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VOL. I · NO. 705Codex daily edition
PUBLISHED DESKField Notes — Daily Technical Edition — 2026-09-09 — Revision 2 — Forensics12 min read · revision 2
READER’S WIREComplex systemsDetection engineeringWindows + Linux internalsBehavioural psychologyCBTNeuropsychologyHuman mind
Forensics12 min edition

Reconstruct Evidence Across Process Boundaries

Forensic confidence depends on preserving volatile state, separating evidence from interpretation, bounding automation, and validating every alert against known system transitions before drawing conclusions during incident response.

AN ANALYSIS ACROSS 10 RELEVANT VOLUMES

Most forensic errors begin before analysis. A responder sees an alert, but the relevant state may already have changed, been rolled back, or become unobservable. The packet’s Linux, Windows, container, and SRE excerpts support a disciplined sequence: capture state, record provenance, model transitions, then test hypotheses against independent observations. This sequence does not produce certainty by itself. It makes uncertainty inspectable. A missing memory image, incomplete logical extraction, failed checkpoint, or untested alert route must remain an explicit state rather than silently becoming a negative finding.

Evidence quality is a systems property, not a property of one tool. Memory acquisition, kernel event capture, state-repository transactions, scoped credentials, and monitoring tests expose different slices of behavior. Each slice has blind spots and failure modes. This edition therefore treats forensic confidence as a derived judgment with inputs: coverage, ordering, integrity, and reproducibility. Automation can reduce exposure and recovery time, but restart thresholds, retry counts, and cancellation paths require measured bounds. Validation must exercise both nominal and degraded states, including return to nominal load.

REPORTS & CORRESPONDENCE
I

Acquire State Before Interpreting Events

Start with an evidence boundary. The malware-analysis excerpt defines memory forensics as acquisition followed by analysis and notes that a dump can reconstruct events after live tooling is no longer available. Learning Linux Binary Analysis adds that process inspection depends on registers, the stack, dynamic linking, and ELF state; its monitor can inspect live memory or snapshots. Learn Kubernetes Security gives an operational analogue: CRIU, or Checkpoint and Restore In Userspace, freezes a running container, persists its state, and restores it in a sandbox. The common requirement is acquisition before interpretation.

  1. malware analysis detection engineering comprehensive · PAGE 457Chapter: Part IV: Malware Analysis and Classification; topic: Chapter 14: Memory Forensics with Volatility; subtopic: Memory Acquisition; headingPath: Part IV: Malware Analysis and
  2. Learning Linux Binary Analysis · PAGE 97Chapter: Chapter 3: Linux Process Tracing; topic: ptrace and forensic analysis; subtopic: ptrace and forensic analysis; headingPath: Chapter 3: Linux Process Tracing > ptrace and
  3. Learn Kubernetes Security · PAGE 261Chapter: Chapter 11: Defense in Depth; topic: Conducting forensics with Sysdig Inspect and CRIU; subtopic: Using CRIU to collect data; headingPath: Chapter 11: Defense in Depth >
II

Separate Observations From Hypotheses

Once evidence exists, reconstruct transitions rather than listing isolated artifacts. The Windows excerpt describes application staging, user-data restoration, transactional State Repository updates, and notifications only after commit. That order supplies a sequence for analysis. Hiding Behind the Keyboard shows why coverage matters: logical mobile extraction found two entries, while physical searching recovered additional content. Google SRE describes troubleshooting as iterative hypothesis testing against telemetry, logs, expected behavior, and known failure modes. A forensic conclusion should therefore identify the observed transition, the missing transitions, and the test that could disconfirm the explanation.

  1. Windows Internals, Part 2, 7th Edition · PAGE 297Chapter: Chapter 8 System mechanisms; topic: Conclusion; subtopic: Conclusion; headingPath: Chapter 8 System mechanisms > Conclusion
  2. Hiding Behind the Keyboard · PAGE 56Chapter: 3 - Triaging Mobile Evidence; topic: EXAMPLES OF LOGICAL AND PHYSICAL DATA; subtopic: EXAMPLES OF LOGICAL AND PHYSICAL DATA; headingPath: 3 - Triaging Mobile Evidence > EX
  3. google site reliability engineering · PAGE 104Chapter: Chapter 12 - Effective Troubleshooting; topic: Theory; subtopic: Theory; headingPath: Chapter 12 - Effective Troubleshooting > Theory
III

Bound Automation and Failure Scope

Containment and automation alter the evidence they are meant to preserve. Evasive Malware describes anti-forensics as removing or hiding traces, and notes that bare-metal analysis loses convenient clean snapshots. The Book of Batch Scripting shows why an auto-kill threshold must distinguish a hang from a slow valid run, and why retry counts should reflect clustered failures rather than independent-failure arithmetic. Google SRE recommends impulse and gradual load tests, separate component testing, and recovery testing. Building Secure and Reliable Systems adds distinct failure domains and scoped credentials. Automation must preserve provenance while limiting impact.

