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Generate a Airport SITREP And in minutes identify the size and scope of the adversarial cyber attack

Airport cyber incident investigations often involve records scattered across enterprise networks, airport operations systems, access-control platforms, badge records, baggage systems, flight-information displays, gate systems, vendor maintenance access, camera metadata, facility-control systems, security tools, and operational event records. REMI AI brings those mixed sources together and generates a cyber SITREP that explains the situation in plain English. It identifies what happened, how access was achieved, which systems were touched, whether airport operations or facility-control activity occurred, where suspicious files or AI-spawned tools appeared, what remains unproven, and which records support the sequence.

Instead of manually comparing SIEM alerts, endpoint logs, VPN activity, vendor-access records, engineering workstation events, HMI logs, control-configuration changes, historian records, and portable-media activity one source at a time, REMI analyzes the full evidence set together. REMI is designed to understand advanced AI-enabled disruption patterns, including state-actor style reconnaissance, delayed execution, lateral movement, tool spawning, configuration probing, and activity that may not look dangerous until it is reconstructed across systems and time.

REMI SUPPORTS BOTH TOWER and the Airport's IT Network

REMI analyzes evidence from both enterprise incident response and water treatment OT/IT environments, including endpoint activity, VPN and identity records, firewall logs, SCADA activity, HMI actions, PLC/RTU events, historian data, alarms, vendor access, and maintenance records.

By connecting these records across IT and water operations, REMI helps investigators see whether a cyber incident stayed inside enterprise systems or moved toward treatment, pumping, chemical-feed, distribution, or water-quality processes. It reconstructs what happened, which systems were touched, what changed, what evidence supports the findings, and what records are still needed to close the gaps.

IT Event Logs

Endpoint and EDR logsProcess activity, files, scripts, malware paths, hashes, and device telemetry.
Server and Windows event logsLogons, services, scheduled tasks, PowerShell, registry, and system events.
Identity and access logsUsers, admin accounts, MFA, SSO, tokens, groups, permissions, and sign-ins.
Firewall and network logsInternal traffic, external IPs, ports, DNS, VPN sessions, and lateral movement paths.
Cloud platform logsAzure, AWS, Google Cloud, SaaS activity, storage access, app credentials, and API events.

OT Event Logs

SCADA and HMI logs
Operator screens, commands, acknowledgments, setpoint changes, overrides, and control-room activity.
PLC and RTU event logs
Controller events, logic edits, downloads, forced values, mode changes, and device status records.
Historian and process data
Trend values, tag changes, pressure, flow, temperature, voltage, frequency, tank level, and process state records.
Alarm and event records
Alarm floods, silenced alarms, acknowledgments, resets, threshold changes, and abnormal operating states.
Engineering workstation logs
Project file changes, configuration tools, controller uploads/downloads, user activity, scripts, and remote sessions.
Remote access and vendor logs
VPN sessions, jump hosts, maintenance accounts, vendor diagnostics, source IPs, and access windows.
Industrial network logs
Firewall flows, switch records, protocol traffic, segmentation events, OT network paths, and unusual connections.
Maintenance and change records
Work orders, change tickets, approved maintenance windows, asset-owner records, and configuration approvals.

REMI Is Trained to Recognize Advanced Adversarial Cyber Behaviors in Nuclear Plant Environments

samples from nuclear behavioral and pattern analysis

REMI is trained to recognize advanced adversarial cyber behaviors in both enterprise incident response and water treatment environments.

REMI analyzes industrial vendor logs to identify suspicious access, lateral movement, AI-spawned tools, configuration changes, disruption indicators, and activity that may only become clear when plant, engineering, vendor, security, and control-system records are reviewed together.

OT Behavioral Detection

Chemical dosing changes
Chlorine, pH, fluoride, polymer, feed-rate, or dosing changes outside expected patterns.
Pump and lift anomalies
Abnormal starts, stops, tank levels, pressure shifts, or flow changes.
PLC and RTU activity
Logic edits, controller downloads, setpoint changes, forced values, or mode changes.
HMI and operator actions
Unusual commands, overrides, screen access, or alarm acknowledgments.
Historian and alarm gaps
Missing telemetry, alarm floods, quiet periods, resets, or altered trends.
Vendor remote access
VPN sessions, jump hosts, diagnostics, maintenance accounts, and source IPs.
Water quality indicators
Turbidity, residuals, sensor readings, sample records, or threshold violations.
Distribution impact
Reservoirs, valves, pressure zones, booster stations, storage tanks, or downstream effects.

