From Prevention to Protection: Safeguarding Companies and Class Action Administrators in the Breach Lifecycle
1h 3m
Created on September 30, 2025
Intermediate
Overview
Cyberattacks are on the rise-and class actions are prime targets. This CLE explores how cyber threats impact every stage of the class action lifecycle, from breach to settlement. From initial incident response to settlement distribution, every phase of a class action is vulnerable to sophisticated attacks, including impersonation schemes, wire fraud, and AI-driven scams. Attendees will learn how to identify vulnerabilities, navigate legal and ethical risks, and implement practical strategies to protect sensitive data and preserve case integrity.
Learning Objectives:
- Identify and assess the latest cybersecurity threats impacting class action litigation, including current breach statistics, trends in targeted attacks, and industry sectors most vulnerable to cybercriminal activity
- Recognize key vulnerabilities across the entire class action lifecycle-from the initial data breach through litigation and settlement administration-and how these vulnerabilities can be exploited by threat actors
- Breakdown the legal and ethical obligations related to data security in class action practice, including compliance with professional responsibility rules such as ABA Model Rule 1.6, court expectations around disclosure and data handling, and how failing to meet these obligations can expose counsel and their clients to significant legal liability
- Evaluate the limitations of cybersecurity insurance coverage by analyzing common exclusions, gaps in protection, and policy ambiguities
- Implement practical and proactive cybersecurity protocols throughout the litigation and settlement process, including strategies for incident response, internal risk management, secure data transfer, and vendor due diligence
- Anticipate and prepare for emerging cybersecurity threats, including increasingly sophisticated social engineering attacks, deepfakes, and the use of generative AI in fraudulent claim submission or impersonation
Credits
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