  1. Evasive Malware · PAGE 337Chapter: Part IV: Defense Evasion; topic: 15. Fileless, Living Off the Land, and Anti-Forensics Techniques; subtopic: 15. Fileless, Living Off the Land, and Anti-Forensics Techni
  2. The Book of Batch Scripting · PAGE 410Chapter: Part III: Advanced Topics; topic: 26. Automatic Restarts and Multithreading; subtopic: The Design Considerations; headingPath: Part III: Advanced Topics > 26. Automatic R
  3. google site reliability engineering · PAGE 197Chapter: Chapter 22 - Addressing Cascading Failures; topic: Testing for Cascading Failures; subtopic: Test Noncritical Backends; headingPath: Chapter 22 - Addressing Cascading Fail
IV

Validate Recovery and Alert Paths

End with repeatable validation. The Site Reliability Workbook separates monitoring tests into metric behavior, rule evaluation, and alert routing, then recommends a running system with known metrics when synthetic coverage is incomplete. Building Secure and Reliable Systems recommends safe cancellation of injected behaviors and mirrored requests for readiness checks. Windows Internals shows that transactional state changes can trigger registered listeners only after commit. These ideas produce a concrete acceptance test: inject a benign synthetic transition, capture its evidence, verify the derived metric, confirm the alert route, and inspect the recovered state. A passing alert is not proof of complete visibility.

  1. The Site Reliability Workbook · PAGE 105Chapter: Part I. Foundations; topic: Chapter 4. Monitoring; subtopic: Conclusion; headingPath: Part I. Foundations > Chapter 4. Monitoring > Conclusion
  2. Building Secure and Reliable Systems · PAGE 212Chapter: Part II. Designing Systems; topic: Chapter 8. Design for Resilience; subtopic: Validation in Practice; headingPath: Part II. Designing Systems > Chapter 8. Design for Res
  3. Windows Internals, Part 2, 7th Edition · PAGE 297Chapter: Chapter 8 System mechanisms; topic: Conclusion; subtopic: Conclusion; headingPath: Chapter 8 System mechanisms > Conclusion
THE TECHNICAL DESK

Forensic State Machines and Testable Evidence

A forensic workflow is a state machine: a finite set of evidence states with explicitly allowed transitions. The design below separates capture, reconstruction, automation, and validation so each boundary can be tested independently.

0101

Represent Acquisition and Preservation States

An evidence record should distinguish live observation, captured state, restored state, and analyzed state. Memory acquisition produces a dump before analysis begins. CRIU can freeze a container and restore the saved state, but the packet notes experimental status and version-specific failure. That makes checkpoint success an assertion to verify, not an assumption. A record should include time, source, integrity value, acquisition method, and expected next state. Missing fields should produce an incomplete record. They should not be coerced into a clean result. The state boundary limits claims about what the investigator could actually observe.

  • Assign every artifact an acquisition state and source identifier.
  • Record integrity and ordering metadata before analysis begins.
  • Reject transitions that skip capture or preservation evidence.
▣ SAFE LAB NOTEBOOK
events = [
    {"id": "e1", "state": "running", "source": "synthetic-proc"},
    {"id": "e2", "state": "checkpointed", "source": "synthetic-criu"},
    {"id": "e3", "state": "terminated", "source": "synthetic-control"},
    {"id": "e4", "state": "restored", "source": "synthetic-sandbox"},
    {"id": "e5", "state": "analyzed", "source": "synthetic-review"},
]
allowed = {
    ("running", "checkpointed"),
    ("checkpointed", "terminated"),
    ("terminated", "restored"),
    ("restored", "analyzed"),
}
for before, after in zip(events, events[1:]):
    edge = (before["state"], after["state"])
    if edge not in allowed:
        print("invalid transition", edge)
print("observed states:", [event["state"] for event in events])
Read-only validation of a synthetic evidence-transition sequence.
  1. malware analysis detection engineering comprehensive · PAGE 457Chapter: Part IV: Malware Analysis and Classification; topic: Chapter 14: Memory Forensics with Volatility; subtopic: Memory Acquisition; headingPath: Part IV: Malware Analysis and
  2. Learn Kubernetes Security · PAGE 261Chapter: Chapter 11: Defense in Depth; topic: Conducting forensics with Sysdig Inspect and CRIU; subtopic: Using CRIU to collect data; headingPath: Chapter 11: Defense in Depth >
0202

