Detect Possible Teams BEC Attack by High Teams Recipients

Time window: 1d
Group by: AccountObjectId, SenderEmailAddress, SenderObjectId
Author: Robbe Van den Daele
Source: github.com/HybridBrothers/Hunting-Queries-Detection-Rules

An external sender suddenly increasing the amount of internal users they are sending messages to, can indicate that external user being compromised and used for BEC Attacks. In these kind of attacks compromised accounts are used to send phishing links or attachments to users in business relationships.

MITRE ATT&CK coverage

Tactic	Techniques
Initial Access	`T1566` Phishing

References

Rule body yaml

// Possible BEC detection by high teams recipients 
let increase_percentage = 200;
let base = (
    MessageEvents
    | where TimeGenerated > ago(14d)
    // Focus on chat messsages
    | where ThreadType == "chat"
    // Only return external users sending messages
    | join kind=leftanti (
        IdentityInfo
        | where TimeGenerated > ago(14d)
        | distinct AccountObjectId
    ) on $left.SenderObjectId == $right.AccountObjectId
    // Make a set of all the chats they are posting to, for every day
    | summarize ChatSet = make_set(ThreadId) by SenderEmailAddress, bin(TimeGenerated, 1d)
    // Count the amount of chats they posted to for each day
    | extend ChatAmmount = array_length(ChatSet)
);
// Get the average of send chats per external user per day
let averageBySender = (
    base
    | summarize AverageChatsBySender = avg(ChatAmmount) by SenderEmailAddress
);
// Check if the sender dubbled their chats to internal users compared to their baseline
base
| where TimeGenerated > ago(1d)
| join kind=inner averageBySender on SenderEmailAddress
| where ChatAmmount > AverageChatsBySender * (increase_percentage / 100)

Stages and Predicates

Parameters

let increase_percentage = 200;

Let binding: `averageBySender`

let averageBySender = (
    base
    | summarize AverageChatsBySender = avg(ChatAmmount) by SenderEmailAddress
);

Derived from base.

The stages below define let base (the rule's main pipeline source).

Stage 1: `source`

MessageEvents

Stage 2: `where`

| where TimeGenerated > ago(14d)

Stage 3: `where`

| where ThreadType == "chat"

Stage 4: `join` (negated)

| join kind=leftanti (
        IdentityInfo
        | where TimeGenerated > ago(14d)
        | distinct AccountObjectId
    ) on $left.SenderObjectId == $right.AccountObjectId

Stage 5: `summarize`

| summarize ChatSet = make_set(ThreadId) by SenderEmailAddress, bin(TimeGenerated, 1d)

Stage 6: `extend`

| extend ChatAmmount = array_length(ChatSet)

The stages below run on base (the outer pipeline).

Stage 7: `where`

base
| where TimeGenerated > ago(1d)

Stage 8: `join`

| join kind=inner averageBySender on SenderEmailAddress

Stage 9: `where`

| where ChatAmmount > AverageChatsBySender * (increase_percentage / 100)

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

Field	Kind	Values
`ThreadType`	eq	`chat` transforms: `cased`

Output fields

Fields the rule emits when it matches. Chronicle authors list these in the outcome block; they appear on the detection and $risk_score drives alerting. Sentinel / Defender XDR rules build them up through project / summarize / extend stages. Sentinel maps these into alert fields via entityMappings and customDetails; Defender XDR custom detections surface them as alert fields directly.

Field	Source
`ChatSet`	`summarize`
`SenderEmailAddress`	`summarize`
`ChatAmmount`	`extend`

`j` / `k`	Scroll down / up
`d` / `u`	Half-page down / up
`gg` / `G`	Top / bottom
`h` / `l`	History back / forward
`f`	Follow link (`Shift` = new tab)
`/`	Focus search
`?`	Toggle this help
`↑` / `↓`	Navigate search results
`Enter`	Open highlighted result
`Esc`	Close results / dialog

