Detect. Validate. Recover: A New Approach to Evidence-Based Ransomware Detection

Ravindra Deotare, Principal Product Manager

September 08, 2026

Detect. Validate. Recover: A New Approach to Evidence-Based Ransomware Detection

Content

    Key Takeaways

    • Two-Stage Detection Framework: Combines behavioral insights (such as suspicious extensions, ransomware notes, and few more) with deep forensic validation (entropy analysis along with MIME and file header mismatch) to detect known and unknown ransomware families with near-zero false positives.
    • Evidence-Based Insights: Provides actionable forensic proof and severity-graded alerts, helping security teams verify true ransomware impact instantly.
    • Fast, Clean Recovery: Direct integration with Recovery Insights, Security Command Center, and Restore Scan enables IT admins to quickly locate and restore uncorrupted data.
    • Seamless Integration: Operates as a plug-and-play feature alongside Druva's existing security tools, including Data Anomaly Detection, Threat Watch, ThreatHunt, and MDDR.
    • Broad Cloud Support: Available starting September 17, 2026, for Premium SKU workloads across AWS EC2/EBS, VMware VMs, and Microsoft Azure VMs.

    When cyberattacks hit, guesswork isn't an option. Security teams need clear answers about what’s infected and what’s safe to restore — without sifting through endless false alarms. Druva has continuously built tools to give you actionable insights to guide incident response. Our latest feature, Ransomware Detection, takes that commitment further by giving you a smarter way to spot, confirm, and recover from both known and unknown ransomware threats.

    Meet Druva Ransomware Detection

    Instead of flagging generic system anomalies, Ransomware Detection uses a two-stage AI and machine learning framework to answer the question that actually matters: was your backup data genuinely impacted? By combining behavioral intelligence, ransomware-specific indicators, and deep file-level forensic analysis, we deliver high-confidence, explainable detections with clear evidence of impact. This includes analyzing signals such as mass file-extension changes, dropped ransomware artifacts, suspicious file transformations, and encryption patterns to detect potential ransomware activity early in the backup lifecycle.

    Now organizations can confidently distinguish legitimate operational changes from genuine ransomware activity, identify affected recovery points, and make faster, more informed recovery decisions.

    What is Druva Ransomware Detection?

    Druva Ransomware Detection is an AI-driven, two-stage security feature designed to identify, validate, and recover from ransomware attacks across backed-up environments.

    Key Benefits

    • Precision Detection: Go beyond anomaly detection to confirm true ransomware impact with high-confidence signals and near-zero false positives.
    • Smart Alert Prioritization: Focus on what matters using clear severity levels — from early warnings to confirmed critical alerts — based on the strength of evidence.
    • Zero-Day Threat Protection: Detect known, unknown, and emerging ransomware strains by recognizing behavioral patterns and encryption techniques.
    • Evidence-Driven Clarity: Access forensic evidence behind every critical detection for a deeper understanding of what changed, why it matters, and whether ransomware impact is confirmed.
    • Scalable Intelligence: Continuously evolve detection efficacy through field-driven telemetry, threat intelligence, and ongoing model refinement.
    • Confident Recovery: Clearly differentiate affected vs. clean recovery points to safely restore the business without second-guessing.

    Our Approach: Detect, Validate, Recover

    Druva Ransomware Detection feature is built around a progressive stage model.

    • The first stage looks for behavioral indicators associated with ransomware.
    • The second stage performs deeper forensic analysis to determine whether ransomware has actually impacted the data.

    Then brings those findings directly into cyber recovery so administrators can identify, validate, and recover from a trusted point. Behavior narrows the field. Forensics confirms the impact. Recovery turns the conclusion into action.

    Stage 1: Behavioral Detection

    Detect potential ransomware activity based on behavioral signals.

    In this stage, Druva continuously evaluates backup snapshots for high-risk behavioral indicators like mass renaming, ransom notes, and suspicious and novel file extensions against proprietary AI/ML models, rather than just relying solely on known file hashes or extensions. When high-risk indicators are identified, Druva raises a “Suspicious Indicators Found” alert, signaling potential ransomware activity and automatically escalating the snapshot for forensic validation. 

    Stage 2: Forensic Validation

    Confirm ransomware presence and encryption impact.

