Financial services companies are increasingly becoming prime targets for Advanced Persistent Threats (APTs)—highly sophisticated cyberattacks that often persist over an extended period. APTs focus on infiltrating systems, stealing sensitive financial data, and even manipulating stock trading mechanisms. These attacks are typically stealthy, designed to remain undetected while cybercriminals achieve their objectives, which could include long-term espionage or financial gain. Given the complexity and persistence of APTs, traditional cybersecurity measures are often inadequate. To defend against these threats, financial institutions must adopt a comprehensive and proactive cybersecurity approach.
Advanced Threat Detection and Monitoring
APTs are known for their stealth, often going unnoticed for months or even years. Financial services companies must implement advanced threat detection systems capable of identifying anomalous behaviors and flagging potential intrusions early. Tools such as Security Information and Event Management (SIEM) and Intrusion Detection Systems (IDS) can help monitor network traffic, detect unusual patterns, and alert security teams to potential threats before they escalate.
In addition to real-time monitoring, behavioral analysis and machine learning algorithms should be integrated to detect subtle deviations in user or system behavior. These tools can uncover even the most sophisticated APTs by recognizing long-term patterns that may indicate an ongoing attack.
Network Segmentation and Least Privilege Access
To prevent APTs from spreading across a company’s network once inside, financial institutions should implement network segmentation. By dividing the network into isolated segments, companies can contain an attack to one area, preventing attackers from moving laterally and accessing sensitive systems, such as trading platforms or customer databases.
Moreover, least privilege access should be enforced. This principle ensures that users only have access to the systems and data necessary for their roles. Limiting access makes it more difficult for attackers to reach valuable assets even if they successfully infiltrate one part of the network.
Regular Patch Management and Software Updates
APTs often exploit zero-day vulnerabilities or unpatched software flaws to gain entry into systems. Financial services companies must maintain a rigorous patch management policy, ensuring that all software and systems are regularly updated. Automated patching systems can help streamline this process, reducing the risk of a potential breach through outdated software.
Incident Response Planning
Given the persistence of APTs, having a robust incident response plan is critical. Financial institutions should prepare for worst-case scenarios by conducting regular penetration testing and tabletop exercises to simulate an APT attack. These exercises can help teams identify weaknesses, streamline communication, and improve the speed and efficiency of their response.
Furthermore, data encryption and backups play a vital role in minimizing the impact of an APT attack. Encrypting sensitive data ensures that even if cybercriminals steal information, they cannot use it without the decryption key. Regular backups ensure that operations can be restored quickly in the event of data corruption or loss.
Threat Intelligence Sharing
APTs often target multiple organizations within the same industry. By participating in threat intelligence sharing networks, financial institutions can stay informed of the latest attack methods and vulnerabilities exploited by cybercriminals. This information can be used to strengthen defenses and anticipate potential threats.
The CodeHunter Solution
The highly sophisticated nature of Advanced Persistent Threats poses a significant challenge for the financial services industry. However, by employing advanced threat detection CodeHunter’s patented threat hunting engine identifies custom, multi-step, and zero-day malware designed to evade detection. Malware can’t hide from CodeHunter’s behavioral analysis, which uses a combination of static and dynamic analyses to provide robust context to expedite SOC team’s threat remediation. Machine learning is also employed to rapidly scan files at the binary level both at scale and at speed, a capability that surpasses a reverse malware engineer’s abilities. Discover how CodeHunter gives SOC teams to the capability to be proactively vigilant to mitigate the risks posed by long-term cyberattacks here.
