CRED’s Saksham Tushar on Data Enrichment for Effective Threat Detection
Sep 4, 2024
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Saksham Tushar, the Head of Security Operations & Threat Detection Engineering at CRED, dives into the intricacies of compliance in a fast-paced tech environment. He discusses how CRED streamlines complex compliance requirements and leverages automation to enhance threat detection. Saksham highlights the importance of verifying automated outcomes and using Python libraries for swift incident investigations. Additionally, he emphasizes the need for contextual understanding of security incidents and the integration of threat intelligence to create a robust security operations framework.
CRED addresses complex compliance challenges by simplifying requirements into manageable standards, ensuring efficient security processes and regulations adherence.
The use of centralized threat intelligence and automated data enrichment significantly enhances incident response and the overall effectiveness of security operations.
Deep dives
Overview of Cred and Security Operations
Cred is one of the largest fintech companies in India, offering a reward-based credit card bill payment app designed to incentivize good financial behaviors. The app has multiple lines of businesses focused on managing finance and bill payments, which necessitates robust security measures. The security operations team, led by Saksham Tushar, focuses on threat management ranging from threat intelligence (CTI) to forensic investigations. This comprehensive approach ensures that the entire lifecycle of threats is addressed effectively.
Compliance-Driven Security Framework
The development of security operations at Cred was largely informed by the need to comply with extensive regulations faced by fintech organizations in India. The strategy began by identifying key compliance requirements, allowing the team to streamline necessary security measures while ensuring they meet audit standards. Foundational security practices prioritized include 24/7 monitoring and anti-malware protections, which serve as essential components of their security framework. Additionally, the establishment of maturity models helps assess automation capabilities and further enhance their security posture.
Advanced Threat Detection and Utilization of Data
Cred employs a sophisticated data management strategy that involves centralizing various forms of data in cloud storage, allowing for effective threat detection and incident response. The use of an Elastic Common Schema aids in normalizing diverse log data, ensuring that only relevant information is ingested for analysis while retaining access to extensive historical data. Inline and SIM enrichment processes are employed to enhance the quality of data used in threat hunting and incident investigation. Additionally, programming with tools like Jupyter notebooks has streamlined the analytical process, allowing for efficient correlation and investigation of complex security incidents.
In this episode of Detection at Scale, Jack speaks with Saksham Tushar, Head of Security Operations & Threat Detection Engineering at CRED, about the challenges of compliance in a high-growth environment. Saksham shares their strategy for automating security processes and enriching data to enhance threat detection.
He emphasizes the importance of verifying automated outcomes to ensure accuracy. Saksham also covers how CRED uses Python libraries for efficient incident response and the significance of contextual understanding in security incidents. With a focus on streamlining compliance and leveraging intelligence, Saksham provides valuable insights into building a robust security operations framework in a rapidly evolving landscape.
Topics discussed:
How CRED distilled complex compliance requirements into a manageable set of common standards to streamline processes.
The importance of correlating various log sources to create a comprehensive view of security incidents.
How automation has transformed security processes, making them more efficient and effective.
The use of threat intelligence and how it is centralized and automated to provide actionable insights for security teams.
The development of internal Python libraries that facilitate quick data queries for incident investigations.
The importance of understanding the context around security incidents to better inform responses and strategies.
How using notebooks for investigations aids in communication and auditing, allowing for clear documentation of processes.
How to organize a team to maintain agility while ensuring diverse skill sets are leveraged effectively.
The necessity of verifying automated processes to ensure they yield accurate and actionable outcomes.