Point of Sale (POS) Attacks - SMB Security Threat Detection
As a small business owner, you may not think that cyber attacks are a threat to your point of sale (POS) system. However, the reality is that hackers are increasingly targeting small businesses, as they often have weaker security measures in place compared to larger enterprises. SMB Security is a must, especially if you have a POS system. A successful cyber attack on your POS system could lead to data breaches, financial losses, and damage to your reputation. Therefore, it’s essential to take steps to protect your POS system from cyber attacks. In this blog, we’ll discuss some practical tips for small business owners to secure their POS systems.
1. Use Strong Passwords and Change Them Regularly
One of the simplest yet most effective ways to protect your POS system from cyber attacks is to use strong passwords and change them regularly. A strong password should be at least eight characters long, contain a mix of upper and lowercase letters, numbers, and special characters. Avoid using easy-to-guess passwords like “password123” or “123456,” as they can be easily hacked by cybercriminals. Also, avoid using the same password for multiple accounts, as it increases the risk of a security breach.
2. Install Antivirus Software and Keep It Updated
Installing antivirus software on your POS system is a crucial step in protecting it from cyber attacks. Antivirus software detects and removes malware, such as viruses, trojans, and ransomware, that could compromise your system’s security. Make sure to choose a reputable antivirus software vendor and keep it updated with the latest patches and updates. Regularly scanning your POS system for malware can also help detect and prevent cyber attacks.
3. Limit Access to Your POS System
Limiting access to your POS system can significantly reduce the risk of a cyber attack. Only authorized personnel should have access to your POS system, and each employee should have their own login credentials. You should also restrict access to sensitive data, such as customer payment information and employee data, to a need-to-know basis. Consider implementing multi-factor authentication (MFA), which requires users to provide more than one authentication factor, such as a password and a fingerprint, to access the system.
4. Encrypt Your Data
Data encryption is another effective way to protect your POS system from cyberattacks. Encryption is the process of converting sensitive data into code that can only be decrypted with a decryption key. Data encryption helps prevent hackers from stealing customer payment information, passwords, and other sensitive data. Choose a strong and widely accepted encryption algorithm such as AES or RSA.
5. Train Your Employees on Cybersecurity Best Practices
Employees are the first line of defense against cyberattacks. Therefore, it is important to train on cybersecurity best practices. For example, how to detect phishing emails, how to use strong passwords, how to identify and report suspicious activity, and more. You can also conduct regular cybersecurity awareness training to keep your employees up to date on the latest threats and security countermeasures.
To capture payment card data, POS malware will typically use one of two methods:
1. Memory scraping: This method involves scanning the system’s memory for payment card data as it is being processed. Once the malware has identified payment card data in memory, it will capture it and store it for later exfiltration.
2. Keylogging: This method involves logging keystrokes made by the user, including payment card data. This method is less common than memory scraping, as it is easier to detect and requires more advanced malware.
ElasticSearch detection rules that can be used to detect Point of Sale (POS) attacks using a SIEM platform:
1. Suspicious Network Traffic:
• Rule: Detect when there is an unusually high volume of traffic between a POS system and an external IP address that is not on the list of approved IPs.
• Query:
source.ip: <POS IP Address> and destination.ip: NOT <List of Approved IP Addresses>
2. Unusual User Activity:
• Rule: Detect when a user logs in to a POS system outside of their regular working hours or from an unusual location.
• Query:
event.action: “user_login” and (user.location: NOT <List of Approved Locations> or not (user.id: “Regular User” and date_hour: “9,10,11,12,13,14,15,16”))
3. Malicious Processes:
• Rule: Detect when a suspicious process or file is executed on a POS system.
• Query:
process.name: <Suspicious Process Name> or process.name: <Suspicious File Name>
4. Unauthorized Access Attempts:
• Rule: Detect when there are repeated failed attempts to log in to a POS system with invalid credentials.
• Query:
event.action: “failed_login” and event.module: “system” and user.id: NOT <List of Authorized Users>
5. Memory Scraping:
• Rule: Detect when a process is attempting to read the memory of another process on a POS system.
• Query:
event.action: “process_memory_access” and source.process.name: <Process Name> and destination.process.name: <Process Name>
Here are some sample Splunk SPL detection rules to detect point of sale (POS) attacks using a SIEM platform:
1. Detection of credit card numbers in unencrypted traffic:
index=network_logs (creditcard=* OR ccnumber=* OR cc_number=* OR cardnum=* OR card_number=* OR card_num=*) | stats count by src_ip, creditcard | where count > 10 | table src_ip, creditcard, count
This rule looks for any network logs that contain credit card numbers or related terms, and identifies the source IP address and the number of occurrences. If the count is greater than 10, it will be considered a potential POS attack.
2. Detection of multiple failed login attempts:
index=security_logs sourcetype=winEventLog:security EventCode=4625 | stats count by src_ip | where count > 10 | table src_ip, count
This rule looks for Windows security logs that indicate failed login attempts, and identifies the source IP address and the number of occurrences. If the count is greater than 10, it will be considered a potential POS attack.
3. Detection of unusual traffic patterns:
index=network_logs | timechart span=1h count by src_ip | stats stddev(count) as stdev, avg(count) as avg by src_ip | where stdev > 3 AND avg > 50 | table src_ip, stdev, avg
This rule looks at network logs and calculates the standard deviation and average of traffic by source IP address over a one-hour period. If the standard deviation is greater than 3 and the average is greater than 50, it will be considered a potential POS attack due to an unusual traffic pattern.
4. Detection of suspicious process activity:
index=endpoint_logs sourcetype=WinEventLog:Security (EventCode=4688 OR EventCode=592) | search (cmdline=*skimming* OR cmdline=*dump* OR cmdline=*extract* OR cmdline=*memory*) | stats count by process, user, src_ip | where count > 10 | table process, user, src_ip, count
This rule looks for Windows security logs that indicate suspicious process activity, such as dumping memory or extracting data, and identifies the process, user, and source IP address. If the count is greater than 10, it will be considered a potential POS attack.
Note: The above queries are examples and may need to be adjusted based on your specific POS environment and threat model. Additionally, it is important to tune the thresholds and adjust the severity levels to reduce false positives and ensure that only meaningful alerts are generated.
In summary, protecting your POS system from cyberattacks is a top priority for small business owners. By implementing these actionable tips, you can greatly reduce the risk of security breaches and protect your customers’ data, reputation, and financial well-being. Remember, cybersecurity is not a one-time event, but an ongoing process that requires constant vigilance and adaptation to evolving threats. Reach out to us to talk about SMB Security.