Attack Ent T1518 001 Security Software Discovery

MITRE ATT&CK T1518.001: Security Software Discovery

When to use this skill

Use this skill when the task involves T1518.001, Security Software Discovery, 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 sub-technique.

Technique context

• ATT&CK domain: enterprise
• ATT&CK ID: T1518.001
• Technique name: Security Software Discovery
• Type: sub-technique
• ATT&CK URL: https://attack.mitre.org/techniques/T1518/001
• Tactics: discovery
• Platforms: IaaS, Linux, macOS, Windows
• Required permissions: Not specified
• Effective permissions: Not specified
• Defenses bypassed: Not specified

ATT&CK description

Adversaries may attempt to get a listing of security software, configurations, defensive tools, and sensors that are installed on a system or in a cloud environment. This may include things such as cloud monitoring agents and anti-virus. Adversaries may use the information from Security Software Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.

Example commands that can be used to obtain security software information are netsh, reg query with Reg, dir with cmd, and Tasklist, but other indicators of discovery behavior may be more specific to the type of software or security system the adversary is looking for. It is becoming more common to see macOS malware perform checks for LittleSnitch and KnockKnock software.

Adversaries may also utilize the Cloud API to discover cloud-native security software installed on compute infrastructure, such as the AWS CloudWatch agent, Azure VM Agent, and Google Cloud Monitor agent. These agents may collect metrics and logs from the VM, which may be centrally aggregated in a cloud-based monitoring platform.

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

• No ATT&CK mitigation relationships were present in the source STIX bundle.

Known threat context

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

• ABK (malware)
• APT38 (intrusion-set)
• APT42 (intrusion-set)
• Action RAT (malware)
• Amadey (malware)
• Aquatic Panda (intrusion-set)
• Astaroth (malware)
• AuTo Stealer (malware)
• Avenger (malware)
• BLUELIGHT (malware)
• BadPatch (malware)
• Bazar (malware)
• BlackByte (intrusion-set)
• BlackByte Ransomware (malware)
• Brute Ratel C4 (tool)
• Bumblebee (malware)
• CHIMNEYSWEEP (malware)
• CHOPSTICK (malware)
• Carberp (malware)
• Clop (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

• Isif Ibrahima, Mandiant