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Shrink The Blast Radius

Automate Data Minimization with DSPM

Author

Aman Razi Kidwai

Security Researcher at Securiti

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This post is also available in: Arabic

Recently, DaVita disclosed a ransomware incident that ultimately impacted about 2.7 million people, and it’s already booked $13.5M in related costs this quarter. Healthcare and financial services aren’t just targets; they’re stockpiling far more data than they can secure, turning yesterday’s files into today’s risks. Incidents like this don’t just reflect perimeter gaps; they’re made costlier by what sits inside: years of redundant, obsolete, and trivial (ROT) data spread across clouds and SaaS. Let’s define ROT and why it multiplies risk. (HippaJournal)


 


Cost, Risk & AI: the ROT Trifecta

Increasing Costs

  • ROT data drives year‑over‑year storage, backup, and scanning spend. Many large organisations waste $10–30M/year on ROT storage alone.

Security Risks

  • The global average breach cost hit $4.88M (2024). IBM also notes that over one‑third of breaches involved “shadow data,” where ROT often hides. (IBM Newsroom, cdn.table.media)

Compliance Violations

  • GDPR’s storage limitation principle: don’t keep personal data longer than necessary for the stated purpose; retention controls (e.g., HIPAA documentation retention ≥ 6 years; SEC 17a‑4 multi‑year recordkeeping for broker‑dealers). (eCFR, FINRA) (GDPR)

AI Efficacy

  • Outdated/irrelevant inputs pollute the output of AI Agents; new IBM research spotlights growing AI security gaps as adoption outpaces controls. (CPO Magazine)

4 Key Drivers for Data Minimization

  • Cut costs by eliminating ROT before it hits storage and data management budgets.
  • Reduce the attack surface so incidents touch less data and cost less to contain.
  • Ensure compliance with policy-driven data retention and auditable deletion.
  • Maintain AI Efficacy by curating current, relevant, high‑quality fine-tuned data.

How Securiti Automates Data Minimization

Phase 1: Powered by Data Discovery & Metadata Scanning

  • Discover shadow & cloud‑native data across hybrid multi‑clouds & SaaS (including self‑managed systems that never appear in cloud consoles).
  • Flag obsolete data by age & activity criteria. Why start here? To actively fine-tune policy scope through metadata attributes & cut cost and risk instantly.

Phase 2: Powered by Data Classification Scans

  • Detect duplicate content using AI; by flagging duplicates via checksums & near-duplicates using advanced cluster analysis.
  • Accurately detect sensitive data to policy violations using hundreds of predefined AI/ML Classifiers & define custom policies using metadata.

Eliminate ROT Data with Auto-Remediation

  • Automatically remediate via federated systems (Slack/ServiceNow/Jira); delete or archive; orchestrate workflows & ensure compliance.

Want to know more about ROT Data Minimization?

  • Deep dive: Read our full blog on Data Minimization - Link.
  • See the infographic: Download the ROI of Data Minimization: Save Millions in Cost, Risk & AI With DSPM - Link.
  • Get the Whitepaper: Say Goodbye to ROT Data: A 6-Step Automation Guide - Link.

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