detecting-fileless-attacks-on-endpoints
by mukul975detecting-fileless-attacks-on-endpoints helps build detections for memory-only attacks on Windows endpoints, including PowerShell abuse, WMI persistence, reflective loading, and process injection. Use it for Security Audit, threat hunting, and detection engineering with Sysmon, AMSI, and PowerShell logging.
This skill scores 78/100, which means it is a solid listing candidate for directory users who need fileless-attack detection guidance on endpoints. The repository provides a real workflow, concrete telemetry requirements, and reusable detection patterns/scripts, so an agent can trigger and apply it with less guesswork than a generic prompt. It is still somewhat limited by the lack of an install command and some implementation rough edges, so users should expect a practical but not fully polished workflow.
- Explicit trigger and scope for fileless malware, in-memory attacks, PowerShell abuse, and WMI persistence
- Operational content includes prerequisites, workflow steps, event IDs, Sigma/Splunk-style examples, and MITRE mappings
- Support files add leverage: scripts for log scanning plus references and a reusable telemetry template
- No install command in SKILL.md, so adoption may require manual setup and interpretation
- Some source excerpts show truncated or imperfect script/documentation details, which may create minor execution friction
Overview of detecting-fileless-attacks-on-endpoints skill
What this skill does
The detecting-fileless-attacks-on-endpoints skill helps you build detections for attacks that live in memory, abuse legitimate tools, and leave little or no dropped file on disk. It is aimed at endpoint defenders who need practical detection logic for PowerShell abuse, WMI persistence, reflective loading, and process injection.
Who it is for
Use the detecting-fileless-attacks-on-endpoints skill for Security Audit, detection engineering, and threat hunting on Windows endpoints. It is a good fit if you need to turn telemetry into rules, not just understand the malware after the fact.
Why it stands out
The main value is operational: it ties together telemetry prerequisites, technique mapping, and detection workflows so you can move from “suspicious memory-only behavior” to a deployable rule set. It is stronger than a generic prompt when you need endpoint signals like Sysmon, AMSI, and PowerShell logging to shape the answer.
How to Use detecting-fileless-attacks-on-endpoints skill
Install and activate it
Install the skill with npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-fileless-attacks-on-endpoints. Then invoke it with a goal that includes the environment, log sources, and the attack surface you care about, such as PowerShell, WMI, or process injection.
Give it the right input shape
For best detecting-fileless-attacks-on-endpoints usage, provide:
- endpoint type and OS version
- available telemetry: Sysmon, PowerShell 4104, AMSI, EDR, SIEM
- the technique or suspicion: encoded PowerShell, reflective DLL injection, WMI event subscription
- your output target: detection logic, hunt query, triage checklist, or telemetry gap review
Stronger prompt: “Build a detection plan for fileless attacks on Windows 11 endpoints with Sysmon, PowerShell Script Block Logging, and Microsoft Defender. Focus on PowerShell download cradles, WMI persistence, and encoded commands.”
Read these files first
For the fastest detecting-fileless-attacks-on-endpoints install and usage path, read SKILL.md first, then assets/template.md for the reporting structure, references/api-reference.md for event IDs and query patterns, references/standards.md for ATT&CK mapping, and references/workflows.md for the end-to-end flow. If you plan to automate or inspect behavior, review scripts/agent.py and scripts/process.py to see what indicators the skill actually looks for.
Workflow that produces better output
Use the skill in this order: enable telemetry, confirm event coverage, draft detection logic, map each rule to a technique, and then tune for noise. That sequence matters because fileless detection fails most often when the logs are incomplete or the detection is written before the telemetry is verified.
detecting-fileless-attacks-on-endpoints skill FAQ
Is this only for fileless malware?
No. The detecting-fileless-attacks-on-endpoints skill also covers living-off-the-land abuse that may start with scripts, launchers, or registry-based persistence. It is meant for memory-centric behavior, not classic file-dropping malware.
Do I need prior detection engineering experience?
Not necessarily. Beginners can use it if they already know their logging stack and can describe the suspicious behavior. The biggest blocker is usually not skill level, but missing telemetry or vague inputs.
How is this different from a normal prompt?
A normal prompt may produce generic hunting ideas. The detecting-fileless-attacks-on-endpoints skill is more useful when you need endpoint-specific workflow support: what to log, what to query, what patterns matter, and what to exclude because it is outside the fileless scope.
When should I not use it?
Do not use it for file-based malware analysis, broad incident response playbooks, or reverse engineering tasks that focus on binaries rather than endpoint execution traces. It is also a poor fit if your environment has no usable PowerShell, Sysmon, or AMSI data.
How to Improve detecting-fileless-attacks-on-endpoints skill
Start with concrete telemetry facts
The best improvement for detecting-fileless-attacks-on-endpoints is to specify exactly what is enabled. “We have EDR” is too vague; “Sysmon Event IDs 1, 8, 19, 20, 21 and PowerShell 4104 are enabled, but AMSI is not” lets the skill avoid unrealistic recommendations.
Name the technique and the success criteria
Tell it whether you want detection for encoded commands, reflective assembly loading, WMI persistence, or Defender tampering. Also say what “good” looks like: a SIEM query, a rule draft, a triage checklist, or a telemetry gap assessment. That narrows the output and makes the detecting-fileless-attacks-on-endpoints guide more actionable.
Provide examples, then ask for tuning
If you have a sample alert, a suspicious script block, or a short log excerpt, include it. The skill can then anchor the rule to observed behavior instead of broad patterns. After the first pass, ask it to reduce false positives, add ATT&CK mapping, or split one noisy rule into two narrower detections for Security Audit use.