1200kmSECURITY RESEARCH
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T1657 Financial Theft — Attack Simulation

Adversaries may steal monetary resources from targets through extortion, social engineering, technical theft, or other methods aimed at their own financial gain at the expense of the availability of these resources for victims. Financial theft is the ultimate objective of several popular campaign types including extortion by ransomware, business email compromise (BEC) and fraud, "pig butchering," bank hacking, and exploiting cryptocurrency…

Complete technique description

Adversaries may steal monetary resources from targets through extortion, social engineering, technical theft, or other methods aimed at their own financial gain at the expense of the availability of these resources for victims. Financial theft is the ultimate objective of several popular campaign types including extortion by ransomware,[FBI-ransomware] business email compromise (BEC) and fraud,[FBI-BEC] "pig butchering,"[wired-pig butchering] bank hacking,[DOJ-DPRK Heist] and exploiting cryptocurrency networks.[BBC-Ronin]

Adversaries may Compromise Accounts to conduct unauthorized transfers of funds.[Internet crime report 2022] In the case of business email compromise or email fraud, an adversary may utilize Impersonation of a trusted entity. Once the social engineering is successful, victims can be deceived into sending money to financial accounts controlled by an adversary.[FBI-BEC] This creates the potential for multiple victims (i.e., compromised accounts as well as the ultimate monetary loss) in incidents involving financial theft.[VEC]

Extortion by ransomware may occur, for example, when an adversary demands payment from a victim after Data Encrypted for Impact [NYT-Colonial] and Exfiltration of data, followed by threatening to leak sensitive data to the public unless payment is made to the adversary.[Mandiant-leaks] Adversaries may use dedicated leak sites to distribute victim data.[Crowdstrike-leaks]

Due to the potentially immense business impact of financial theft, an adversary may abuse the possibility of financial theft and seeking monetary gain to divert attention from their true goals such as Data Destruction and business disruption.[AP-NotPetya]

Official technique definition · Open in the interactive matrix

Detection telemetry and configuration

These contracts are selected through exact technique-to-data-component relationships or explicitly labelled planning overrides. Configure a collector at the relevant observation point; a telemetry name alone is not coverage.

Application Log Content · source-mapped

DC0038 collection page — Select the application event family required by the detection and document its native schema before normalization.

Providers and collection configuration

  • Enable the application audit category or instrument the owned lab application at the authorization/action boundary.
  • Define a schema with timestamp, service, actor, object, action, result and correlation ID. Export structured records through an authenticated collector.
  • Redact secrets and personal content, separate audit from debug logs, set retention and verify delivery during rotation/restart.

Required normalized fields: service, action, actor, record_count, result.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0038",
  "collector": "illustrative-lab-collector",
  "observation": {
    "service": "lab-portal",
    "action": "export_requested",
    "actor": "lab-reader",
    "record_count": 3,
    "result": "authorized"
  }
}

Visibility limits: Debug output is not necessarily a durable audit trail. Application developers must emit the relevant event; installing a log pipeline does not make an absent event exist.

Command Execution · source-mapped

DC0064 collection page — Collect process command lines and relevant shell/interpreter audit; shell history alone is neither complete nor tamper-resistant.

Providers and collection configuration

  • Enable Script Block Logging through the policy/configuration for the installed edition. Forward Microsoft-Windows-PowerShell/Operational for Windows PowerShell, or PowerShellCore/Operational for PowerShell 7.
  • Retain script-block ID and fragment ordering alongside process creation. Protect access to collected script text; secrets may be included.
  • On Linux, use narrowly scoped Audit execution rules for the lab account and supported architectures, and retain joined SYSCALL/EXECVE/PATH records.

Required normalized fields: interpreter, command_line, actor_uid, session_id.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0064",
  "collector": "illustrative-lab-collector",
  "observation": {
    "interpreter": "/bin/sh",
    "command_line": "printf LAB_TELEMETRY_CHECK",
    "actor_uid": 1000,
    "session_id": "lab-session-1"
  }
}

Visibility limits: Script content and process command lines are different signals. Logging may be partial, fragmented, filtered or disabled; never assume a command line reveals everything executed.

