[ Reports & investigation ]

Build a sender-level investigation timeline from report and DNS evidence

Build a timeline that separates message observations, report arrival, DNS publication and test evidence without inventing event precision.

By the EmailAuth research team

[ Key points ]

  • Keep observation intervals, arrivals, changes and tests distinct.
  • Current DNS and one later test do not reconstruct earlier receiver behavior.
  • Preserve competing explanations and source-level uncertainty.
On this page

An authentication incident often contains several clocks: a report's covered interval, the report's arrival, a DNS change, an application deployment and a controlled test. Putting them on one timeline is helpful only if each event keeps its original meaning. A daily aggregate report cannot usually tell you the exact minute when each included message failed.

Establish a common time basis

References: RFC 9990 §3.1.1.4, RFC 9990 §3.5.4.

Normalize displayed timestamps to a declared timezone while retaining original values and precision. Record clock sources and known uncertainty. Distinguish the report interval from arrival and ingestion timestamps. Late report delivery should not be plotted as a new burst of sending at the moment the attachment arrived.

Scope the investigation to an author domain and verified service where possible. Keep unclassified sources separate. Preserve reporter and report identity, message counts, source groups and evaluated identities, along with duplicate and overlap decisions. Those details determine which observations can legitimately be compared.

Add DNS evidence without rewriting history

References: RFC 1034 §3.6, RFC 8767 §4, RFC 9990 §3.3.

Record the approved change, intended publication time, authoritative observations and any resolver samples, including lookup time and returned TTL. A current DNS answer establishes what that lookup observed now; it is not a complete history of what every receiver saw earlier.

DNS caching matters under RFC 1034 §3.6; qualifying serve-stale behavior under RFC 8767 §4 can extend cache use beyond normal freshness. Do not claim that all receivers switched at the instant of publication or exactly one displayed TTL later. Preserve the prior configuration, change log and evidence limits. Where a report interval spans a policy change, label it as mixed or potentially mixed rather than assigning every observation to the final policy.

Add application and receiver evidence

References: RFC 5321 §4.2.5.

Place application deployments, gateway changes and signing changes beside the DNS events. Keep controlled tests as individual observations with their actual route, receiver and result. An application log may show submission or acceptance at a hop; it does not necessarily establish final delivery.

Use these evidence types to test competing explanations. A failure increase after a DNS edit might also coincide with a new template that changes signed content. Correlation narrows the investigation but does not identify the cause without further evidence.

Work through a bounded timeline

Illustrative case: a report covers 00:00 to 24:00 UTC. A policy change is recorded at 12:00, and a controlled test at 12:20 passes aligned DKIM. The report contains 80 passing and 20 failing observations, arriving the next morning at 05:00.

You can state the interval totals and the successful test at 12:20. You cannot assign all 20 failures to before noon merely because the test passed later. The next action is to obtain narrower receiver or application evidence, or run additional representative tests. The arrival at 05:00 is a collection event, not the time of the 20 failures.

Close with a causal statement of the right strength

Label conclusions as observed, corroborated or still hypothetical. Name the evidence that supports the suspected cause and any competing explanation not ruled out. If exact linkage is impossible, retain the uncertainty rather than drawing a precise failure boundary on the chart.

Save the timeline with source references, query revision, included intervals and ownership classifications. Record the next verification trigger, such as the first complete comparable reporting period after a repair. A reusable timeline should allow another analyst to reconstruct both the facts and the limits of the conclusion.

Continue the investigation

Use the aggregate-report walkthrough for the underlying fields and the alignment diagnosis guide when raw authentication success does not satisfy DMARC.

Keep the illustration within its evidence

For the fictional 80-pass/20-fail interval, keep all 20 failure times unknown. The 12:20 test is one later observation and the 05:00 arrival is a collection event. No real DNS lookup or authentication test was executed, and the timeline does not locate a proven causal cutover.

[ Takeaway ]

Keep observation intervals, arrivals, changes and tests distinct. Current DNS and one later test do not reconstruct earlier receiver behavior. Preserve competing explanations and source-level uncertainty.

[ By role ]

What this means for you

Choose your role for practical next steps.

IT / Mail Admin

Preserve original times and normalized views.

Separate receipt from observation intervals. Retain DNS and controlled-test evidence.

Next steps

  1. Preserve original times and normalized views.
  2. Separate receipt from observation intervals.
  3. Retain DNS and controlled-test evidence.

CISO / SecOps

Challenge unsupported causal precision.

Record alternative explanations. Require a reproducible post-repair comparison.

Next steps

  1. Challenge unsupported causal precision.
  2. Record alternative explanations.
  3. Require a reproducible post-repair comparison.

Founder / Non-technical

Ask what the timeline actually proves.

Keep business changes visible beside DNS events. Assign the next evidence-gathering step.

Next steps

  1. Ask what the timeline actually proves.
  2. Keep business changes visible beside DNS events.
  3. Assign the next evidence-gathering step.

[ FAQs ]

Frequently asked questions

Is report arrival the time the messages were sent?

No. Keep covered interval, arrival and ingestion times separate.

RFC 9990 §3.1.1.4

Can a daily report identify the failure minute?

Usually not. It groups observations across the reported interval.

RFC 9990 §3.1.1.4

Does current DNS prove yesterday's policy?

No. Retain change records and historical observations for that claim.

RFC 9990 §3.3

Does one TTL prove every receiver updated?

No. A single lookup and TTL do not establish universal receiver state.

RFC 8767 §4

What if the interval spans a policy change?

Preserve the change and label the interval as mixed or potentially mixed.

RFC 9990 §3.3

Does a later passing test classify earlier failures?

No. It establishes the result of that test, not the timing or cause of other observations.

How should competing changes be handled?

Put deployments, templates and gateways on the timeline and test plausible alternatives.

What should the final timeline retain?

Original timestamps, precision, source references, scope, conclusions and unresolved questions.

[ Sources ]

Sources

  1. RFC 9990

    Sections §3.1.1.4 · §3.3 · §3.5.4

  2. RFC 1034

    Sections §3.6

  3. RFC 8767

    Sections §4

  4. RFC 5321

    Sections §4.2.5

[ Glossary ]

Glossary

Observation interval
The report period described by UTC epoch seconds, not the timestamps of individual messages.

RFC 9990 §3.1.1.4

Causal hypothesis
A proposed explanation that remains distinct from observed events until evidence supports the linkage.

Enterprise provenance

Why top financial institutions and governments retired their email security dashboards.

Traditional email authentication platforms sell you a dashboard and ask your engineers to do the labour. In high-stakes environments, manual oversight means delayed enforcement, configuration drift and unmonitored shadow domains.

EmailAuth is the agentic email provenance platform. Our agents enforce p=reject, keep third-party senders aligned and move your domains to full RFC 9989 compliance, the new DMARC standard,, with human-in-the-loop auditability.

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