    At this stage, backup snapshots undergo advanced structural verification, entropy analysis, and statistical checks to validate the presence of encryption. If encrypted files are detected, the administrator receives a critical severity alert “Encryption Detected” — indicating that ransomware impact is confirmed. The alert is backed by multiple forensic indicators, enabling administrators to clearly understand:

    • Was the backup data impacted?
    • What evidence confirms the impact?
    • Which recovery point preceded the infection?
    • Can that recovery point be validated before restoration?

    Stage 3: Cyber Recovery

    Turn detection evidence into a recovery decision.

    Detection is only as valuable as what you do next. Druva surfaces ransomware findings in Recovery Insights and the Security Command Center, giving users correlated signals and explainable evidence that’s connected directly within native recovery workflows. From there, administrators can:

    • Understand: Review the correlated indicators and supporting evidence to understand the alert, the behavioral signals, and the scope of impact.
    • Assess and Select: Use those insights to identify the last-known-clean recovery point and distinguish potentially impacted snapshots from clean candidates.
    • Validate and Recover: Run a Restore Scan against the selected recovery point and proceed with recovery using validated data.

    This is where detection delivers true value for your overall incident response and cyber recovery strategy. It transforms a simple security alert into a clear, validated roadmap back to clean data. 

    How This Fits With Druva’s Broader Detection Capabilities

    Ransomware Detection is the latest investment in Druva’s detection capabilities, complementing existing features while advancing how customers can identify and cleanly recover from ransomware attacks.

    • Ransomware Detection: Multi-stage, AI-powered detection for known and unknown ransomware and post-compromise encryption. Behavior-driven with built-in validation.
    • Data Anomaly Detection: AI/ML powered detection to flag unusual data activities. Flags on anomalous and unusual file patterns (create/modify/delete, entropy) but can’t confirm if it’s truly malicious.
    • Threat Watch: Continuous IOC-based scanning to detect specific known threats using Druva’s IOC — threat intelligence library.
    • MDDR: 24x7x365 monitoring of the backup environment for early detection of threats and destructive user actions. Primarily detection at the admin level (ie, deletions, policy changes, or unauthorized access), not at the data level.

    Getting Started

    Druva Ransomware Detection is a plug-and-play capability available within our Premium Security SKU. It is under Limited Availability (LA) starting September 17, 2026, with current support for the following workloads:

    For more information on Druva Ransomware Detection, or to participate in our Limited Availability release, please contact your Account Manager or raise a case via Dru Assist to enable this feature. 

    FAQs

    Q
    What is the difference between Druva Ransomware Detection and standard backup anomaly detection?
    A

    Standard backup anomaly detection flags simple statistical changes (like sudden file count spikes). Druva Ransomware Detection uses a two-stage approach: Stage 1 monitors behavioral signals (mass renaming, dropped notes), while Stage 2 performs deep forensic validation (entropy analysis and file structure inspection) to confirm active encryption with near-zero false positives.

    Q
    How does Druva prevent false positives during ransomware scans?
    A

    Druva prevents false alarms through its Stage 2 forensic validation layer. Instead of alerting solely on unusual file volume or activity, the system analyzes file entropy (randomness of data caused by encryption) and validates underlying file structures to verify actual malicious activity before issuing critical alerts.

     

    Q
    How does Druva Ransomware Detection identify clean recovery points?
    A

    Druva provides severity-graded forensic alerts alongside integration with Recovery Insights, Security Command Center, and Restore Scan. This allows administrators to trace back to the exact backup taken prior to the initial infection vector, ensuring infected files are not reintroduced during restoration.

    Q
    Which platforms and cloud environments support Druva Ransomware Detection?
    A

    Druva Ransomware Detection supports cloud and virtualized workloads across AWS EC2/EBS, VMware VMs, and Microsoft Azure VMs for enterprise accounts on the Premium Security SKU starting August 27, 2026.

    Q
    Is Druva Ransomware Detection an agent-based or agentless solution?
    A

    It operates as a plug-and-play, agentless capability integrated directly into Druva’s cloud backup architecture. It requires no additional local agents or separate infrastructure setup and works seamlessly alongside existing features like Data Anomaly Detection, Threat Watch, and MDDR.

    Further Reading