T1684No distinct observable

Social Engineering

StealthLinux, macOS, Office Suite, SaaS, Windows

Where this stands

A reviewer read the telemetry and concluded there is nothing here to detect that a sibling technique does not already cover.

The distinguishing signal in all three analytics is a correlation across a time window, and Sigma cannot express it. AN2035 wants execution 'shortly after external communication' (EmailToExecutionWindow, NewLogonWindow), AN2037 wants a TicketToExecutionWindow between a help desk contact and a command, AN2036 wants a DownloadToExecutionWindow. Timeframes and aggregations are outside the constructs lib/sigma models, and once the window is dropped each analytic collapses onto an observable the corpus already publishes: AN2035's Office child process spawning is T1204's rule 190b7574 (Detect a document or archive application spawning a system utility) on the same process_creation/windows logsource, AN2035's browser-to-script chain and AN2037's curl|bash-from-a-chat pattern are T1204.004's rule 61894a28 (Detect an interpreter launched from the shell with a pasted one-liner), AN2036's download- […]

Covered instead by T1204, T1204.001, T1204.002, T1204.004, T1566, T1098.004.

What the technique is

Adversaries may use social engineering techniques to influence users to take actions that result in unauthorized access, approval of changes, disclosure of sensitive information, or execution of adversary-supplied instructions (i.e., introduction of malicious payloads or software), while minimizing technical indicators. Adversaries may leverage trust-building methods across multiple channels (e.g., executive, vendor, or help desk scenarios, including AI-enabled voice interactions) to prompt user-authorized actions such as password resets, MFA changes, financial approvals, or the disclosure of sensitive information. Adversaries may also leverage common business communications and workflows such as email, collaboration platforms, voice communications, recruiting processes, help desk interactions, and SaaS consent mechanisms to make malicious requests appear routine and legitimate. Additionally, adversaries have persuaded victims to take actions through references of current events, harnessing relevant themes to the work role or the organizations mission. For example, adversaries may use scare tactics (i.e., threaten repercussions for non-compliance) or otherwise incite victims’ emotions in order to generate a sense of urgency to take action. […]

Read it on attack.mitre.org

What MITRE says you would watch

AN2037
Detects users executing commands copied from chats, tickets, or emails, including curl|bash patterns, shell script launches from temp directories, credential changes, or SSH key additions shortly after communication events.
AN2035
Detects user execution of newly received content or instructions shortly after external communication, including script launches, Office child process spawning, browser-to-script execution chains, or credential prompts followed by new logon sessions.
AN2034
Detects consent grants, password resets, role changes, external sharing, or token creation shortly after user interaction with messages, invites, or help desk workflows. Emphasis is placed on unusual requester relationships, new device context, or off-hours approvals.