Attack Ent T1005 Data From Local System

MITRE ATT&CK T1005: Data from Local System

When to use this skill

Use this skill when the task involves T1005, Data from Local System, enterprise ATT&CK, TTP mapping, detection engineering, hunting, incident-response enrichment, control validation, or authorized adversary-emulation planning. Treat it as a defensive analysis aid: keep outputs focused on understanding, detecting, mitigating, and safely validating this ATT&CK technique.

Technique context

• ATT&CK domain: enterprise
• ATT&CK ID: T1005
• Technique name: Data from Local System
• Type: technique
• ATT&CK URL: https://attack.mitre.org/techniques/T1005
• Tactics: collection
• Platforms: ESXi, Linux, macOS, Network Devices, Windows
• Required permissions: Not specified
• Effective permissions: Not specified
• Defenses bypassed: Not specified

ATT&CK description

Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.

Adversaries may do this using a Command and Scripting Interpreter, such as cmd as well as a Network Device CLI, which have functionality to interact with the file system to gather information.(Citation: show_run_config_cmd_cisco) Adversaries may also use Automated Collection on the local system.

Agent workflow

1. Clarify scope: identify the system, asset class, log sources, cloud or endpoint platform, and whether the user wants triage, detection, coverage assessment, or safe emulation planning.
2. Load bundled resources as needed: use references/technique-profile.json for structured metadata, references/detection-and-mitigation.md for triage and telemetry guidance, references/known-threat-context.md for ATT&CK relationship context, and templates/ for repeatable outputs.
3. Map observations to ATT&CK: compare the user's evidence to the ATT&CK description, tactics, platforms, and known procedure patterns before asserting a match.
4. Produce defensive outputs: prioritize hypotheses, telemetry requirements, detection logic ideas, validation steps, containment guidance, and mitigations.
5. Preserve uncertainty: distinguish confirmed evidence, plausible indicators, assumptions, and gaps. Recommend what to collect next.
6. Stay safe: do not provide malware, credential theft, persistence, evasion, destructive automation, or unauthorized exploitation instructions. For adversary emulation, keep steps bounded to approved lab or control-validation contexts and omit operational abuse details.

Bundled resources

• references/technique-profile.json: machine-readable ATT&CK metadata for this technique.
• references/detection-and-mitigation.md: detection notes, telemetry checklist, triage questions, mitigation candidates, and false-positive considerations.
• references/known-threat-context.md: ATT&CK relationship context with attribution cautions.
• templates/detection-brief.md: detection engineering brief template.
• templates/hunt-plan.md: threat hunt plan template.
• templates/incident-response-note.md: incident response note template.
• templates/coverage-assessment.md: ATT&CK coverage assessment template.
• scripts/render_brief.py: local helper that renders a Markdown defensive brief from technique-profile.json.
• assets/output-schema.json: JSON schema for structured technique analysis outputs.

To generate a quick brief, run python scripts/render_brief.py --output brief.md from inside this skill directory, or adapt the templates directly.

Detection guidance

No ATT&CK detection guidance was present in the source STIX object.

Useful telemetry and data sources

• Not specified in the STIX object.

Mitigations to consider

• Data Loss Prevention

Known threat context

Use these examples only as contextual leads, not as proof that an observed event is this technique:

• APT1 (intrusion-set)
• APT28 (intrusion-set)
• APT29 (intrusion-set)
• APT3 (intrusion-set)
• APT37 (intrusion-set)
• APT38 (intrusion-set)
• APT39 (intrusion-set)
• APT41 (intrusion-set)
• Action RAT (malware)
• Agrius (intrusion-set)
• Amadey (malware)
• Andariel (intrusion-set)
• Anthropic AI-orchestrated Campaign (campaign)
• AppleSeed (malware)
• Aquatic Panda (intrusion-set)
• AuTo Stealer (malware)
• Axiom (intrusion-set)
• BADFLICK (malware)
• BADNEWS (malware)
• BLINDINGCAN (malware)

Recommended output pattern

When responding with this skill, structure the answer as:

• Assessment: whether the evidence supports this ATT&CK mapping and why.
• Evidence: specific indicators, logs, behaviors, and assumptions.
• Detection: telemetry sources, analytic logic, and tuning considerations.
• Response: containment, eradication, recovery, and validation actions.
• Coverage gaps: missing logs, sensors, controls, or environmental details.
• References: include the ATT&CK URL and any user-provided evidence references.

ATT&CK contributors

• William Cain
• Austin Clark, @c2defense
• Liran Ravich, CardinalOps