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08/06/2026 4:52 pm
TL;DR: Data loss prevention works by classifying data, monitoring movement, and blocking suspicious transfer paths, but it remains rule-based and can miss unexpected exfiltration patterns, according to StrongDM. The real control problem is that DLP can reduce exposure, yet it cannot replace identity governance, access auditability, and least-privilege enforcement across NHI, autonomous, and human access.
NHIMG editorial — based on content published by StrongDM: What Is Data Loss Prevention? Best Practices
By the numbers:
- In 2021, 73% of organizations said preventing data loss and exfiltration is becoming increasingly important to them as cyberattacks become more costly and damaging than ever before.
- In 2021, 98% of businesses had one or more cloud data breaches in the previous 18 months, and 63% of those companies unintentionally exposed sensitive data during that time.
- In 2021, 83% of cloud breaches were access-related.
Questions worth separating out
Q: How should security teams use DLP without over-relying on it?
A: Security teams should use DLP as a containment and detection layer, not as the primary access control.
Q: Why do cloud environments make DLP harder to enforce?
A: Cloud environments make DLP harder because data moves through APIs, shared services, and delegated identities that do not fit simple perimeter rules.
Q: What do security teams get wrong about DLP?
A: The common mistake is assuming DLP can fix excessive access after the fact.
Practitioner guidance
- Classify sensitive data before writing DLP rules Build your DLP policy set from a current inventory of regulated, confidential, and operationally sensitive data, then map each class to the systems and identities that can touch it.
- Tie DLP to identity-aware access controls Use RBAC, ABAC, and PAM controls to limit who can reach sensitive data before DLP has to inspect it.
- Review cloud access paths for access-related exposure Focus reviews on the transfer points where cloud data leaves its intended boundary, especially delegated sharing, API-driven retrieval, and partner access.
What's in the full article
StrongDM's full blog post covers the operational detail this post intentionally leaves for the source:
- Its breakdown of DLP deployment across network, endpoint, cloud, and email channels for teams planning implementation.
- Its discussion of rule-based content review and contextual analysis for classifying sensitive data more precisely.
- Its examples of access controls, encryption, and audit practices that support compliance reporting.
- Its explanation of how StrongDM positions access management alongside DLP for practical enforcement.
👉 Read StrongDM's guide to data loss prevention best practices and access control →
Data loss prevention and IAM: where access controls still fall short?
Explore further
08/06/2026 6:45 pm
DLP is a containment layer, not an identity control plane. Rule-based inspection can slow data movement, but it does not answer the question of whether the right identity should have touched the data at all. When access is delegated through service accounts, shared credentials, or opaque cloud permissions, content policy becomes a late-stage check rather than a governance boundary. Practitioners should treat DLP as downstream of identity decisions, not a substitute for them.
A few things that frame the scale:
- Two-thirds of enterprises have endured a successful cyberattack resulting from compromised non-human identities, with a quarter encountering multiple attacks, according to The 2024 ESG Report: Managing Non-Human Identities.
- Our research also shows that enterprises that have experienced a compromised NHI averaged 2.7 separate incidents in the past 12 months.
A question worth separating out:
Q: How do teams know if DLP is actually working?
A: DLP is working when sensitive-data alerts decline without a spike in user workarounds or policy exceptions. Teams should measure how often DLP blocks legitimate collaboration, how quickly alerts are triaged, and whether entitlement reviews show reduced data reach for high-risk identities. A stable control should lower exposure without pushing behaviour underground.
👉 Read our full editorial: Data loss prevention best practices still leave identity gaps
