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RPA for Cybersecurity in 2024: 7 Use Cases & Best Practices

RPA for Cybersecurity in 2024: 7 Use Cases & Best PracticesRPA for Cybersecurity in 2024: 7 Use Cases & Best Practices

It takes ~280 days to find and contain the average cyberattack which typically costs ~$4M. With the increasing volume of cyber attacks that organizations face every day, more business leaders are considering AI and automation solutions to manage threats. Robotic process automation bots can minimize the risk of cybersecurity exposure by reducing human errors, eliminating unauthorized access, increasing the accuracy of detection and reducing time spent in handling attacks. Nonetheless, RPA tools themselves are at risk of cyber attacks due to backend vulnerabilities and system downtime. Therefore, it is important to implement RPA best practices to avoid weaknesses in the system which can cause breaches and increase exposure to threats.

What is RPA in cybersecurity?

RPA in cybersecurity is the use of robotic process automation bots to protect businesses from cyber attacks and improve their cybersecurity. RPA bots automate repetitive tasks by replicating human encounters with GUI elements, thus, they limit errors caused by human intervention, reduce human exposure to sensitive data, and reduce the cost of a data breach as you can see below.

Average total cost of a data breach by security automation deployment level
Source: IBM Cost of a Data Breach Report 2020

What are the top RPA use cases in cybersecurity?

Investigating cyber threats involves many repetitive tasks and workflows which can be automated using RPA to save time and free cybersecurity analysts to focus on complex problems. RPA can be used for:

Automating data enrichment tasks

RPA bots can automate most data-related tasks required for cybersecurity alerts. They can do these tasks at scale and help humans focus on cases that are likely to be dangerous. These tasks include:

  • Looking up IP addresses
  • Fetching URL intel
  • Investigating domains
  • Retrieving logs
  • Querying accounts

Automating privileged data management

Privileged data management involves manipulating or sharing sensitive data. It is estimated that 95% of cybersecurity breaches are caused by human error, such as:

  • Sending valuable or sensitive data to incorrect email addresses
  • Publishing confidential data on public websites by mistake
  • Misconfiguring assets to allow for unwanted access

RPA bots can be used to manage privileged data entry, updates, and transfer via email or messaging apps, eliminating human errors which lead to system gaps making them prone to attacks.

Eliminating unauthorized access

Using RPA bots to run specific tasks will prevent unauthorized users from managing sensitive or private data. Additionally, bots can allow individuals with credentials to access designated sources, monitor their access, and log their data and actions to create a clear audit trail of access to sensitive data.

Running cyber threat hunts

Cyber threat hunting is the process of repetitively searching through networks to detect and isolate advanced threats. When done manually, it is time consuming because cybersecurity analysts need to skim through a large volume of data about networks to check for indicators of potential risks. The overall threat hunt was estimated to take 170 days to detect an advanced threat, 39 days to mitigate, and 43 days to recover.

Cybersecurity analysts can leverage AI-enabled RPA bots to automate a repetitive search for unusual network traffic, unusual privileged user account activity, login anomalies, increases in database read volumes, suspicious registry or system file changes.

Running penetration tests

Penetration tests, also known as pen tests, are simulations of cyber attacks run on organizations’ computers and systems to to evaluate the security of the system and identify security gaps. RPA bots can be programmed to interact with systems in a specific manner, scan them, capture the necessary data, trigger responses, and generate reports from the results obtained from the pen test simulation.

Protecting against malware and viruses

RPA bots can automatically deploy security controls when vulnerabilities or inconsistencies are discovered in a system. Additionally, if RPA bots encounter an antivirus alarm or notification they will:

  1. Classify the alert according to threat categories
  2. Trigger a security control based on the detected alert
  3. Generate a report of the threat and send it to the cybersecurity team

Updating software

Software updates are significant to cybersecurity because they often include critical patches to security holes. In 2017, the American credit bureau Equifax was a victim of a cyber attack which compromised the data of 143 million people. The cyber attack was possible due to a vulnerability in a web application which was addressed in a recent software update that Equifax did not install. RPA bots can identify pop-ups regarding software updates and send a notification to the IT department about the update. AI-enabled RPA bots can also be programmed to search for the latest software update online, download the file, and trigger an update workflow. In both cases, automating software updates will eliminate the risk of cyber attacks related to software gaps.

What are the risks of RPA?

Although RPA bot can significantly facilitate cybersecurity processes, they can introduce a risk of data leakage and fraud. Some of the risks of using RPA in cybersecurity are:

  • Abusing access to bot credentials: Users who have access to the bot handling sensitive data may use their credentials to program the bot to send specific data to their own addresses. However, assigning each bot to a specific user will ensure accountability of bot operators.
  • System downtime: Bot downtime can happen due to a rapid sequence of bot activity, lack of maintenance, or unexpected network failures. If a bots responsible for detecting cybersecurity alerts encounters an outage, all its privileged data will be exposed to threat. Therefore, it is important to always scan the bots for vulnerabilities and simulate threats to reveal system flaws and gaps. 
  • Cyber attack on the RPA bot: A 2018 survey revealed that a cybersecurity attack against automation or RPA in a large enterprise is anticipated to:
    • disrupt operations/manufacturing (40%)
    • compromise sensitive data (39%)
    • have a negative impact on the quality of products (32%)
    • cause damage to a physical property (29%)
    • harm human life (22%)

What are the best practices for implementing RPA in cybersecurity?

To avoid risks associated with RPA, businesses can implement the following best practices:

  • Assign a unique ID to each bot and process
  • Rotate bot credentials between employees or IT personnel
  • Record bot processes to create an audit trail
  • Run regulatory scans on bots to check for weaknesses or inconsistencies
  • Use encrypted password management tools to enforce passwords within activity sessions

It is also important to implement the best practices of RPA implementation to ensure a sustainable RPA deployment and avoid pitfalls.

What are the alternatives for implementing RPA in cybersecurity?

There are cybersecurity focused software suites making use of AI and machine learning that take care of similar automations out of the box. You can rely on them for an end-to-end cybersecurity solution.

Some of the automations mentioned here are also addressed by workload automation software that tends to rely not on UI but on backend code. Therefore such tools can be more precise but if they are not integrated to work with a specific system, the integration may not be easy.

For more on RPA

To explore RPA use cases in different domains, feel free to read our in-depth articles:

To read about RPA use cases, read our comprehensive list of 45 RPA Case Studies: Explore RPA in your Industry & Function.

And if you still have any questions about RPA, download our in-depth whitepaper on the topic:

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If you feel like your business will benefit from RPA and you want to invest in an off-the-shelf RPA solution, scroll down our data-driven list of RPA vendors.

And we can guide you through the process:

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This article was drafted by former AIMultiple industry analyst Alamira Jouman Hajjar.

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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