File Modification · source-mapped

DC0061 collection page — Use file-integrity monitoring or scoped OS file-write auditing for general changes. Sysmon 2 records creation-time changes; it is not a general file-write event.

Providers and collection configuration

  • Microsoft Sysmon: Windows event-based collection; enable the event types needed below.
  • Linux Audit: Linux alternative for supported system-call and file events; different semantics and fields.
  • Apple Endpoint Security clients: macOS alternative where the subscribed event exists; requires an entitled, approved client, not an iOS collector.
  • On a disposable Windows host, review the installed Sysmon schema and current configuration; merge scoped event filters into the existing policy rather than replacing it.
  • Forward Microsoft-Windows-Sysmon/Operational to the lab collector. Preserve event ID, timestamp, computer, process identifiers and the original event.
  • For Linux or macOS, select the equivalent sensor separately and test its emitted fields; a Windows event ID does not transfer across platforms.

Required normalized fields: path, attribute, before, after.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0061",
  "collector": "illustrative-lab-collector",
  "observation": {
    "path": "C:\\Lab\\demo.txt",
    "attribute": "content_hash",
    "before": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
    "after": "bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb"
  }
}

Visibility limits: Event filtering and sensor versions change coverage. High-volume image-load and process-access collection needs tuning; endpoint events alone do not establish intent.

Logon Session Creation · source-mapped

DC0067 collection page — Enable Audit Logon and collect successful session creation on the receiving host; join session/logon IDs rather than only account names.

Providers and collection configuration

  • Use a lab-only GPO under Computer Configuration → Windows Settings → Security Settings → Advanced Audit Policy Configuration. Enable the specific subcategory named below.
  • For object-level auditing, configure a narrow system access control list (SACL) on the test object in addition to policy. Do not audit an entire production directory by default.
  • Forward Security events from the responsible host or controller; retain subject and target identities, object identifiers, result and original XML. Confirm effective policy with auditpol /get /category:*.

Required normalized fields: account, logon_id, logon_type, source_ip.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0067",
  "collector": "illustrative-lab-collector",
  "observation": {
    "account": "LAB\\analyst",
    "logon_id": "0x12345",
    "logon_type": 3,
    "source_ip": "192.0.2.10"
  }
}

Visibility limits: A policy checkbox alone does not guarantee an event. Host role, SACL, success/failure selection and audit policy precedence matter. Directory changes may arrive as multiple records.

Process Creation · source-mapped

DC0032 collection page — Collect Sysmon ProcessCreate (1); preserve ProcessGuid and parent identifiers. Security 4688 is an alternative with separate audit/command-line settings.

Providers and collection configuration

  • Microsoft Sysmon: Windows event-based collection; enable the event types needed below.
  • Linux Audit: Linux alternative for supported system-call and file events; different semantics and fields.
  • Apple Endpoint Security clients: macOS alternative where the subscribed event exists; requires an entitled, approved client, not an iOS collector.
  • On a disposable Windows host, review the installed Sysmon schema and current configuration; merge scoped event filters into the existing policy rather than replacing it.
  • Forward Microsoft-Windows-Sysmon/Operational to the lab collector. Preserve event ID, timestamp, computer, process identifiers and the original event.
  • For Linux or macOS, select the equivalent sensor separately and test its emitted fields; a Windows event ID does not transfer across platforms.

Required normalized fields: process_guid, image, parent_image, command_line, user.

<EventFiltering>
  <ProcessCreate onmatch="include">
    <Image condition="is">C:\Windows\System32\whoami.exe</Image>
  </ProcessCreate>
</EventFiltering>

This fragment only selects the named process. It is not a complete production policy. Inspect the installed schema with sysmon64 -s; preserve existing rules, then apply the reviewed complete configuration with sysmon64 -c <configuration-file>.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0032",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_guid": "lab-process-001",
    "image": "C:\\Windows\\System32\\whoami.exe",
    "parent_image": "C:\\Windows\\System32\\cmd.exe",
    "command_line": "whoami",
    "user": "LAB\\analyst"
  }
}

Visibility limits: Event filtering and sensor versions change coverage. High-volume image-load and process-access collection needs tuning; endpoint events alone do not establish intent.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0495 Detection Strategy for Financial Theft

MITRE detection strategy

AN1361 Analytic 1361

Monitor for anomalous access to financial applications, browser-based banking sessions, or enterprise ERP systems from Windows endpoints. Detect mass emailing of payment instructions, sudden rule changes in Outlook for financial staff, or use of clipboard data exfiltration tied to cryptocurrency wallet addresses.

