Data is the backbone of all businesses as everything moves online. Effective data analysis helps businesses to predict future trends, identify any gaps, and understand customer behavior, bringing them ahead of their competitors. Other than being indispensable, data is also a sensitive asset because if found in the wrong hands, it can bring disastrous consequences for any organization.
What is Data Exfiltration?
Data Exfiltration involves the unauthorized removal of data from a computer or server for malicious purposes. The primary motives behind this can often be financial gain through the sale of stolen data, gaining a competitive edge by stealing intellectual property, trade secrets, or confidential business plans, as well as extortion and efforts to sabotage a business’s operations to damage its reputation.
Despite facing numerous attempts at data exfiltration every day, companies are largely successful in protecting their digital assets with the help of robust cybersecurity measures. Learn more about data exfiltration here.
How to Detect Data Exfiltration
Detecting data exfiltration at its earliest stages is absolutely crucial, prompting the immediate alerting of IT teams to halt any unauthorized activities. There are several indicators of suspicious activity like unexpected surge in traffic, longer access time than usual, large file transfer to strange locations, or unauthorized external devices use.
Some of the most common but almost infallible methods of detecting data exfiltration are:
1. Use an SIEM
SIEM stands for Security Information and Event Management. It is an advanced cyber security tool used to monitor real-time traffic. This tool collects and analyzes data within the network of organization and in case of any abnormality from usual traffic, it alerts the security team for potential intrusion. SIEM collects data from all sources such as malware activities, inbound and outbound traffic, firewall logs, and IoT devices leaving no stone unturned.
2. Monitor all Network Protocols
Monitoring all network protocols is another important method to detect any data exfiltration. Attackers frequently try to mask their activities by using trustworthy protocols like HTTP, FTP, or DNS. Comprehensive monitoring helps in identifying hidden or dubious data transfers and results in early threat detection.
3. Monitor Foreign IP address Connections
Another useful technique for spotting data exfiltration is to specially look for any connections to foreign IP addresses. Hackers usually use foreign IP addresses and servers to hack into systems and steal data as it makes it difficult for local law enforcement to get involved.
Organizations should especially supervise IP addresses from countries that are associated with large cyber-crimes to spot potential intrusion.
4. Monitor Outbound Traffic Patterns
Monitoring outbound traffic patterns is crucial to ensure data security. One needs to continuously keep track of any irregularity in pattern for early threat detection. Any delay in responding to a suspicious activity could lead to cyberattacks and data breach. There are automated tools that help in flagging any abnormalities and alerting the system for potential breaches.
The Anatomy of a Data Exfiltration Attack
In most cases, experts have noticed that data breaches happen in a set structure of three phases.
1. Exploiting Vulnerability
The first phase of data exfiltration is finding a network vulnerability and using it against the organization. Cybercriminals gain access to systems by exploiting network vulnerabilities, it could be by phishing attempts, malware attacks, unsecured network points, or weak encryption.
2. Accessing Data
Once inside they find the location of sensitive data, the data could range from the organization’s financial information, trade secrets, or customer’s data. They try to escalate the intrusion by getting access to the said data and finding a way of exporting it to some other system.
3. Exporting Data
After identifying the data, the intruders plan the exfiltration process. They can use any technique for exporting the data like encrypting the content to hide the exfiltration, tunneling through a trustworthy protocol, or using an external storage device.
The Exfiltration attack usually takes place in small cycles at different intervals making it difficult to detect the intrusion.
Indicators of a Data Exfiltration Attack
One needs to have strong pattern recognition to catch any abnormal activity that may be an indicator of a data exfiltration attack.
- Unusual Traffic: A big deviation from usual traffic, especially an unusual spike, is generally a method to mask the security violation.
- Unauthorized Access: Access to someone who doesn’t need the data is another subtle sign of a data breach.
- Abnormal user behavior: A user accessing data at an unconventional time or from a remote location indicates compromised credentials.
- Unexplained Data Transfer: The transfer of data at some alien location through strange methods could be an attacker stealing data.
- Foreign IP address: Keep a check of IP addresses, especially from foreign countries known for infamous cyber activities.
All these signs are a big red flag for the IT security team as any of them could indicate that data intrusion or data breach is taking place. Delays in action could cost the organization financial losses, reputational damages, and even hefty fines and lawsuits.
Best Practices for Detecting Data Exfiltration
A study by IBM suggests that in 2023, it takes 204 days to detect a data breach and then 73 more days to contain it. Primarily let us focus on best practices to detect data exfiltration efforts:
Continuous Monitoring: Regular and continuous monitoring of traffic, user behavior, and data flow leads to pattern recognition. Once the IT intelligence team knows the typical and routine pattern, identifying and understanding unusual patterns leads to early data exfiltration detection.
Log and Behavior Analytics: Along with understanding patterns, organizations should also regularly analyze the logs from servers, devices, and different networks as well as analyze user behavior. Any deviation from the ordinary should be reported to the team without any delays.
