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T1697 Steal Application Specific Passwords — Attack Simulation

Adversaries may steal Application Specific Passwords (ASPs) to gain access to Valid Accounts, bypassing multifactor authentication (MFA) methods. ASPs are passwords typically used to give third-party applications or legacy devices (which do not support MFA methods) account access. An adversary may socially engineer a user into providing an ASP (using methods like Phishing for Information), generate an ASP for an already compromised account, or…

Complete technique description

Adversaries may steal Application Specific Passwords (ASPs) to gain access to Valid Accounts, bypassing multifactor authentication (MFA) methods. ASPs are passwords typically used to give third-party applications or legacy devices (which do not support MFA methods) account access.[Application Specific Passwords][Application Specific Passwords Push Sec]

An adversary may socially engineer a user into providing an ASP[UNC6293 ASP Creative Phishing Attack][Application Specific Passwords Phishing] (using methods like Phishing for Information), generate an ASP for an already compromised account,[Mandiant APT42-untangling][TAG APT42] or obtain an ASP stored on a system. Afterward, adversaries may use the ASP to access Valid Accounts and, in some cases, maintain Persistence, bypassing any form of MFA set on the account.

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.

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.

User Account Authentication · source-mapped

DC0002 collection page — Collect successful and failed sign-ins, authentication method, application and conditional-access context; distinguish account validation from session creation.

Providers and collection configuration

  • Enable/export the required identity sign-in and audit categories from the lab tenant to a protected destination. Document license, role and retention requirements.
  • Correlate issuance or administrative changes with later sign-ins using non-secret credential IDs, application IDs, user IDs and correlation IDs.
  • Exclude passwords, bearer tokens, cookies and private keys. Record success, failure, authentication context and application result separately.

Required normalized fields: account, application, result, reason, 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": "DC0002",
  "collector": "illustrative-lab-collector",
  "observation": {
    "account": "analyst@example.test",
    "application": "lab-portal",
    "result": "failure",
    "reason": "invalid_credential",
    "source_ip": "192.0.2.10"
  }
}

Visibility limits: A token creation record is not evidence of token use; a sign-in is not a complete record of every resource access. Some provider-side data is unavailable to the customer.

User Account Modification · source-mapped

DC0010 collection page — Enable Audit User Account Management and retain the changed attributes and target account; correlate approved administrative requests.

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: target_account, 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": "DC0010",
  "collector": "illustrative-lab-collector",
  "observation": {
    "target_account": "lab-temp",
    "attribute": "enabled",
    "before": false,
    "after": true
  }
}

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.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0926 Suspicious Acquisition and Use of Application-Specific Passwords

MITRE detection strategy

AN2077 Analytic 2077

Detect successful SaaS authentication through an application-specific or legacy credential mechanism from a source/client not previously associated with that account, correlated with new session establishment or subsequent access inconsistent with ApprovedASPUsage.

Platforms: SaaS.

AN2076 Analytic 2076

Detect successful Office Suite access using an authentication method that does not perform the account's expected MFA flow, correlated within ASPActivityWindow with first-seen client/application access, an anomalous source/device, or an ASP-related account credential change where available.

Platforms: Office Suite.

  • Application Log Content — m365:unified; channel Authentication/account audit event identifying app-password or applicable legacy-authentication activity .
  • User Account Authentication — azure:signinlogs; channel Successful account authentication with authentication/client properties inconsistent with normal MFA-backed access .
  • User Account Modification — idp:audit; channel ASP added/created where exposed by provider.

AN2075 Analytic 2075

Detect creation of an application-specific password for a user account, correlated within ASPActivityWindow with authentication from a source, device, client, or location outside the account's established baseline, or followed by authentication using a legacy/non-MFA authentication path inconsistent with ApprovedASPUsage.

Platforms: Identity Provider.

  • User Account Modification — idp:audit; channel Application-specific password created/added for account .
  • User Account Authentication — idp:authentication ; channel Successful authentication associated with legacy/application-specific credential flow .
  • Logon Session Creation — idp:session ; channel New session established from source/device inconsistent with account baseline .
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 T1697 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.
  • 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.
  • Identity and SaaS: Per identity and application: first-seen clients/resources, changes in authentication failures and session patterns, and unusual permission changes. Separate automation, travel, shared egress and identity-provider policy changes.
  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.

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 T1697 Steal Application Specific Passwords; 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 Steal Application Specific Passwords, 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

    ASPs can be obtained through social engineering, which your technique explicitly includes. Train users not to generate or disclose ASPs in response to unsolicited instructions.

  • M1018 User Account Management

    Restrict which users may create/use ASPs; disable ASP creation where unnecessary; remove existing ASPs. Microsoft allows admins to disable creation and separately delete existing ASPs; Google administrators can view/revoke users' application-specific passwords.

  • M1036 Account Use Policies

    Restrict authentication paths/clients/locations through which accounts using legacy/app-password authentication can authenticate. This matters because an ASP that has been stolen shouldn't automatically have unrestricted account reach.

  • M1042 Disable or Remove Feature or Program

    Disable ASP functionality where modern authentication is available. Microsoft specifically supports disabling users' ability to create app passwords and recommends disabling legacy authentication so existing app passwords no longer work.

Connected ecosystem references

Linked tags

Detection and collection

T1697 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.