Model Observations, Hypotheses, and Disconfirmation

A hypothesis is a proposed cause that predicts an observable state or transition. Google SRE describes troubleshooting as iterative comparison between telemetry, logs, system design, expected behavior, and failure modes. The investigator should store observations separately from interpretations, then attach a test to each proposed cause. For example, a process-memory anomaly may support several explanations: injection, corrupted state, or incomplete acquisition. A single matching artifact does not resolve them. Use independent evidence, controlled treatment, or replay in a sandbox. Record which prediction passed, which failed, and which remains untested.

  • Store raw observations separately from analyst conclusions.
  • Attach one confirming and one disconfirming test to each hypothesis.
  • Mark untested explanations as unresolved rather than false.
▣ SAFE LAB NOTEBOOK
observations = [
    {"signal": "memory_region_changed", "observed": True},
    {"signal": "network_connection_seen", "observed": False},
]
hypotheses = {
    "injection": {"requires": ["memory_region_changed"]},
    "remote_control": {"requires": ["network_connection_seen"]},
}
for name, hypothesis in hypotheses.items():
    result = all(item["observed"] for item in observations
                 if item["signal"] in hypothesis["requires"])
    print(name, "supported" if result else "not supported by captured evidence")
Synthetic hypothesis checks that preserve missing evidence as a limitation.
  1. google site reliability engineering · PAGE 104Chapter: Chapter 12 - Effective Troubleshooting; topic: Theory; subtopic: Theory; headingPath: Chapter 12 - Effective Troubleshooting > Theory
  2. Learning Linux Binary Analysis · PAGE 97Chapter: Chapter 3: Linux Process Tracing; topic: ptrace and forensic analysis; subtopic: ptrace and forensic analysis; headingPath: Chapter 3: Linux Process Tracing > ptrace and
0303

Bound Timeouts, Retries, and Containment

An automated response changes system state and can destroy the next observation opportunity. The Batch Scripting excerpt recommends measuring normal duration, maximum valid duration, polling interval, and retry count before killing a suspected hang. It also warns that failures may cluster, so independent probability can understate risk. Google SRE adds separate component breaking points and recovery behavior after overload. A safe controller therefore needs a timeout budget, bounded retries, a cancellation path, and a terminal state for manual review. It should emit every decision, including no-op decisions caused by incomplete telemetry.

  • Set thresholds from measured synthetic workloads and valid slow cases.
  • Bound retries and stop when failures cluster or evidence becomes incomplete.
  • Log every timeout, cancellation, retry, and terminal review state.
▣ SAFE LAB NOTEBOOK
samples = [12, 18, 35, 58]
valid_max = 35
poll_interval = 10
for elapsed in samples:
    action = "complete" if elapsed <= valid_max else "manual-review"
    checks = (elapsed + poll_interval - 1) // poll_interval
    print({"elapsed": elapsed, "checks": checks, "action": action})
Synthetic timeout classification with no process execution or system changes.
  1. The Book of Batch Scripting · PAGE 411Chapter: Part III: Advanced Topics; topic: 26. Automatic Restarts and Multithreading; subtopic: The Core Auto-Kill-and-Restart Logic; headingPath: Part III: Advanced Topics > 26. A
  2. google site reliability engineering · PAGE 197Chapter: Chapter 22 - Addressing Cascading Failures; topic: Testing for Cascading Failures; subtopic: Test Noncritical Backends; headingPath: Chapter 22 - Addressing Cascading Fail
CROSS-BOOK CORRELATION

Bounded Analogy: Confidence Is Not Evidence

THE OPERATING QUESTIONHow can evidence systems separate captured state from confidence in the explanation?

