Trust seems like a quality that would be inherent in any golden retriever or boy scout, but what about your cyber resilience strategy?

When faced with an ever-increasing amount of cyberattacks, do you trust the people, technology and procedures in place? 

Resiliency requires planning and constant testing. The notion of trust is becoming increasingly vital as organizations face a rising tide of ransomware attacks, and despite advancements in defense strategies, there remains a significant gap in ensuring trusted data integrity and reassurance that you can recover quickly from an attack. 

While many organizations aim to be transparent post-attack, they’re far from alone in dealing with the aftermath. Companies depend on their data protection solutions to restore operations. Unfortunately, the limitations of traditional systems are often exposed after an attack, leaving many to pay ransoms, determine how widespread the damage is and frantically retrieve data. The cost of a recovery can skyrocket – not to mention the regulatory fines that may be associated with the breach.  

Threats are ever evolving, and while solutions have cyber security features built in to stop ransomware from penetrating, the cyber criminals are still going to find a way in, and these solutions are not equipped to facilitate a trusted, smarter recovery. 

One of the most critical soft points in these solutions is their lack of precision in responding to attacks. When faced with questions like “What was the impact of the attack?” and “What data is safe to restore?”, traditional solutions often rely on broad, generalized indicators like unusual file changes or compression rate changes to detect potential ransomware activity. These methods lack granular insight needed to assess which specific files were impacted or a curated path to recovery that doesn’t risk reinfecting the data.

Trust 

Trust in a cyber resilience solution hinges on its ability to provide detailed and accurate insights. Solutions that rely solely on high-level indicators can miss advanced ransomware attacks, particularly as cybercriminals evolve their methods. Leveraging behavioral AI for precise detection of ransomware patterns is the king on this chessboard. 

Ransomware AI engines will fail if they are only trained on ransomware basics. It’s critical to train on actual ransomware variants and to fully comprehend the behavior that results from an attack. This level of intelligence minimizes false alerts and, more importantly, provides organizations with the detailed forensics they need to target specific corrupted data rather than performing blanket recoveries that may overwrite healthy data.

As cyberattacks increasingly target important backups and databases, solutions that fail to validate integrity leave organizations open and vulnerable to incomplete recoveries. Ransomware is evolving to evade detection, now often intermittently corrupting data, sneakily causing widespread damage, and even targeting databases that are essential to operations. A recovery strategy that cannot ensure the integrity of these systems can leave businesses in repair mode even after the attack has been identified.

Additionally, reliance on traditional threshold-based analysis, which guesses at unusual changes in compression or file size, is not enough to stay ahead of evolving ransomware tactics. Advanced AI solutions must go beyond these metrics, continually training on the latest ransomware variants to prevent attackers from bypassing detection by altering file behaviors.

The Need for Trustworthy Cyber Resilience

Trust in cyber resilience is not just about prevention but also about recovery. Resilience is complex and requires planning, monitoring and testing. It also needs to answer the hard questions: Is the AI engine smart enough to handle advanced threats? Can it keep pace with the evolving nature of ransomware? Without these assurances, businesses cannot fully trust their systems to recover clean data after an attack.

The threat landscape demands solutions that continually adapt, providing service-level agreements (SLAs) that guarantee the reliability of data recovery and accuracy in detecting new threats. A trustworthy system not only detects corruption due to malware and ransomware,  but also ensures rapid, precise recovery after an event, giving organizations the confidence they need to move forward.

 A Call to Action: Demand Trust in Your Cyber Resilience Strategy

Organizations must demand more from their data protection solutions. Trust should be built on:

  • Accurate detection of ransomware behaviors, trained through real-world variants.
  • Detailed forensic insights to minimize data loss and focus on recovering only compromised files.
  • Regular validation of database and file data integrity, ensuring that no critical data is left vulnerable.
  • Continuous AI training to stay ahead of modern ransomware tactics, avoiding outdated threat detection methods.

Trust is earned! As ransomware threat actors become more cunning, and attacks become more advanced, trust becomes imperative. Trust in cyber resilience means confidence that after an attack, data is clean, recoverable, and business operations can be restored with minimal loss or downtime. By prioritizing trustworthy cyber resilience strategies and embracing advanced AI solutions, organizations can move beyond the limitations of traditional systems and confidently face these evolving challenges posed by modern cyber threats.