Ransomware is considered the most prevalent and menacing threat for innumerable reasons. Even though threat actors rarely leverage attacks on individuals but more often on enterprises and governments, ransomware looms over everyone who uses a connected device. To heighten their success rate, a ransomware actor uses dozens of tricks, and data diddling is prominent among them. For the unacquainted, data diddling is a trick that happens when unauthorized and intentional alteration or manipulation of data that mostly goes unnoticed at the point of entry, before it is processed, or even after processing. Significantly, the manipulation is often subtle and designed to go unnoticed, allowing altered data to be passed off as legitimate.
If you’re wondering how data diddling helps ransomware actors, let us tell you that this fraudulent process allows cybercriminals to manipulate data in financial systems such as banks, emails, social media accounts, and corporate databases without drawing immediate attention. When the ransomware gets deployed, the victims not only get the data encrypted but also corrupted, inaccurate, or altered data, making recovery extremely challenging. In this article, we will explore the significance of detecting minor anomalies in systems, how early identification of data diddling can prevent more extensive ransomware attacks, and offer advice on recognizing signs of data tampering in personal and enterprise environments.
What Is Data Diddling and Why It Matters in Cybersecurity
Before we proceed to the segment where we explore how data diddling offers prolific advantages to ransomware actors, let us explain how data diddling is executed using the easiest-to-understand approach.
Key Characteristics of Data Diddling:
Data Manipulation: The First Step in a Silent Cyberattack
The key aspect of data diddling is inputting subtle changes to the authentic data with false information during its input, transmission, or storage phases.
Subtle Changes That Lead to Big Consequences
The alterations are often minor and hard to detect, such as changing transaction amounts, altering account balances, or modifying records.
Financial Fraud: Why Attackers Often Use Data Diddling
Data diddling is a frequently overlooked cyberattack with potentially catastrophic consequences, including financial gain or sabotage, such as embezzling funds, skewing data reports, or avoiding detection by auditors.
Ransomware actors often prefer Data Diddling as an initial part of a bigger plan, and it is subtle and involves gradual and seemingly innocuous changes to data that may go unnoticed for extended periods. The manipulation typically occurs in real time, as data is entered, modified, or transmitted.
In many ransomware cases, attackers do not immediately lock users out of their systems. Instead, they use data diddling to change financial records, alter customer databases, or tamper with transaction logs. Once the data is compromised, the attacker can deploy ransomware, adding another layer of complexity to recovery efforts.
For instance, before triggering the ransomware mayhem, the threat actors could alter salary records, tax deductions, or payment amounts through data diddling in the potential payroll system without immediate detection. Later, when they deploy the ransomware, the victim organization usually attempts to restore from backups, which is largely inaccurate. This makes recovery more costly and time-consuming.
Read More: What is Data Diddling in Cyber Security?
How Ransomware Actors Exploit Data Diddling to Amplify Their Attacks
Here is how data diddling helps ransomware actors to expand the catastrophe in detail.
1. Altering Authentication Systems:
Weakened Security Protocols: In the initial step of most malicious attacks, attackers get the ability to modify user permissions and access controls, enabling them to escalate privileges or disable security measures without being detected. This creates an extremely vulnerable environment for the deployment of ransomware.
2. Creating False Trails: How Data Diddling Obscures Malware
Hidden Payloads: Ransomware actors can spread their malware through routine data processing by injecting malicious code into data files. When these files are opened or processed, the ransomware is activated.
3. Creating Fake Logs and Activity:
False Trail: Attackers can alter system logs or event history, making it harder for IT teams to trace the source of the breach or identify which data has been compromised. This delays detection and response, giving ransomware more time to spread.
4. Undermining Data Integrity:
Loss of Trust: By tampering with data, ransomware attackers can make organizations lose trust in their data integrity. Victims may be compelled to pay the ransom to restore lean data, even if they haven’t lost access but have doubts about its accuracy.
5. Leveraging Insider Knowledge:
Exploiting Data Knowledge: Ransomware actors may use data diddling to manipulate records in ways that only someone with insider knowledge could understand. For example, they may know which data is most valuable and corrupt it in ways that make recovery difficult without paying the ransom.
6. Baiting Targets with Altered Information:
Misleading Victims: Attackers may alter business-critical data in ways that mislead decision-makers into taking actions that benefit the attackers, such as transferring funds to an attacker-controlled account before launching ransomware to cover their tracks.
Real-World Examples of Data Diddling in Common Platforms
- Banking Applications: Data diddling in banking apps involves subtle manipulations of transaction amounts or account balances. Attackers can alter the sum of a transaction by small amounts, such as rounding up or down, in a way that users might not immediately notice.
