Safeguard 3.13: Deploy a Data Loss Prevention Solution

“Safeguard 3.13: deploy a data loss prevention solution requirement” is about stopping data exfiltration before it becomes an incident, a customer notification, or an exam finding. DLP is one of the few control families that can prevent loss at the moment of action (send, upload, copy, sync), but only if you define what you care about, where it can go, and how enforcement will work in your environment. ¹

For a Compliance Officer, CCO, or GRC lead, the fastest path is to translate the requirement into a control statement with measurable scope: which data types are in-scope, which platforms are covered (email, endpoints, cloud, SaaS), what “prevent” means (block, quarantine, encrypt, warn), and how exceptions are granted and reviewed. Then build an evidence rhythm so you can show the control operates, not just that a tool is licensed. ¹

This page gives requirement-level implementation guidance you can hand to Security and IT, plus the artifacts and audit answers you will need.

Regulatory text

Framework requirement (excerpt): “CIS Controls v8 safeguard 3.13 implementation expectation (Deploy a Data Loss Prevention Solution).” ¹

Operator interpretation of what you must do

• Deploy technical controls that can detect and prevent unauthorized transmission or exposure of sensitive data.
• Ensure the solution is implemented in production across the channels where your organization moves data (common paths: email, endpoints, cloud storage, SaaS apps, web uploads, removable media).
• Be able to demonstrate the control is operating with recurring evidence (policy configurations, coverage/health reporting, and alert handling). ¹

Practical translation: auditors will not accept “we have a DLP tool” without proof it is enabled, scoped, tuned, monitored, and enforced for defined sensitive data categories.

Plain-English interpretation (what this requirement is really asking)

You need a DLP program that answers four questions with technical enforcement behind it:

1. What data are you protecting? Examples: customer PII, employee PII, payment data, source code, contracts, security secrets, regulated reports.
2. Where is it allowed to go? Sanctioned systems (CRM, ticketing, approved cloud drives) and approved recipients/domains.
3. How will you stop improper movement? Block, quarantine, require encryption, require business justification, warn-and-log, or allow with escalation.
4. How do you prove it works? Show coverage, show policies, show alerts and tickets, show exceptions and approvals, show review cadence. ¹

Who it applies to (entity and operational context)

This safeguard applies broadly to enterprises and technology organizations that store or process sensitive data and have meaningful exfiltration paths. ¹

You should treat 3.13 as in-scope if you have any of the following:

• Workforce email and collaboration tools where data can be sent externally.
• Cloud file storage or SaaS apps where users can share links publicly or with personal accounts.
• End-user endpoints where data can be copied to USB, synced to consumer cloud, or pasted into browser uploads.
• Third-party workflows (outsourced support, contractors, BPOs) where data leaves your boundary and you need compensating controls. DLP can be part of your third-party risk control stack by restricting what can be shared and how.

What you actually need to do (step-by-step)

1) Define scope: data categories and “systems of record”

Deliverable: a short “DLP scope & data categories” standard.

• Inventory the sensitive data types you will detect. Keep the first release small and high value (for example, one regulated category plus one business-critical category).
• Identify where the data lives (repositories) and how it moves (email, cloud share links, endpoint copy/paste, web uploads).
• Define sanctioned destinations (approved domains, approved SaaS tenants, approved storage locations).

Evidence tip: write these as testable statements (“Customer PII must not be emailed to non-approved external domains”).

2) Pick enforcement points (don’t start with everything)

Most organizations implement DLP across these control planes:

• Email DLP (outbound rules, encryption/quarantine, domain controls)
• Endpoint DLP (USB, clipboard, print, local agents)
• Cloud/SaaS DLP (cloud storage sharing, uploads, OAuth app connections)

Decide what is “must cover now” versus “later phase” based on your highest-risk exfil paths and where regulated data is handled. ¹

3) Establish detection logic and policy design

Deliverable: a DLP policy matrix.

Create policies using a mix of:

• Data identifiers (structured patterns, document fingerprinting, labels)
• Context (internal vs external recipient, unmanaged device, personal email, public link)
• Actions (block, quarantine, encrypt, warn, log)

A simple policy matrix you can use:

Data type	Channel	Condition	Enforcement	Owner
Customer PII	Email	External recipient not on allowlist	Quarantine + approval	Security
Source code	Cloud storage	Public link sharing	Block	IT
Credentials/secrets	Web upload	Upload to unsanctioned site	Block + alert	Security

4) Deploy in monitor mode, then tune

Operational sequence that works:

• Start with monitor-only (or warn-only) to measure false positives and business impact.
• Tune detectors: reduce noisy patterns, add file fingerprints, tighten context conditions.
• Define what constitutes a “real event” versus an “informational” alert, then align routing and SLAs.

5) Turn on enforcement with an exception workflow

Deliverable: an exception procedure that auditors can follow.

Minimum elements:

• Who can request an exception.
• Required justification fields (business purpose, data type, destination, duration).
• Approval authority (Security and data owner).
• Compensating controls (encryption, secure transfer method, time-bound access).
• Review and expiry.

This is where many programs fail. Blocking without an exception path causes shadow IT; exceptions without review create a policy theater control.

6) Operationalize: alert triage, case management, and metrics

Define:

• Triage queue ownership (Security Operations, IT, or a shared model).
• Ticketing integration requirements (alert → case → disposition).
• Disposition codes (false positive, policy violation, allowed business use, escalated incident).
• Escalation triggers (repeat offender, confirmed exfil attempt, high-sensitivity dataset).

