3. Should databases be checked for ransomware corruption?
Posted: Wed Feb 05, 2025 10:33 am
2. How is data loss minimized?
Organizations take snapshots or backups of their data on a regular basis, ranging from hourly to daily. Restoring a snapshot or backup after an attack results in clean data overwriting production data, some of which may have been corrupted by ransomware.
If only 20% of the data in a backup has been tampered with by an attacker, restoring a full backup or snapshot will overwrite 80% of the data that did not need to be restored. This will include valuable business information that may be lost forever. A detailed forensic assessment of exactly which files were affected is essential to minimizing data loss.
Cybercriminals understand that databases are the bahamas mobile database of many businesses, making them prime targets for extortion. By damaging these databases, they can force organizations to pay a ransom. Using common variants such as ransomware, which periodically encrypts data, attackers can disrupt both user files and critical databases.
While some vendors claim that there is no need to check the integrity of databases, arguing that corrupted databases will simply stop functioning, this is misleading and has significant consequences after an attack. Regularly checking production databases, including their content and structure, is necessary to ensure cybersecurity resilience and reduce potential damage.
4. Is the AI system used “smart” enough?
Understanding how an AI engine learns is critical to assessing its effectiveness. When dealing with ransomware, it is important that the AI is trained on real ransomware variants and their impact on data.
If AI is trained to look only for threshold changes or compression ratio fluctuations, attackers can adjust their tactics to evade detection. Many modern encryption algorithms do not affect compression ratios, and some ransomware variants do not trigger metadata-based threshold alerts.
AI systems must be trained on real-world ransomware behavior and continually updated with new variants to ensure accuracy and relevance to support intelligent recovery.
Organizations take snapshots or backups of their data on a regular basis, ranging from hourly to daily. Restoring a snapshot or backup after an attack results in clean data overwriting production data, some of which may have been corrupted by ransomware.
If only 20% of the data in a backup has been tampered with by an attacker, restoring a full backup or snapshot will overwrite 80% of the data that did not need to be restored. This will include valuable business information that may be lost forever. A detailed forensic assessment of exactly which files were affected is essential to minimizing data loss.
Cybercriminals understand that databases are the bahamas mobile database of many businesses, making them prime targets for extortion. By damaging these databases, they can force organizations to pay a ransom. Using common variants such as ransomware, which periodically encrypts data, attackers can disrupt both user files and critical databases.
While some vendors claim that there is no need to check the integrity of databases, arguing that corrupted databases will simply stop functioning, this is misleading and has significant consequences after an attack. Regularly checking production databases, including their content and structure, is necessary to ensure cybersecurity resilience and reduce potential damage.
4. Is the AI system used “smart” enough?
Understanding how an AI engine learns is critical to assessing its effectiveness. When dealing with ransomware, it is important that the AI is trained on real ransomware variants and their impact on data.
If AI is trained to look only for threshold changes or compression ratio fluctuations, attackers can adjust their tactics to evade detection. Many modern encryption algorithms do not affect compression ratios, and some ransomware variants do not trigger metadata-based threshold alerts.
AI systems must be trained on real-world ransomware behavior and continually updated with new variants to ensure accuracy and relevance to support intelligent recovery.