- Emails: Attackers might tamper with email records, subtly changing the subject lines, content, or recipient addresses. This could lead to sensitive information being sent to the wrong parties or important emails being lost or delayed.
Read More: Sodinokibi Ransomware and QBot Malware: The (R)Evil Connection Explained
Why Ransomware Actors Prefer Data Diddling: Top Reasons
Data diddling is a preferred tactic among ransomware actors for a myriad of reasons. Here is a list of the most prominent among them:
1. Evasion of Detection:
Subtle Data Alterations: Ransomware attackers can use data diddling to make gradual, subtle changes to critical data. These small modifications can go unnoticed by security teams, giving the attackers time to fully compromise the system or plant their ransomware without raising immediate alarms.
2. Financial Fraud:
Manipulation for Financial Gain: Attackers can modify data using data diddling to siphon off funds or cause financial disruptions. They may combine this with ransomware to pressure victims to pay the ransom, as they already face financial damage.
3. Disguising Attack Preparation:
Masking Malware Installation: Data diddling can disguise the installation of ransomware or backdoors. By altering system logs or security events, attackers can hide their tracks. At the same time, they prepare the final payload, making it harder for cybersecurity teams to detect anomalies until it is too late.
4. Prolonged Access: Keeping Control Through Data Manipulation
Persistent Access: Data diddling allows ransomware actors to maintain long-term access to systems by slowly changing security settings, permissions, or configurations. This prolonged access enables them to stage the ransomware attack at the right moment, causing maximum disruption.
5. Manipulation of Critical Infrastructure:
Damage to Critical Systems: In sectors like healthcare, finance, or utilities, data diddling can alter vital information like medical records, financial data, or operational controls. This creates a crisis situation, increasing the likelihood that victims will pay the ransom to restore trust in their data integrity and functionality.
Preventive Measures to Safeguard Your Systems from Data Diddling
Data diddling attacks, where data is altered during input, processing, or output, can have severe consequences for enterprises. To mitigate and protect against these attacks, enterprises need to implement a combination of technical, operational, and administrative safeguards. Here is a list of essential safeguards:
- Data Encryption: Sensitive data must be encrypted at rest, in transit, and during processing. Encryption ensures attackers cannot read or manipulate intercepted or modified data without the decryption key.
- Detecting Data Anomalies: Early detection of system anomalies is crucial for preventing severe attacks. Data diddling is effective because its changes are often hard to detect. Remaining vigilant about minor inconsistencies in data can help catch signs of tampering before significant damage occurs.
- Data Integrity Checks: Regular checksums, hash functions, and data integrity verification processes can help ensure that data remains unaltered. By validating the integrity of data at different points in its lifecycle, organizations can detect unauthorized modifications before they snowball into more significant problems.
- Input Validation: Implement strict input validation protocols to ensure that only correctly formatted and expected data is allowed into the system. This prevents tampered or malicious data from being accepted into the system.
- Automated Monitoring Systems: Enterprises should use real-time data monitoring tools that flag unusual activities, such as unauthorized access to critical data files, unexpected changes to crucial databases, or irregularities in transaction logs.
- Access Control and Tighten Privilege: Use role-based access control (RBAC) and apply the principle of least privilege to ensure that users only have the minimum access necessary for their roles.
- Implement Multi-Factor Authentication (MFA): Enforce multi-factor authentication for users accessing sensitive systems or data. MFA requires multiple verification methods (e.g., password, token, fingerprint) to validate a user’s identity.
- Real-Time Monitoring and Intrusion Detection Systems (IDS): Deploy real-time monitoring systems and IDS to detect abnormal activity or changes in data patterns that may indicate a data diddling attack.
- The Importance of Behavioral Analytics: Advanced behavioral analytics can detect subtle anomalies in user behavior that could indicate data diddling. If a user account suddenly accesses files or data types outside of its regular activity, this could be an early warning sign of tampering or unauthorized access.
- Maintain Regular Backups: Ensure that backups are taken regularly and stored securely. These backups should be monitored for signs of tampering, and organizations should conduct regular tests to ensure their integrity.
- Perform Regular Security Audits: A proactive measure against data diddling attacks is the routine audit of systems. These audits are crucial in identifying vulnerabilities and potential areas where data could be tampered with, focusing on technical vulnerabilities and user behavior for comprehensive protection.
- Employee Awareness and Training: Education is key for both individuals and organizations. Employees should be trained to recognize signs of potential data tampering, such as sudden system slowdowns, unexpected file modifications, or unusual access patterns in shared accounts.