7) Prove ongoing operation (recurring evidence capture)

CIS language is about implementation expectation; in audits, “implemented” means you can show:

• Policies exist and are enabled.
• Coverage is active on in-scope systems.
• Alerts are reviewed and acted on.
• Changes are controlled. ¹

A practical way to do this is to map Safeguard 3.13 to a documented control and schedule recurring evidence capture so you are never assembling proof at the last minute. This is also where Daydream fits naturally: use it to map the safeguard to a control narrative, assign owners, and collect the same evidence set on a repeatable cadence.

Required evidence and artifacts to retain

Keep artifacts that demonstrate design, implementation, and operation:

Design

• DLP standard/control statement mapped to CIS Safeguard 3.13 ¹
• Data classification/sensitive data category definitions
• DLP policy matrix and enforcement rationale
• Exception procedure and approval roles

Implementation

• Screenshots or exports of enabled DLP policies (with last modified dates)
• Coverage report (endpoints enrolled, mailboxes/tenants covered, cloud connectors enabled)
• Integration evidence (ticketing/case management connection, alert routing rules)

Operational evidence

• Sample of DLP alerts with case dispositions and approvals
• Exception register with expiry and periodic review outcomes
• Change records for policy updates (who approved, what changed, why)
• Periodic control attestation or control self-test results

Common exam/audit questions and hangups

Expect these questions and pre-answer them in your control narrative:

1. “What sensitive data does DLP protect here?” Provide your categories, examples, and policy mapping.
2. “Where is DLP enforced?” List channels and scope boundaries (endpoint, email, cloud).
3. “Is it blocking or just alerting?” Clarify which policies are enforce vs monitor, and why.
4. “How do you handle false positives and business exceptions?” Show workflow, approvals, and time bounds.
5. “Show evidence of operation.” Produce recent alerts, triage notes, and trend reporting.

Hangup to avoid: claiming “enterprise-wide DLP” when some high-risk channels are out of scope. Auditors prefer an honest, risk-based scope with a roadmap.

Frequent implementation mistakes and how to avoid them

1. Trying to detect everything on day one.
   Fix: start with a small set of high-risk data types and one or two channels; expand after tuning.

2. No data owner involvement.
   Fix: assign each sensitive data category a business owner who approves exceptions and signs off on enforcement thresholds.

3. Over-reliance on regex/pattern matching.
   Fix: add context (recipient type, domain allowlists, managed device state) and stronger identifiers (labels, fingerprints) where possible.

4. Blocking without user messaging or a path forward.
   Fix: build user-facing notifications and a fast exception channel for legitimate work.

5. No recurring evidence.
   Fix: schedule recurring exports/screenshots, ticket samples, and exception reviews; store them in your GRC system (or Daydream) aligned to Safeguard 3.13. ¹

Enforcement context and risk implications

No public enforcement cases were provided in the source catalog for this safeguard, so you should treat 3.13 as a framework expectation rather than a standalone regulatory rule with a fixed penalty model. ¹

Risk-wise, weak DLP typically shows up after an event: unintended external sharing, emailing sensitive data to the wrong recipient, employees moving data to personal accounts, or third-party mishandling. The governance risk is “cannot demonstrate preventative controls,” which becomes a recurring audit observation even if you have strong detective controls.

A practical 30/60/90-day execution plan

First 30 days (stabilize scope and design)

• Publish DLP control statement mapped to Safeguard 3.13 and assign an executive owner and technical owner. ¹
• Define initial sensitive data categories and “allowed destinations.”
• Select enforcement points for initial rollout (email and cloud are common starters).
• Build the DLP policy matrix and exception workflow.

By 60 days (implement and tune in production)

• Deploy DLP policies in monitor/warn mode for in-scope channels.
• Integrate DLP alerts with ticketing/case management and define disposition codes.
• Run tuning cycles with business stakeholders; document policy changes through change control.
• Start an exception register and approval workflow.

By 90 days (enforce and operationalize evidence)

• Enable enforcement for the highest-risk policies (block/quarantine/encrypt).
• Train Service Desk/SOC and publish user guidance (what happens when blocked, how to request an exception).
• Establish recurring evidence capture (policy exports, coverage reporting, alert samples, exception review notes) mapped to Safeguard 3.13. ¹
• Add a quarterly control self-test: attempt test exfil scenarios and record outcomes.

Frequently Asked Questions

Do we have to block data movement to meet safeguard 3.13?

The safeguard expects deployment of a DLP solution, and examiners usually look for prevention on at least the highest-risk paths. Start with monitoring to tune, then enforce for defined data types and channels with a documented exception process. ¹

What counts as “DLP” for this requirement: email rules, CASB, endpoint agent, or all of them?

Any of those can be part of your DLP control if it detects sensitive data and applies policy actions. Your job is to define scope and show coverage across the channels where your sensitive data actually moves. ¹

How do we prove DLP is operating during an audit?

Keep policy configuration exports, coverage/health reports, and a sample set of alert cases with documented disposition and approvals. Pair that with a control narrative mapped to Safeguard 3.13 and a recurring evidence schedule. ¹

We get too many false positives. What do auditors expect us to do?

Auditors expect you to manage false positives through tuning and documented governance, not ignore alerts. Show tuning history, changes approved through change control, and a triage workflow that distinguishes informational events from policy violations.

How should we handle legitimate business sharing with third parties?

Use an exception workflow with approvals from Security and the data owner, time-bound access, and compensating controls like encryption or secure transfer. Keep the exception register and review it regularly as part of evidence.

Can Daydream help with this safeguard?

Yes, if you treat Safeguard 3.13 as a control with repeatable evidence. Daydream can track control ownership, map the safeguard to your internal control narrative, and collect recurring DLP artifacts (policy exports, coverage reports, case samples) so audits don’t become a scramble. ¹

Footnotes

1. CIS Controls v8; CIS Controls Navigator v8