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T1059.006 Python — Detection Rules

Detection workspace for T1059.006 Python: 4 Sigma sources, 1 Atlas concepts and 0 anomaly models. No live detection validation.

Source-backed rule directory

Atlas deterministic concepts

T1059.006 Python

MATCH(python_execution) AND script_path OR parent_process NOT_IN approved_list -> ALERT

Anomaly models

No exact Atlas model in this snapshot.

ATT&CK analytic guidance

DET0063 Cross-Platform Behavioral Detection of Python Execution

AN0172 Analytic 0172

Detects Python execution via python.exe or py.exe with anomalous parent lineage (e.g., Office macros, LOLBAS), execution from unusual directories, or chained network/PowerShell/system-level activity.

AN0173 Analytic 0173

Detects native Python or framework-based execution from Terminal, embedded apps, or launchd jobs. Flags network calls, persistence writes, or system enumeration after Python launch.

AN0174 Analytic 0174

Detects Python execution from non-standard user contexts or cron jobs that invoke outbound traffic, access sensitive files, or perform process injection (e.g., ptrace or /proc memory maps).

AN0175 Analytic 0175

Detects Python script or interpreter execution on ESXi hosts via embedded BusyBox shells, nested installations, or dropped files via SSH or datastore mount. Flags unusual scripting or post-compromise enumeration behavior.

Connected ecosystem references

Linked tags

Simulation, tools and telemetry

T1059.006 simulation workspace

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 anomaly research

Original publication snapshot · Anomaly Detection Atlas

Pinned research references. No browser attack runner, live simulation result or validated detector is asserted. Source mappings and validation limits are preserved. ATT&CK / Atomic provenance · Detection provenance.