IT Behavioral Detection

Unusual sign-ins
New locations, impossible travel, off-hours access, failed MFA, token reuse, or abnormal login patterns.
Endpoint activity
Unexpected processes, scripts, malware paths, dropped files, persistence, hashes, and device telemetry.
Network movement
Internal traffic, external callbacks, DNS activity, VPN sessions, ports, protocols, and lateral movement paths.
Privilege and access changes
Admin role changes, permission updates, group membership changes, service accounts, and token activity.
Cloud and SaaS activity
Storage access, mailbox activity, API calls, app credentials, file sharing, downloads, and data movement.
Data exfiltration indicators
Large transfers, unusual downloads, external sharing, archive creation, USB activity, and abnormal outbound traffic.
Insider threat indicators
After-hours access, unusual file access, policy bypasses, removable media use, deleted logs, or access outside job role.
Inside assistance indicators
Shared credentials, approved access used at abnormal times, suspicious vendor coordination, unlocked remote tools, or access enabled before activity.

Behaviors & Pattern Categories

Remote access behavior
VPN sessions, jump hosts, RDP/SSH access, vendor maintenance accounts, new source IPs, and off-hours access into airport networks.
Identity and account anomalies
MFA activity, token use, privileged accounts, shared accounts, failed access, role changes, PAM activity, and account behavior outside normal patterns.
Airport network movement
Traffic moving between enterprise systems, operations desktops, vendor access paths, airport support networks, and operational platforms.
Endpoint and workstation activity
Process chains, scripts, PowerShell, registry changes, scheduled tasks, services, dropped files, and activity on airport operations workstations.
AI-spawned tools and malware controllers
Generated scripts, staged binaries, beaconing tools, command channels, loaders, rootkits, and malware paths appearing across systems.
Firewall, DNS, proxy, and web traffic
Outbound callbacks, DNS tunneling, DoH activity, fast-flux domains, proxy traffic, WAF events, unusual ports, and suspicious external connections.
Data staging and archive creation
Compression activity, staged folders, bulk file movement, large exports, temporary archives, and transfer preparation before removal or exfiltration.
Mailbox, cloud, and SaaS activity
Email access, cloud sync, eDiscovery exports, OAuth activity, shared storage access, app credentials, and unusual SaaS activity.
Database and application access
Bulk queries, dumps, high-volume reads, application exports, passenger-service records, operational databases, and airport application logs.
Baggage and display system activity
BHS events, FIDS/BIDS updates, carousel changes, gate display records, route/display mismatches, and abnormal operational screen changes.
Gate, terminal, and common-use systems
Boarding systems, kiosks, shared workstations, common-use terminals, check-in systems, passenger-processing tools, and terminal operations records.
Access-control and restricted-area activity
Badge activity, door events, secure-zone access, after-hours entry, access denials, camera metadata, and restricted-area movement records.
Tower and airfield operations records
Tower event notes, system-status records, outage timing, runway/taxiway support events, communications timing, and operational disruption records.
Flight-data and timing anomalies
ADS-B, MLAT, ASTERIX-style feeds, GPS/PTP/NTP timing offsets, aircraft position records, altitude/speed data, and sensor-timing mismatches.
Facility control behavior
BMS, HVAC, power, alarms, life-safety systems, building controls, backup systems, and airport facility events tied to disruption timing.
Vendor and maintenance activity
Work orders, diagnostics, approved windows, remote support sessions, maintenance packages, update files, and vendor account activity.
Portable media and device history
USB activity, removable-media transfers, device insertions, file copies, endpoint device history, and portable diagnostic package use.
Logging and monitoring tampering
Disabled logging, audit-policy changes, SIEM suppression, EDR exclusions, deleted records, timestamp changes, and reduced telemetry.
Credential and secrets exposure
Credential dumping, LSASS access, Kerberos activity, service-account use, cached logons, tokens, certificates, vault access, and secret retrieval.
Disruption preparation indicators
Reconnaissance, delayed execution, staging, tool deployment, repeated probing, backup/snapshot activity, and pre-positioning inside airport networks.
Physical-cyber convergence
Cyber activity aligned with access-control records, camera metadata, facility alarms, airport operations timing, vendor presence, or restricted-area movement.

Correlation Is Where the Incident Story Starts to Form 

REMI connects scattered flagged behaviors into the first clear view of how malware activity connects to operational disruption.


REMI connects related activity across plant, engineering, vendor, security, and control-system records so responders can see how separate events fit together.

A single alert rarely explains a nuclear cyber event. One system may show vendor access, another may show engineering workstation activity, another may show a diagnostic package or file change, and another may show activity near HMI, historian, or control-configuration records. REMI correlates those records by time, account, device, IP address, file, process, session, and repeated behavior to build the first evidence-backed version of the story.