01
01

Measure the Observable Surface

The behavioural study tested rule-following with eight undergraduates using competing reinforcement schedules. Participants followed the richer instructed alternative when discriminative stimuli were present, but preference became unsystematic without them. Bounded analogy: an alert rule may guide interpretation when context exists, while the same event without provenance should not receive the same confidence.

INVARIANTContext-dependent behaviour does not establish complete system visibility.
  1. The Site Reliability Workbook · PAGE 105Chapter: Part I. Foundations; topic: Chapter 4. Monitoring; subtopic: Conclusion; headingPath: Part I. Foundations > Chapter 4. Monitoring > Conclusion
02
02

Preserve the Capture Boundary

The neuropsychology study designed a brief battery against a longer reference battery and validated it in two stroke cohorts. Bounded analogy: a short telemetry view can screen for likely impairment but cannot stand for the full state. Its sensitivity and specificity must be reported with the reference process and population.

INVARIANTA compact signal is useful only against a declared reference and scope.
  1. malware analysis detection engineering comprehensive · PAGE 457Chapter: Part IV: Malware Analysis and Classification; topic: Chapter 14: Memory Forensics with Volatility; subtopic: Memory Acquisition; headingPath: Part IV: Malware Analysis and
03
03

Account for Missing Channels

The CBT trial compared therapist-supported internet rumination-focused CBT with a waitlist in 118 adults and measured outcomes at seven weeks and six months. Bounded analogy: improvement against a weak baseline does not identify every causal mechanism. A forensic control should compare against active alternatives when attribution matters.

INVARIANTA measured change is not a complete causal explanation.
  1. Hiding Behind the Keyboard · PAGE 56Chapter: 3 - Triaging Mobile Evidence; topic: EXAMPLES OF LOGICAL AND PHYSICAL DATA; subtopic: EXAMPLES OF LOGICAL AND PHYSICAL DATA; headingPath: 3 - Triaging Mobile Evidence > EX
04
04

Test Threshold Effects

The cognitive-science study manipulated prior beliefs during EEG measurement and found that confidence changed while accuracy and reaction time did not materially change. Bounded analogy: a detector’s confidence score can move because of priors or calibration while raw event evidence stays fixed. Store both layers and test them separately.

INVARIANTDerived confidence can change without a corresponding change in captured evidence.
  1. google site reliability engineering · PAGE 104Chapter: Chapter 12 - Effective Troubleshooting; topic: Theory; subtopic: Theory; headingPath: Chapter 12 - Effective Troubleshooting > Theory
05
05

Validate the Recovery Path

The research findings do not justify clinical or operational advice. They support a narrow testing principle: separate inputs, derived judgments, and outcomes. In systems work, mirror benign requests, inject reversible states, and verify the return path. The comparison is methodological, not biological, and should not be generalized beyond controlled validation.

INVARIANTA bounded analogy must preserve its domain limits and test conditions.
  1. Building Secure and Reliable Systems · PAGE 212Chapter: Part II. Designing Systems; topic: Chapter 8. Design for Resilience; subtopic: Validation in Practice; headingPath: Part II. Designing Systems > Chapter 8. Design for Res
◉ THE HUMAN SYSTEMS REVIEW

The mind under observation

RESEARCH FILE04PRIMARY STUDIES · UPDATED WEDNESDAY, 09 SEPTEMBER 2026

A current research digest across behavioural psychology, CBT, neuropsychology and cognitive science. Each report separates the claim from its design and limitations; the systems parallels are analogies for thinking, never claims that people are machines.

behavioural psychology01

Toward a Procedure to Study Rule-Governed Choice: Preliminary Data

THE QUESTIONHow do explicit rules and reinforcement rates jointly affect human choice under conflicting discriminative stimuli?
DESIGN
Two experiments used concurrent variable-interval and extinction schedules; Experiment 1 tested eight undergraduates given incompatible rules, while Experiment 2 used the same choice procedure without rules.
FINDING
With both stimuli present, participants favored the alternative linked to the richer reinforcement rate and prior instruction; without stimuli, preference was indifferent or unsystematic.
LIMIT
The preliminary procedure used small undergraduate samples and produced two alternative explanations, limiting generalization beyond this controlled laboratory choice task.
SYSTEMS LENS

Contextual alert rules may guide action, but missing context should lower confidence rather than create an assumed state.

