Detection rules › Kusto
Suspicious access of BEC related documents
This query looks for users with suspicious spikes in the number of files accessed that relate to topics commonly accessed as part of Business Email Compromise (BEC) attacks. The query looks for access to files in storage that relate to topics such as invoices or payments, and then looks for users accessing these files in significantly higher numbers than in the previous 14 days. Incidents raised by this analytic should be investigated to see if the user accessing these files should be accessing them, and if the volume they accessed them at was related to a legitimate business need. This query contains thresholds to reduce the chance of false positives, these can be adjusted to suit individual environments. In addition false positives could be generated by legitimate, scheduled actions that occur less often than every 14 days, additional exclusions can be added for these actions on username or IP address entities. This query uses the imFileEvent schema from ASIM, you will first need to ensure you have ASIM deployed in your environment. Ref https://learn.microsoft.com/azure/sentinel/normalization-about-parsers
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Collection |
Telemetry coverage
Rule body
id: cd8d946d-10a4-40a9-bac1-6d0a6c847d65
name: Suspicious access of BEC related documents
description: |
'This query looks for users with suspicious spikes in the number of files accessed that relate to topics commonly accessed as part of Business Email Compromise (BEC) attacks.
The query looks for access to files in storage that relate to topics such as invoices or payments, and then looks for users accessing these files in significantly higher numbers than in the previous 14 days. Incidents raised by this analytic should be investigated to see if the user accessing these files should be accessing them, and if the volume they accessed them at was related to a legitimate business need.
This query contains thresholds to reduce the chance of false positives, these can be adjusted to suit individual environments. In addition false positives could be generated by legitimate, scheduled actions that occur less often than every 14 days, additional exclusions can be added for these actions on username or IP address entities. This query uses the imFileEvent schema from ASIM, you will first need to ensure you have ASIM deployed in your environment. Ref https://learn.microsoft.com/azure/sentinel/normalization-about-parsers'
severity: Medium
requiredDataConnectors: []
queryFrequency: 1d
queryPeriod: 14d
triggerOperator: gt
triggerThreshold: 0
tactics:
- Collection
relevantTechniques:
- T1530
eventGroupingSettings:
aggregationKind: SingleAlert
query: |
let BEC_Keywords = dynamic([ 'invoice','payment','paycheck','transfer','bank statement','bank details','closing','funds','bank account','account details','remittance','purchase','deposit',"PO#","Zahlung","Rechnung","Paiement", "virement bancaire","Bankuberweisung",'hacked','phishing']);
// Adjust this threshold based on your environment
let sensitivity = 2.5;
let Events = materialize(imFileEvent
| where TimeGenerated between(startofday(ago(14d))..endofday(ago(0d)))
| where User !~ "app@sharepoint"
| where EventType =~ "FileAccessed"
| extend OriginalEvent = column_ifexists("EventOriginalType","Unknown")
| where OriginalEvent !~ "FileSyncDownloadedFull"
| where EventProduct in ("SharePoint 365", "Azure File Storage", "OneDrive" , "SharePoint")
| where FilePath has_any(BEC_Keywords)
| extend _AuthDetails = column_ifexists("AuthorizationDetails", "None")
| extend SPuser = case(gettype(_AuthDetails) == "array", tostring(todynamic(_AuthDetails)[0].principals[0].id), "Unknown")
| extend User = case(isnotempty(User), User, SPuser)
| where isnotempty(User));
Events
| summarize dcount(FileName) by User, bin(startofday(TimeGenerated), 1d)
| summarize CountOfDocs = make_list(dcount_FileName, 10000), TimeStamp = make_list(TimeGenerated, 10000) by User
| extend (Anomalies, Score, Baseline) = series_decompose_anomalies(CountOfDocs, sensitivity, -1, 'linefit')
| mv-expand CountOfDocs to typeof(double), TimeStamp to typeof(datetime), Anomalies to typeof(double), Score to typeof(double), Baseline to typeof(long)
| where Anomalies > 0
| project TimeStamp, CountOfDocs, Baseline, Score, Anomalies, User
| join kind=inner(Events | extend TimeStamp = startofday(TimeGenerated)) on TimeStamp, User
| extend IpAddr = column_ifexists("IpAddr", SrcIpAddr)
| extend Name = iif(User contains "@", split(User, "@")[0], split(User, "\\")[1])
| extend UPNSuffix = iif(User contains "@", split(User, "@")[1], "")
| extend NTDomain = iif(User contains "@", split(User, "\\")[0], "")
| project-reorder TimeGenerated, User, EventType, EventResult, EventProduct, FilePath, HttpUserAgent, IpAddr, CountOfDocs, Baseline, Score
entityMappings:
- entityType: Account
fieldMappings:
- identifier: FullName
columnName: User
- identifier: Name
columnName: Name
- identifier: UPNSuffix
columnName: UPNSuffix
- entityType: Account
fieldMappings:
- identifier: FullName
columnName: User
- identifier: Name
columnName: Name
- identifier: NTDomain
columnName: NTDomain
- entityType: Account
fieldMappings:
- identifier: AadUserId
columnName: User
- entityType: IP
fieldMappings:
- identifier: Address
columnName: IpAddr
- entityType: File
fieldMappings:
- identifier: Name
columnName: FilePath
customDetails:
Type: EventType
Result: EventResult
Product: EventProduct
UserAgent: HttpUserAgent
alertDetailsOverride:
alertDisplayNameFormat: Suspicious access of {{CountOfDocs}} BEC related documents by {{User}}
alertDescriptionFormat: |
This query looks for users (in this case {{User}}) with suspicious spikes in the number of files accessed (in this case {{CountOfDocs}} events) that relate to topics commonly accessed as part of Business Email Compromise (BEC) attacks. The query looks for access to files in storage that relate to topics such as invoices or payments, and then looks for users accessing these files in significantly higher numbers than in the previous 14 days. Incidents raised by this analytic should be investigated to see if the user accessing these files should be accessing them, and if the volume they accessed them at was related to a legitimate business need.