Connection: stolen-laptop record → VPN login
Details: NPE-LT-18 was tied to c.arden, whose VPN login came from 203.0.113.44 one week after the laptop was reported stolen.
Why it matters: The same engineer’s device history and account activity are now linked to the remote-access event.
Connection: VPN login → nuclear business network
Details: The c.arden VPN session reached 10.77.18.25 inside the nuclear business network 13 seconds after login.
Why it matters: The remote session did not stop at authentication; it reached an internal network destination.
Connection: business network → office desktop
Details: The same session moved from 10.77.18.25 to OPS-DT-07 43 seconds later.
Why it matters: The activity moved from network entry into a usable internal desktop environment.
Connection: office desktop → engineering workstation
Details: OPS-DT-07 connected toward NPE-ENG-04 inside the nuclear engineering support environment 2 minutes 12 seconds later.
Why it matters: The path crossed from business-network access toward engineering support systems.
Connection: engineering workstation → historian-support records
Details: NPE-ENG-04 activity aligned with historian-support records 2 minutes 38 seconds later.
Why it matters: The engineering workstation path is now connected to plant-support records.

ANALYSIS EXPLAINS HOW THE ATTACK HAPPENED

How It Happened

1 1 wk earlier
Stolen LaptopNPE-LT-18 reported stolen
7 days later
2 1:14 AM
VPN Loginc.arden from 203.0.113.44
3 sec later
3 1:14 AM
Business Entryconnected to 10.77.18.25
12 sec later
4 1:15 AM
Firewall Flowtoward NPE-ENG-04
2 min later
5 1:17 AM
Engineering ActivityNPE-ENG-04 workstation records
4 min later
6 1:21 AM
Historian Recordssupport activity out of plan

How REMI Explains It

How REMI Analysis Explains the Remote VPN Path

Analysis determined that the incident was allowed to progress because vendor_maint_02 successfully established a remote VPN session from 203.0.113.44 and reached the office network at 192.165.43.18. From there, the same account, session window, source IP address, office-network destination, and firewall flow records aligned with movement toward the engineering network, where ENG-WS-04 and related control-support records appeared in the evidence.

REMI’s Assessment

The alarm bells did not ring early because the activity used a valid account and moved through systems that already had trusted access paths between the office and engineering environments. The VPN login, office-network connection, account activity, session timestamp, firewall flow records, and later engineering-network traffic were each visible in separate records, but they did not become a clear incident story until REMI connected them across account, IP address, timestamp, destination system, network path, and control-support evidence.

REMI turns correlated evidence into the explanation of how the incident happened and why the warning signs were missed.


REMI uses the detection and correlation results to dynamically generate the investigative questions that matter for the case. It helps explain whether insider involvement is possible, which accounts were used, why existing IT or security alerts may not have triggered, how access was achieved, what systems were touched, and what evidence still needs to be confirmed.

The Analysis section also produces prioritized next steps for investigators. It identifies malware paths, AI-spawned tools, scripts, files, hashes, affected devices, and artifacts that should be preserved, removed, or submitted for sandboxing. REMI also recommends follow-up questions to ask witnesses, vendors, account owners, and IT teams, along with additional source records needed to expand the findings and improve confidence in the reconstruction.

on-the-spot Reporting

Advanced Cyber Attacks On Nuclear Power Facilities

REMI generates both nuclear-specific reports and broader incident response reports from the same evidence package. For nuclear environments, the reports focus on plant, engineering, vendor, security, and control-system activity, including HMI events, historian records, control-configuration changes, vendor maintenance access, portable-media activity, and plant-adjacent IT/OT behavior.

Reporting Package

Executive Summary
What happened, what systems were affected, and what needs attention.
Detection Summary
Flagged behaviors, triggered indicators, affected sources, and first observed activity.
Behavioral Analysis
Suspicious access, unusual process activity, abnormal commands, persistence, tool spawning, and disruption patterns.
Timeline Report
Event-by-event sequence showing when activity began, spread, changed, and ended.
Correlation Report
Connects accounts, devices, IP addresses, files, processes, sessions, and events across separate sources.
Group / Entity Analysis
Related users, vendors, machines, tools, accounts, and systems involved in the event.
Affected Systems Report
Touched devices, high-priority systems, and records showing configuration or settings changes.
Forensic Preservation Report
Files, paths, logs, artifacts, scripts, binaries, hashes, and evidence to preserve.
Cyber SITREP / Next Steps Report
Size, scope, findings, open questions, and prioritized responder actions.