Analysis of Verbal Behavior · 2024 May 28↗
CBT02

An Internet-Delivered Rumination-Focused CBT Intervention for Adults With Depression and Anxiety: A Randomized Controlled Trial.

THE QUESTIONDoes therapist-supported internet rumination-focused CBT reduce repetitive negative thinking, anxiety, and depression relative to a waitlist?
DESIGN
A single-blind, two-arm randomized trial assigned 118 Romanian adults with elevated worry or rumination and anxiety or depression to seven weeks of internet CBT or delayed treatment, with six-month follow-up in the CBT arm.
FINDING
Compared with waitlist, CBT reduced perseverative thinking, brooding, worry, anxiety, and depression at seven weeks, with effects maintained at six months in the treated arm.
LIMIT
The waitlist was not an active comparator, participants had elevated transdiagnostic symptoms, and six-month maintenance lacked a concurrent randomized control group.
SYSTEMS LENS

A detected change should be compared with active baselines when attribution matters; improvement alone does not identify its mechanism.

Behavior Therapy · 2025 Jul↗
neuropsychology03

StrokeCog-15 Is an Efficient Neuropsychological Battery to Screen for Cognitive Impairment in Chronic Stroke

THE QUESTIONCan a fifteen-minute, four-test battery detect chronic poststroke cognitive impairment against a comprehensive neuropsychological reference battery?
DESIGN
Researchers derived StrokeCog-15 from a 60-minute, nine-test battery in 126 chronic ischemic stroke participants, then evaluated it against 61 participants from an external prospective cohort using sensitivity and specificity.
FINDING
The brief battery achieved sensitivity 0.97 and specificity 0.78 in derivation, then 0.93 and 0.67 externally, outperforming the Montreal Cognitive Assessment on sensitivity.
LIMIT
Both cohorts involved chronic ischemic stroke, impairment was defined by the reference battery, and observational validation does not establish causality or broad transportability.
SYSTEMS LENS

A compact telemetry view can screen states efficiently, but its coverage and error rates require an explicit reference population.

Stroke · 2025 Sep↗
cognitive science04

Common neural choice signals reflect accumulated evidence, not confidence

THE QUESTIONDo confidence-related EEG signals encode confidence directly or accumulated evidence used to compute confidence?
DESIGN
A within-subject EEG experiment with 32 Dutch-speaking participants manipulated prior beliefs, measured accuracy, reaction time, confidence, CPP, Pe, alpha and beta activity, and applied neural decoding analyses.
FINDING
Prior beliefs changed confidence without changing accuracy or materially changing reaction time; CPP and Pe tracked accumulated evidence, while a frontal signal reflected both beliefs and confidence.
LIMIT
The modest single-sample perceptual task, lack of performance feedback, and indirect EEG measures constrain generalization from neural correlates to operational confidence and incident decisions.
SYSTEMS LENS

Treat alert confidence as derived, not raw evidence; test completeness, priors, and analyst calibration under controlled perturbations.

Cerebral Cortex · 2025 Aug 1↗
THE ANALOGY DESK

Four bridges between engineered and human complexity

01
behavioural psychology

HUMANWith both stimuli present, participants favored the alternative linked to the richer reinforcement rate and prior instruction; without stimuli, preference was indifferent or unsystematic.

SYSTEMContextual alert rules may guide action, but missing context should lower confidence rather than create an assumed state.

02
CBT

HUMANCompared with waitlist, CBT reduced perseverative thinking, brooding, worry, anxiety, and depression at seven weeks, with effects maintained at six months in the treated arm.

SYSTEMA detected change should be compared with active baselines when attribution matters; improvement alone does not identify its mechanism.

03
neuropsychology

HUMANThe brief battery achieved sensitivity 0.97 and specificity 0.78 in derivation, then 0.93 and 0.67 externally, outperforming the Montreal Cognitive Assessment on sensitivity.

SYSTEMA compact telemetry view can screen states efficiently, but its coverage and error rates require an explicit reference population.

04
cognitive science

HUMANPrior beliefs changed confidence without changing accuracy or materially changing reaction time; CPP and Pe tracked accumulated evidence, while a frontal signal reflected both beliefs and confidence.

SYSTEMTreat alert confidence as derived, not raw evidence; test completeness, priors, and analyst calibration under controlled perturbations.

