Is the scenario supported?
Check the account, Region, protection plan, and relevant data sources against the chosen scenario. Record missing prerequisites before interpreting a test result.
INDEPENDENT LAB · PRE-MVP
Did the detection fire?
Did the alert reach your team?
For security engineers responsible for AWS detection coverage. The lab is developing repeatable checks that connect a specific test to its telemetry, finding, and downstream alert.
01 / THE PROBLEM
A service can be enabled while a specific threat scenario or alert route remains unverified. The first checks will address three practical questions.
Check the account, Region, protection plan, and relevant data sources against the chosen scenario. Record missing prerequisites before interpreting a test result.
Trace a finding into the destination used by the team. Check filters and rule mappings: receiving an event and creating an actionable alert are separate outcomes.
Repeat a check after a protection setting, routing rule, or detection mapping changes. Compare the evidence with the previous run and identify what needs review.
Evidence for a named scenario, configuration, and observation window. A successful test applies to those conditions; other threat variants and untested scenarios remain unverified. Missing evidence leaves the result inconclusive.
02 / EXAMPLE REPORT
An illustrative routing check using a generated GuardDuty sample finding. All observations below are invented to demonstrate the proposed report format. This is not a completed lab run or a customer result.
ILLUSTRATIVE · SYNTHETIC EXAMPLE
The generated sample finding has a recorded ID and timestamp.
The receiving system contains an event correlated to the same finding.
The configuration snapshot shows that the matching destination rule does not create an alert.
A recorded query covering the full observation window returns no matching alert.
CHECK RESULTS
Alert routing: Not detected
Threat detection: Not tested
INTERPRETATION & NEXT CHECK
E2 confirms event ingestion; E3 identifies an alert-generation gap consistent with E4. Review whether the rule should create an alert, change it if appropriate, then repeat the check. A successful retest is needed to confirm the fix.
A sample finding tests the handling of an injected event. Testing threat detection itself requires a separate behavior-based scenario and its own evidence. AWS documentation on sample findings
03 / READING THE RESULTS
Each check gets its own outcome. Detection and alert delivery are assessed separately, so a successful routing test cannot be mistaken for proof that a threat was detected.
Results are time-bounded observations. A delayed finding can change the assessment; an absent alert alone does not establish the cause.
04 / METHOD & DATA
Each proposed report will include the scenario and procedure version, test conditions, timestamps, evidence references, outcome, and recommended follow-up.
The prototype will start with synthetic datasets and isolated AWS test accounts. Procedures will define the allowed actions, required permissions, observation window, and cleanup. Execution records will distinguish failed test steps from absent detections.
Versioned procedures make checks repeatable. Cloud processing and detection timing can still vary between runs.
The planned prototype uses the Claude API to help interpret selected configuration and evidence inputs, suggest relevant MITRE ATT&CK mappings, and draft explanations. Each conclusion must reference evidence and receive practitioner review.
Model output will not serve as proof that a test ran or a detection fired. Mapping a scenario to an ATT&CK technique does not demonstrate coverage of the entire technique.
For feedback now, a description of your workflow is enough. This site has no account connection or evidence upload facility.
Initial model evaluation is planned with synthetic inputs. Customer-data handling, retention, and deployment options have not been finalized. Any future trial would need an agreed data scope and processing terms before evidence is shared with an external model provider.
05 / THE PROJECT
1a2b Cloud Detection Lab is an independent project by Nikolai, a security engineer with a background in cloud security, DevSecOps, automation, and threat detection.
The direction draws on practical work reviewing cloud protection settings and mapping provider findings to downstream detection rules. The lab aims to turn those recurring questions into repeatable, evidence-backed checks.
The current work is defining the first AWS scenarios and report format. There is no publicly available product yet. The next milestone is an isolated prototype that records both detection and routing outcomes, followed by feedback from security practitioners.
HELP CHOOSE THE FIRST CHECKS
If you build or operate AWS detections, I’d like to understand how you verify them today and where the process breaks down.
Tell me about one scenario: the signal you expect, where the alert should arrive, and what is difficult to verify. A brief description is enough to start.
Share your validation workflow box@1a2b.org