Introduction
Cyber threats are growing more sophisticated by the day. The average cost of a data breach has risen to over $4 million, and it takes around 280 days on average to identify and contain a cyberattack. At the same time, there is a massive cybersecurity talent shortage, with nearly 3 million unfilled positions globally.
Organizations desperately need better ways to secure their systems against threats. This is where robotic process automation (RPA) comes in. RPA tools can automate repetitive, manual cybersecurity processes to free up security analysts to focus on higher-value tasks.
In this comprehensive guide, we will explore the top ways RPA is transforming cybersecurity operations, common use cases and benefits, risks to be aware of, best practices for implementation, and alternative solutions.
How RPA Improves Cybersecurity Operations
RPA tools work by automating human interactions with applications at the graphical user interface (GUI) level. For cybersecurity teams, this confers several key advantages:
- Faster response times: Bots can take immediate action when threats are detected without waiting for human approval.
- Fewer errors: Bots do not make mistakes due to fatigue or inattention like humans.
- Increased efficiency: Repetitive tasks like data enrichment are handled automatically, freeing up staff.
- Enhanced reporting: RPA centralizes information from multiple systems for analyzing incidents.
- Cost savings: RPA reduces the workload for high-cost cybersecurity experts.
As a result, organizations using RPA for cybersecurity processes experience breaches that are less severe, less disruptive, and less expensive. They also benefit from improved regulatory compliance and transparency around security controls.
Top 7 Cybersecurity Use Cases for RPA
Let‘s explore some of the most common and impactful ways RPA is being applied across the cybersecurity function:
1. Automating Threat Hunting
Threat hunting refers to proactively scanning systems and networks to identify vulnerabilities and signs of compromise, such as suspicious user activity.
This process generates massive volumes of security data that must be analyzed to uncover stealthy attacks. RPA tools like UiPath are perfectly suited for ingesting all this data from various sources, enriching it as needed using advanced machine learning algorithms, detecting anomalies, generating alerts, and creating reports for security staff.
The machine learning capabilities now embedded in leading RPA solutions make them even more effective at identifying threats missed by rules-based systems. For example, tools like WorkFusion incorporate unsupervised learning techniques to detect zero-day threats not seen previously based on minor deviations from normal behavior.
Studies have shown companies using automated threat hunting detect breaches over 60 days faster on average.
2. Automating Incident Response
When a cyberattack does occur, time is of the essence. The longer an attacker remains in the system, the more damage they can do and data they can exfiltrate.
RPA tools accelerate incident response in several key ways while maintaining robust encryption protocols:
- Immediately isolating compromised endpoints to stop lateral spread.
- Gathering forensic artifacts like system logs to determine root cause.
- Notifying on-call incident responders of the attack via integration with notification platforms like PagerDuty.
- Initiating remediation procedures like resetting passwords and patching vulnerabilities through existing IT service management ticketing tools.
By quickly taking these actions, bots act as a “digital first responder,” reducing dwell time from months to minutes and allowing the security team to focus their efforts on strategic tasks like eliminating the attacker’s foothold and improving defenses.
More Use Cases…
Risks of Using RPA in Cybersecurity
While offering immense potential benefits, RPA also introduces unique risks that cybersecurity leaders must mitigate:
Bot Vulnerabilities
Like any application, RPA tools themselves can contain security flaws that attackers exploit to breach networks. Bots often have excessive privileges needed to access sensitive systems, reside on endpoints alongside users, and use insecure protocols for command and control communications.
Rigorously hardening bots via:
- Platform isolation techniques like containerization.
- Mutual authentication between bots and servers.
- Encryption for stored credentials and network traffic.
Greatly reduces these attack surfaces malicious actors can target.
More risks…
Best Practices for RPA Cybersecurity Success
Based on the experience of leading organizations using RPA strategically for security, we recommend several best practices:
Start Small, Then Scale
The most impactful RPA cybersecurity initiatives begin with a few narrowly focused bots before expanding. Attempting to automate everything at once rarely ends well. Define clear metrics like mean time to respond for gauging bot success.
More best practices…
The Future of RPA for Cybersecurity is Bright
RPA is already indispensible for many security teams today, serving as a “force multiplier” against increasingly potent and prolific threats. Cybersecurity leaders expect to expand RPA budgets over 50% annually through 2025.
However, as attackers grow more sophisticated, merely automating manual processes faster will not be enough. Tomorrow’s cybersecurity RPA solutions must incorporate artificial intelligence and analytics to stay steps ahead of the adversary. Only by matching (and exceeding) the creativity and cunning of hackers can enterprises hope to secure their critical systems and data.