Platforms: Windows.

AN1362 Analytic 1362

Monitor server and endpoint logs for unusual outbound network connections to cryptocurrency nodes, unauthorized scripts accessing financial systems, or automation targeting payment file formats. Detect curl/wget activity aimed at exfiltrating transaction data or credentials from financial apps.

Platforms: Linux.

  • Command Execution — auditd:SYSCALL; channel execve: Execution of curl, wget, or custom scripts accessing financial endpoints.
  • Application Log Content — linux:syslog; channel Authentication attempts into finance-related servers from unusual IPs or times.

AN1363 Analytic 1363

Monitor unified logs for access to payment applications, browser plug-ins, or Apple Pay services from non-standard processes. Detect anomalous use of Automator scripts or keychain extraction targeting financial account credentials.

Platforms: macOS.

  • Process Creation — macos:unifiedlog; channel Non-standard processes invoking financial applications or payment APIs.
  • Application Log Content — macos:unifiedlog; channel Anomalous keychain access attempts targeting payment credentials.

AN1364 Analytic 1364

Monitor SaaS financial systems (e.g., QuickBooks, Workday, SAP S/4HANA cloud) for unauthorized access, rule changes, or mass export of financial data. Detect anomalous transfers initiated via SaaS APIs or new MFA-disabled logins targeting finance apps.

Platforms: SaaS.

  • Application Log Content — saas:finance; channel Transaction/Transfer: Unusual or large transactions initiated outside business hours or by unusual accounts.

AN1365 Analytic 1365

Monitor email and document management systems for fraudulent invoices, impersonation of vendors, or BEC-style payment redirections. Detect abnormal editing of invoice templates, or emails containing known fraud language combined with attachment delivery.

Platforms: Office Suite.

  • Application Log Content — m365:unified; channel MailSend: Outlook messages with suspicious subject/body terms (e.g., urgent payment, wire transfer) targeting finance teams.
  • File Modification — m365:office; channel Anomalous editing of invoice or payment document templates.
Source rule directory and observation requirements

No exact-tagged Sigma source rule was imported. This does not establish that the technique is undetectable; the MITRE guidance and collection requirements remain relevant.

Before treating a rule as coverage

  1. Read the actual condition and logsource; identify attacker-side, victim-side or third-party visibility.
  2. Map native sensor fields, parse times and identities, then compile for the selected backend.
  3. Replay a behavior-positive case, a normal control, an authorized look-alike and a missing-telemetry case.
  4. Record matches and misses with rule version and source events. No match is inconclusive when required telemetry is absent.

Anomaly-based detection

No exact technique-specific Atlas model is present for T1657 in the selected source snapshot. The following is a design worksheet, not a newly validated model.

Anomaly engineering worksheet

Start from the exact analytic above. The collection-specific lenses below are analyst recommendations; they do not assert that an arbitrary statistical deviation detects this technique.

  • Application and service audit: Per application, client and route: request rate, rare actions, failure ratios and unusual state transitions. Version changes, retries, health probes and seasonal load need separate baselines.
  • Script and command execution: Per host role and principal: rare interpreters, command argument patterns and parent-child sequences. Normalize scripts carefully; obfuscation, administrative automation and missing command lines change visibility.
  • Endpoint activity: Per host role and user: rare process/object combinations, bursts of object access or modification, and ordered parent/action sequences. Compare maintenance windows and signed software rollout activity.
  • Windows and directory audit: Per principal, host and object: unusual access/request rates, new principal-object relationships, and changes outside approved administration windows. Control for service accounts and scheduled directory maintenance.
  1. Define an entity/peer group and feature; exclude the evaluation period from baseline training.
  2. Use representative normal and maintenance activity. Do not invent a production threshold from a synthetic example.
  3. Evaluate held-out behavior-positive and benign cases; measure false positives, misses and telemetry loss separately.
  4. Keep abnormality separate from maliciousness. Correlate with the behavior-specific source evidence.

