What are the most common mistakes when interpreting logs?¶

The most common mistakes in log interpretation come from treating technical identifiers and system labels as direct proof of human action.

The same errors recur across many systems.

Avoid the dangerous assumption¶

The dangerous assumption is that a log is a complete, neutral and self-explanatory history.

It is not.

Common mistakes include treating an account name as a person, a device name as a physical device, an IP address as a user and a successful login as proof of legitimate use.

Investigators also confuse alerts with source evidence, severity with maliciousness and absence of a record with proof that nothing happened.

Timestamp errors are common. These include ignoring time zones, mixing event and ingestion time, assuming clocks were correct and inventing sequence between events with the same precision.

Another mistake is relying on one log in isolation. Different systems may record request, receipt, processing and completion separately. A client record does not prove server outcome, and a firewall allow event does not prove application success.

Exports, dashboards and SIEM records may be filtered, normalised, enriched or incomplete. Field definitions and original source records should be obtained where important.

Automation is often overlooked. Scripts, services, scheduled tasks, APIs, synchronisation and security software can generate events without direct human action.

Finally, investigators may over-collect without a clear question or continue analysis after the likely evidential value has been reached.

Operational takeaway¶

Avoid interpreting logs as direct human narratives; establish source, field meaning, time, automation, completeness and corroboration before drawing conclusions about identity, intent or outcome.