This query contains thresholds to reduce the chance of false positives, these can be adjusted to suit individual environments. In addition false positives could be generated by legitimate, scheduled actions that occur less often than every 14 days, additional exclusions can be added for these actions on username or IP address entities. This query uses the imFileEvent schema from ASIM, you will first need to ensure you have ASIM deployed in your environment. Ref https://learn.microsoft.com/azure/sentinel/normalization-about-parsers
version: 1.0.5
kind: Scheduled
Stages and Predicates
Parameters
let sensitivity = 2.5;
let Events is inlined into the numbered stages below.
Let binding: BEC_Keywords
let BEC_Keywords = dynamic([ 'invoice','payment','paycheck','transfer','bank statement','bank details','closing','funds','bank account','account details','remittance','purchase','deposit',"PO#","Zahlung","Rechnung","Paiement", "virement bancaire","Bankuberweisung",'hacked','phishing']);
Stage 1: source
let Events
Stage 2: source
imFileEvent
Stage 3: where
where TimeGenerated between (ago(1209600s) .. now())
Stage 4: where
where User !~ "app@sharepoint"
Stage 5: where
where EventType =~ "FileAccessed"
Stage 6: extend
extend OriginalEvent
Stage 7: where
where OriginalEvent !~ "FileSyncDownloadedFull"
Stage 8: where
where EventProduct in~ ("Azure File Storage", "OneDrive", "SharePoint", "SharePoint 365")
Stage 9: where
where (FilePath contains "invoice" or FilePath contains "payment" or FilePath contains "paycheck" or FilePath contains "transfer" or FilePath contains "bank statement" or FilePath contains "bank details" or FilePath contains "closing" or FilePath contains "funds" or FilePath contains "bank account" or FilePath contains "account details" or FilePath contains "remittance" or FilePath contains "purchase" or FilePath contains "deposit" or FilePath contains "PO#" or FilePath contains "Zahlung" or FilePath contains "Rechnung" or FilePath contains "Paiement" or FilePath contains "virement bancaire" or FilePath contains "Bankuberweisung" or FilePath contains "hacked" or FilePath contains "phishing")
Stage 10: extend (3 consecutive steps)
extend SPuser, User, _AuthDetails
Stage 11: where
where isnotempty(User)
Stage 12: summarize
summarize by User
Stage 13: summarize
summarize CountOfDocs, TimeStamp by User
Stage 14: extend
extend Anomalies, Baseline, Score
Stage 15: mv-expand
mv-expand CountOfDocs
Stage 16: where
where Anomalies > 0
Stage 17: project
project Anomalies, Baseline, CountOfDocs, Score, TimeStamp, User
Stage 18: join
join kind=inner (Events) on TimeStamp, User
Stage 19: extend (4 consecutive steps)
extend IpAddr, NTDomain, Name, UPNSuffix
Stage 20: project-reorder
project-reorder
Indicators
These rows show field, operator, and value matches.
| Field | Kind | Values | Search |
|---|---|---|---|
Anomalies | gt |
| field:"Anomalies" kind:gt value:"0" |
EventProduct | in |
| field:"EventProduct" kind:in |
EventType | eq |
| field:"OperationName" kind:eq value:"FileAccessed" |
FilePath | match |
| field:"FilePath" kind:match |
OriginalEvent | ne |
| field:"OriginalEvent" kind:ne value:"FileSyncDownloadedFull" |
User | is_not_null | field:"user" kind:is_not_null | |
User | ne |
| field:"user" kind:ne value:"app@sharepoint" |
Output fields
These fields are emitted when the rule matches.
| Field | Source |
|---|---|
Anomalies | project |
Baseline | project |
CountOfDocs | project |
Score | project |
TimeStamp | project |
User | project |
IpAddr | extend |
Name | extend |
UPNSuffix | extend |
NTDomain | extend |