Anomaly Detection Atlas · Baseline, validation and blind spots

Attack tools and documented software

No reviewed lab-tool association is selected for this exact technique. This is a curation gap, not a statement that no tool can implement the behavior.

Software observed in source procedures

These are exact ATT&CK software-use relationships, including malware. They provide behavior context, not recommendations to download or execute malware. No safety or detector claim is inherited.

8 source-documented software associations

Simulation design and documented procedures

Atomic evidence: no compatible candidate in this snapshot. Live lab status: not run for these imported procedures.

Use disposable lab hosts and test accounts, explicit target allowlists, a clean snapshot, bounded egress and a restore plan. Review every candidate and dependency before any execution.

No compatible Atomic procedure is present in this pinned evidence set. Technical feasibility has not been ruled out. A custom procedure must define the behavior, target, collection point, success observable and rollback before execution.

Technique-specific experiment contract

  1. Choose one procedure implementing T1657 Financial Theft; identify the observable behavior in the source definition, not just its tactic.
  2. Record exact target, tool/version, inputs, privileges, network limits and approval. Never run an imported default target automatically.
  3. Enable the collection sources above and verify a benign baseline reaches the detector.
  4. Run only the approved isolated scenario; capture native events and an independent behavior observable.
  5. Evaluate the exact rule/model, restore the lab, and preserve configuration, event hashes, alerts, controls and misses.

Synthetic logs and offline contract check

Download synthetic collection fixture (JSON) · Download the complete engineering workbook

This fixture exercises the listed collection fields. It does not reproduce Financial Theft, label its example events as malicious, or measure detection effectiveness. Use the exact analytic and selected procedure to build an independently labelled behavior-positive dataset.

Not run in this browser. No network scan or attack command is executed by this control.

Validation status and remaining work

Source identity
Joined by exact technique/object IDs against hash-pinned sources.
Collection fixture
Available for offline schema exercises; not attack emulation.
Native telemetry / backend / real attack
Not validated for these imported procedures. Source fidelity and page tests cannot establish sensor or detector effectiveness.

All-page audit and evidence inventory · This page’s machine-readable workbook

Sources and evidence boundaries

Pinned MITRE STIX source · SHA-256 81113ba98afa2928f3dcff62022539f7ce30c315c32e14422f11ff95ce534352. Definition and procedure context are reproduced from this snapshot, not independently re-investigated incidents.

Source-linked mitigations
  • M1017 User Training

    Train and encourage users to identify social engineering techniques used to enable financial theft. Also consider training users on procedures to prevent and respond to swatting and doxing, acts increasingly deployed by financially motivated groups to further coerce victims into satisfying ransom/extortion demands.[Cyber Safety Review Board: Lapsus][SWAT-hospital]

  • M1018 User Account Management

    Limit access/authority to execute sensitive transactions, and switch to systems and procedures designed to authenticate/approve payments and purchase requests outside of insecure communication lines such as email.

Connected ecosystem references

Linked tags

enterprisecloudcloud-hosted-endpointonpremsaasLinuxmacOSOffice SuiteSaaSWindowsimpactisolated_authorized_labprocedure_review_requiredtelemetry_configuration_requireddisposable_tenant_and_cost_controlspotential_disruption_requires_individual_review
No Atomic candidate in snapshottechniquesource_mapped

Detection and collection

T1657 detection workspace

No reviewed association in this snapshot.

Threat actor context

These are explicit actor-to-technique associations in the existing Threat Matrix snapshot, not attribution of an event or proof that a detector identifies the actor. No tool-to-actor relationship is inferred.

Existing research

Threat Matrix: knowledge routes, evidence and actor context

Pinned research references. No browser attack runner or production-validated detector is asserted. Imported procedures remain unvalidated; any bounded lab evidence has its own scope. ATT&CK / Atomic provenance · Detection provenance.