Regular Audits: Frequent audits of systems, processes, and compliance to IT policies help in finding any flaw that an attacker can exploit and could help in sensitive data protection.
Penetration Testing: Penetration testing is where ethical hackers are hired to stimulate a hacking attempt. This helps them find any network vulnerabilities and works as one of the best data loss prevention tools.
Fidelis Data Loss Prevention Security (DLP)
According to a report by IBM, 93% of companies that experience prolonged data loss go bankrupt.
Prevention of data loss is never any company’s priority until they encounter cyberattacks. In hindsight, they realize the importance of Data Exfiltration Prevention Solutions. Other than taking safety measures and hiring an alert cyber security team, organizations should also invest in a robust data security tool. One of those solutions is Fidelis Network Data Loss Prevention. It creates a protective barrier between an organization and an attacker. Fidelis DLP is equipped with Patented Deep Session Inspection® technology that investigates any potential threat and prevents a session that violates the data policy of organizations.
How it works?
Traffic monitoring: DLP tools monitor the flow of real-time use activity, traffic, and data to catch any sensitive data spill.
Investigating unusual patterns: DLP tools have advanced analytics technology that detects and investigates atypical activity that can be a sign of intrusion and breach.
Misconfiguration: Fidelis DLP has the ability to detect and prevent unauthorized cloud access, keeping all data secure and protected.
Automated Alerts: Another feature that makes DLP the best out there is the automated suspicious activity alert to the IT team. So, an action can be taken before data is compromised.
Best Practices for Preventing Data Exfiltration
Most cybercrimes can be prevented by proactive defenses. Organizations need to effectively practice data security strategies to make their cyber posture stronger. With the right combination of technology, policies, and employee training, preventing data exfiltration is possible. Here are some Best Practices for Preventing Data Exfiltration:
Access Control
The fundamental and most overlooked method of preventing data theft is access control. The companies should implement Role-Based Access Control and follow the principle of least privileged access. This means the user would only be able to access data that is absolutely necessary to get their work done.
Users should also be encouraged and required to use multi-factor authentication (MFA) this would prevent hacking from compromised credentials. Organizations should also conduct regular audits to check if any unauthorized or abnormal activity is occurring.
Use Endpoint Protection
Use technologies to secure endpoints of any network so any data cannot be exported. Implement tools like Fidelis Data Loss Prevention Solutions that are designed to monitor, analyze, and detect cyber security breaches.
Strong encryption also works in favor of organizations as it protects the data at rest or in transit. Even if data is intercepted, encryptions make data unreadable and unusable for attackers.
Regularly Update Systems
Developers are coming up with regular updates and patches. These updates are a result of exhaustive testing and customers’ feedback. Organizations should keep their system and software updated as outdated software is vulnerable to attacks.
Use of IoT devices whose software and firmware can be updated easily as IoTs are the easiest entry point and hence are targeted by hackers the most.
Incidental Response Plans
To keep up with the increasing cybercrimes, companies should be prepared with a foolproof incidental response plan. This will mitigate the risk of data theft even in case of cyber intrusion.
The cyber security team should think about all possible scenarios and come up with a step-by-step plan to stop the illegal action.
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Conclusion
Understanding network vulnerabilities is the first step in preventing data exfiltration, after which a strategic framework is created to safeguard the company’s critical data.
Detecting and preventing data exfiltration is not a one-person job or even a one-time job as it requires continuous prudence from an organization, cyber-security team, and every employee involved. But with outlined tools and practices organizations can create a strong defense around the data, keeping the intruders at bay.
Frequently Ask Questions
What technologies are used to prevent data exfiltration?
Organizations can use several tools to prevent data exfiltration some of those tools are:
- Data Loss Prevention: DLP protects against unlawful data transfer by monitoring the inflow and outflow of traffic.
- Encryption: Encryption converts data into a unreadable format and secures it at endpoints and in movement.
- Endpoint Protection: Endpoint detection and response (EDR) tools keep an eye on independent devices to secure them from any authorized access.
- Security Information and Event Management: SIEM solutions analyzes real-time logs and events across networks.
- Firewall and Intrusion Detection/Prevention System: Firewall, IDS, and IPS works as a first barrier by monitoring and blocking any suspicious activities.
What role does encryption play in preventing data exfiltration?
Encryption is a code language that is used when data is at rest or is in transmission. This code language is only understood by the sender and receiver hence even if data is captured, the perpetrator will be unable to use and read the same.
Local laws and regulations state that sensitive data and information shall be encrypted. Hence, data encryption not only prevents exfiltration but also prevents organizations from hefty lawsuits.
How can data exfiltration be detected in real time?
Tools like SIEM (Security Information and Event Management), IDS (Intrusion Detection System), IPS (Intrusion Prevention System), and DLP (Data Loss Prevention) are used for data exfiltration in real-time.
Other than the tools mentioned above, one can also use Network Traffic Analysis (NTA) to monitor any unusual pattern of data. Furthermore, Behavior Analytics can be used to define normal user behavior and detect any intrusion by analyzing any deviation from standard behavior.