SitRep

What happened
The evidence-backed sequence of events from first activity through affected systems.
Who and what was involved
Accounts, devices, networks, systems, vendors, files, sessions, and source records.
How the activity moved
Entry point, connection path, lateral movement, trusted access paths, and systems touched.
Insider or assisted access review
Account use, approvals, shared access, vendor activity, or open remote tools tied to the evidence.
What is fully answered
Findings supported by source records, timestamps, logs, artifacts, and system activity.
What remains unresolved
Open questions where the current evidence does not yet prove the full answer.
What data is needed next
Logs, approvals, asset-owner records, vendor records, source files, or telemetry needed to close each gap.
What to do right now
Preserve, isolate, sandbox, remove, remediate, verify, escalate, or request additional records.

Story Gaps

Partly answered: REMI confirmed the VPN session used vendor_maint_02 outside the normal access window.
Question: Was the VPN login approved?
Event logs needed: Maintenance ticket, vendor work order, change approval, and MFA approval record.
Partly answered: REMI confirmed the VPN login came from 203.0.113.44, a source IP not seen in prior sessions.
Question: Was this source location expected?
Event logs needed: VPN source-IP history, identity sign-in logs, geolocation records, and vendor access baseline.
Answered: REMI confirmed the session reached 192.165.43.18 after authentication.
Detail gap: Was this an approved intermediate host?
Event logs needed: Asset inventory, firewall flow logs, DHCP/DNS records, system owner records, and approved remote-access path records.
Partly answered: REMI connected the VPN session to traffic toward ENG-WS-04.
Question: Which engineering actions were performed?
Event logs needed: EDR telemetry, engineering workstation logs, project-file access records, tool execution logs, and jump-host records.
Open question: The account owner behind the VPN session is not fully proven.
Question: Who used the VPN account?
Event logs needed: MFA device record, identity provider logs, account-owner record, vendor assignment record, and privileged-access logs.

Actionable items

1 Preserve VPN and endpoint evidence first
Preserve logs for vendor_maint_02, source IP 203.0.113.44, internal host 192.165.43.18, desktop OPS-DT-07, and engineering workstation ENG-WS-04 before removal.
2 Isolate the affected desktop and engineering workstation
Isolate OPS-DT-07 and ENG-WS-04 from the network. Firewall and EDR records show the VPN path moved through these systems.
3 Locate malware paths on ENG-WS-04
Search ENG-WS-04 for C:\Users\Public\update-task.vbs, C:\Temp\stage.ps1, and C:\ProgramData\svc-loader.bat.
4 Locate AI-spawned controller on OPS-DT-07
Search OPS-DT-07 for C:\Users\j.martinez\AppData\Roaming\sysrunner.exe and preserve a forensic copy for sandboxing.
5 Remove confirmed staged scripts after preservation
After preservation, remove C:\Temp\stage.ps1, C:\ProgramData\svc-loader.bat, and C:\Users\Public\update-task.vbs from affected hosts.
6 Disable exposed remote access
Disable vendor_maint_02, revoke active VPN sessions, rotate credentials, reset MFA, and review vendor access tied to 203.0.113.44.
7 Scrub affected engineering folders
Review and remediate project folders on ENG-WS-04, including D:\Engineering\Projects\NorthPump and related control-support files touched during the session.
8 Verify no return activity
Check OPS-DT-07, ENG-WS-04, 192.165.43.18, and VPN logs for new callbacks, scheduled tasks, repeated processes, reopened sessions, or restored persistence.

Use Case:

how REMI turns event logs and source records into a cyber SITREP

AI-Spawned Malware Controller Inside Engineering Support

At 5:18 AM, the plant systems engineer at Granite Ridge Nuclear Station noticed that engineering support records did not line up with the overnight work plan. Nothing was fully down, but the pattern was wrong: an engineering workstation showed command activity after the maintenance window, a historian support server recorded...

Download remi_nuclear_ai_malware_controller_sitrep_use_case.pdf

AI-Generated Logic Package Disguised as Vendor Maintenance

At 6:04 AM, the control systems engineer at Granite Ridge Nuclear Station noticed that auxiliary support values did not line up with the approved post-maintenance baseline. The plant support system was stable, but the pattern was wrong: a controller showed a new active revision, the upload time came after the approved vendor window, and the package name matched a work order while the behavior did not match the signed baseline.

Download: remi_nuclear_ai_logic_package_sitrep_use_case.pdf

AI-Directed Pre-Positioning Across Nuclear Support Systems

At 4:37 AM, the cyber security lead at Granite Ridge Nuclear Station noticed that low-volume access across plant support systems did not line up with the overnight work plan. Nothing triggered a major alarm, but the pattern was wrong: a service account touched historian servers, a jump host launched administrative tools, and an engineering file share recorded folder enumeration during a window with no approved support activity.

Download: remi_nuclear_ai_logic_package_sitrep_use_case.pdf