`type:`	`events` / `rules` / `providers`
`vendor:`	`sigma` / `elastic` / `splunk` / `kusto` / `chronicle` (vendor name alone also works: `sigma:`, `kql:`, `secops:`…)
`tactic:`	TA-id, slug, or name: `credential_access`, `TA0006`
`technique:`	technique or sub-technique ID: `T1003`, `T1003.001` (alias `tech:`)
`severity:`	`critical` / `high` / `medium` / `low` / `informational` (alias `sev:`)
`risk_score`	Numeric comparison on the Elastic risk score (0 to 100): `risk_score>50`, `risk_score<=20`, `risk_score=99` (alias `risk`; Elastic rules only)
`stages:`	Rules with exactly N pipeline stages
`correlation:`	`single_event` / `sequence` / `alternatives` / `alternatives_cross_log` / `all_required` / `correlated`
`with:`	Co-occurrence event-id; stacks (`with:4624 with:4769`) to require all, while a comma list in one occurrence (`with:4624,4769`) is an either-or group. Implies multi-event
`like:`	Structural neighbors of a rule slug (equivalents + subsumption stricter / broader): `like:comsvcs_lsass_memory_dump-splunk-sysmon`
`groupby:`	Entity-grouping substring match against `group_by_keys`: `groupby:user`, `groupby:host`
`uses:`	Rules whose predicate tree touches the field (any kind, any value): `uses:CommandLine`
`excludes:`	Rules with top-level `not()` clauses on the field (FP whitelists): `excludes:ParentImage`
`field:` / `value:`	Predicate search; narrows rule cards to those with a matching leaf and drives the indicator tier. Unquoted = substring, wildcards allowed (`value:mimikatz`)
`indicator:`	Shorthand for `field:F value:V`: `indicator:Image=*\powershell.exe`
`kind:`	Filter by predicate kind. Narrows rule cards to those carrying a matching predicate leaf (`vendor:elastic kind:cidr_match`) and drives the indicator tier: `contains` / `starts_with` / `ends_with` / `regex` / `cidr` / `eq` / `in` … (operator aliases `op:`/`match:`)
`has:` / `no:`	`sample`, `field`, `notes`, `refs`, `trace`, `thirdparty`, `rule`, `pattern`, `timewindow`, `threshold`, `newterms`, `sigma`/`elastic`/`splunk`/`kusto`/`chronicle`
`-op:val`	Exclude matches; works on most operators but not `type:`/`like:`/`has:`/`no:` (use `no:<flag>` to exclude a rule flag): `tactic:execution -vendor:splunk`. Standalone `-kind:`/`-field:`/`-value:` drop every rule carrying a matching predicate leaf (`type:rules -kind:is_null`)
`field:"…"` / `value:"…"`	Quoted value = anchored exact match (also allows spaces): `value:"net user"`
`a,b`	Comma = OR inside one operator (`vendor:sigma,elastic`, `severity:high,critical`); repeating a facet merges the same way. `field:`/`value:` never split (literal commas)
`vendors:` / `stage:`	Singular and plural spellings fold to the canonical operator and value: `tactics:` = `tactic:`, `type:event` = `type:events`, `correlation:sequences` = `correlation:sequence`, `has:thresholds` = `has:threshold`
`"quoted phrase"`	Exact-match a multi-word phrase (free text)

Detect Possible Teams BEC Attack by High Teams Recipients

MITRE ATT&CK coverage

References

Rule body yaml

Stages and Predicates

Parameters

Let binding: `averageBySender`

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `join` (negated)

Stage 5: `summarize`

Stage 6: `extend`

Stage 7: `where`

Stage 8: `join`

Stage 9: `where`

Indicators

Output fields

Keyboard shortcuts

Search operators

Detect Possible Teams BEC Attack by High Teams Recipients

MITRE ATT&CK coverage

References

Rule body yaml

Stages and Predicates

Parameters

Let binding: averageBySender

Stage 1: source

Stage 2: where

Stage 3: where

Stage 4: join (negated)

Stage 5: summarize

Stage 6: extend

Stage 7: where

Stage 8: join

Stage 9: where

Indicators

Output fields

Let binding: `averageBySender`

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `join` (negated)

Stage 5: `summarize`

Stage 6: `extend`

Stage 7: `where`

Stage 8: `join`

Stage 9: `where`