cyber threats evolve faster than most organizations can adapt, Mayank Chauhan operates at the critical intersection of technical precision and executive decision-making. His philosophy is simple but powerful: every vulnerability is ultimately a business risk, and every remediation is an investment in organizational resilience.
Rather than communicating in abstractions, Mayank translates complex attack vectors and threat intelligence into narratives that resonate with boards, regulators, and business leaders alike — enabling faster, smarter risk decisions across the enterprise.
In the Indian financial services sector, regulatory compliance is not a checkbox — it is a continuous operational posture. Mayank has led technical defense strategies through two of the most demanding audit frameworks in the industry: the Reserve Bank of India (RBI) cybersecurity framework and the ISO 27001 information security management standard.
His approach goes beyond preparation. By building controls that are audit-native — documented, tested, and continuously monitored — his teams enter every examination with confidence, not apprehension. The result: zero critical findings and sustained certification.
Defended technical controls under India's apex banking regulator scrutiny.
Maintained ISMS controls through rigorous third-party certification audits.
Aligned with India's Computer Emergency Response Team (CERT-In) directives, ensuring timely incident reporting and adherence to national cybersecurity mandates.
Security programs architected around NIST Cybersecurity Framework (CSF) and MITRE ATT&CK, enabling structured threat modeling, gap analysis, and adversary-aligned defense strategies.
Mayank's intellectual contributions extend well beyond the console. His research on Machine Learning in Intrusion Detection Systems (IDS) — published through Springer — examines how adaptive ML models can fundamentally change the speed and accuracy of threat identification in complex network environments.
His work on Onion Routing and anonymization networks contributes to the broader discourse on privacy-preserving architectures and their implications for both defenders and adversaries. This dual-perspective research informs the way he designs detection and response strategies in production environments.
Springer publication on adaptive machine learning for network intrusion detection.
Research on anonymization protocols and their security implications.
AVP, VAPT @ SBI Cards · Security Architect · CEH & CISM Certified