These bridges transfer questions and methods—not diagnoses, mechanisms or moral conclusions. This section is educational and is not medical guidance.
EDITORIAL SYNTHESIS

Evidence Requires State, Scope, and Repetition

The packet supports a forensic workflow that begins with acquisition and ends with tested recovery. Linux memory analysis and container checkpoints make volatile state available for later inspection. Windows transactions show why ordering and commit boundaries matter. Mobile triage shows that logical coverage can miss recoverable content. SRE troubleshooting and monitoring tests make hypotheses and alert routes testable. Automation adds risk when thresholds, retries, or cancellation paths are unmeasured. The research comparisons support only bounded methodological parallels: separate observations from derived confidence, declare coverage, and preserve the conditions under which a conclusion was produced.

  1. 01Capture before interpretation.
  2. 02Record state transitions explicitly.
  3. 03Treat missing evidence as a result.
  4. 04Bound automated intervention and retries.
THE CAPSTONE LAB

Synthetic Evidence Transition Review

A bounded exercise that combines the systems, evidence and observation concepts from today’s edition.

TIMEBOX
75 minutes
LEVEL
Advanced
CONCEPTS
05
CONCEPTS IN PLAY01State-machine modeling02Volatile evidence acquisition03Hypothesis testing04Failure-aware automation05Synthetic monitoring validation
SCENARIO

Review a benign synthetic incident in which a process alert precedes a checkpoint, a telemetry gap, a bounded timeout, and a restored sandbox state.

FINAL DELIVERABLE

Submit a transition table, evidence ledger, hypothesis matrix, timeout analysis, and alert-validation record for peer review.

  1. 01
    PHASE 1

    Define the Evidence State Model

    Create explicit states and allowed transitions for the synthetic incident.

    • Define running, checkpointed, terminated, restored, and analyzed states.
    • Assign required fields for time, source, integrity, and confidence.
    • Mark prohibited transitions such as analysis before acquisition.
    EXPECTED EVIDENCEA state diagram and transition table with required and missing fields.
  2. 02
    PHASE 2

    Generate and Acquire Synthetic Evidence

    Produce a reproducible event stream without touching host or network state.

    • Generate in-memory process and container events with fixed timestamps.
    • Add one deliberate telemetry gap and one delayed event.
    • Calculate a digest over the synthetic event sequence.
    EXPECTED EVIDENCEThe event fixture, digest, gap record, and acquisition metadata.
  3. 03
    PHASE 3

    Test Competing Hypotheses

    Separate captured observations from explanations and disconfirming checks.

    • Define injection, remote-control, and benign-corruption hypotheses.
    • Map each hypothesis to required observations and absent observations.
    • Run read-only checks against the synthetic ledger.
    EXPECTED EVIDENCEA hypothesis matrix showing supported, unsupported, and unresolved claims.
  4. 04
    PHASE 4

    Evaluate Timeout and Recovery Logic

    Test bounded automation against valid slow runs and clustered failures.

    • Use synthetic durations below and above the valid maximum.
    • Apply a fixed polling interval and bounded retry count.
    • Record completion, manual-review, cancellation, and retry states.
    EXPECTED EVIDENCEA decision log demonstrating no automatic action on incomplete evidence.
  5. 05
    PHASE 5

    Validate Metrics and Alert Routing

    Verify that known synthetic transitions produce the intended derived signals.

    • Expose synthetic request, error, and transition counts.
    • Evaluate rules against normal, degraded, and recovered sequences.
    • Confirm labels route alerts to the expected review destination.
    EXPECTED EVIDENCEMetric snapshots, rule results, routing records, and a recovery comparison.
ACCEPTANCE CRITERIA
  • ✓Every analyzed record has a preceding acquisition record.
  • ✓The telemetry gap remains visible in the final ledger.
  • ✓Timeout logic distinguishes valid slow runs from hangs.
  • ✓Alerts fire only for tested synthetic conditions.
  • ✓A reviewer can reproduce the final state from submitted evidence.
AFTER-ACTION REVIEW
  1. 01Which conclusion depends on the missing event?
  2. 02Which transition has no independent observation?
  3. 03What evidence would disconfirm the leading hypothesis?
  4. 04Where could automation destroy the next observation opportunity?
LAB SAFETY — Work only with benign data and processes on systems you own. Do not weaken controls, elevate privileges, establish persistence, or touch production environments.