Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Youngmaidainon/Agent-Level-Up --skill conducting-malware-incident-responsegit clone --depth 1 https://github.com/Youngmaidainon/Agent-Level-UpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/youngmaidainon/agent-level-up/conducting-malware-incident-response)<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/conducting-malware-incident-response"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/conducting-malware-incident-response/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/conducting-malware-incident-response"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/conducting-malware-incident-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00078 | $0.02232 |
| Opus 5 | $0.00039 | $0.01116 |
| Sonnet 5 | $0.00016 | $0.00446 |
| Haiku 4.5 | $0.00008 | $0.00223 |
Grade A, and why
conducting-malware-incident-response scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
91% identical to conducting-malware-incident-response — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conducting Malware Incident Response
When to Use
- EDR or antivirus detects malware execution on one or more endpoints
- A user reports suspicious system behavior indicative of malware infection
- Threat intelligence indicates a malware campaign targeting the organization's industry
- Network monitoring detects beaconing traffic consistent with known malware C2 patterns
- A file detonation in a sandbox returns a malicious verdict
Do not use for analyzing malware samples in a research context; use dedicated malware analysis procedures for reverse engineering.
Prerequisites
- EDR platform with process tree visibility and host isolation capability
- Malware sandbox environment (Cuckoo, ANY.RUN, Joe Sandbox, Hybrid Analysis)
- Access to threat intelligence platforms for malware family identification (VirusTotal, MalwareBazaar)
- Forensic imaging tools for evidence preservation (FTK Imager, KAPE)
- Clean system images or gold images for endpoint rebuild
- MITRE ATT&CK framework reference for technique mapping
Workflow
Step 1: Detect and Confirm Malware Presence
Validate the malware alert and gather initial indicators:
- Review EDR alert details: detection name, file path, hash (SHA-256), process tree
- Check if the detection is a known malware family or generic heuristic detection
- Query the file hash against VirusTotal, MalwareBazaar, and internal threat intelligence
- Examine the process execution chain to determine how the malware was delivered
Detection Summary:
File: C:\Users\jsmith\AppData\Local\Temp\update.exe
SHA-256: a1b2c3d4e5f6...
Detection: CrowdStrike: Malware/Qakbot | VirusTotal: 58/72 engines
Parent: WINWORD.EXE → cmd.exe → powershell.exe → update.exe
Delivery: Email attachment (Invoice-Nov2025.docm)
Network: HTTPS POST to 185.220.101[.]42:443 every 60s
Persistence: Scheduled Task "WindowsUpdate" → update.exe
Step 2: Scope the Infection
Determine how many systems are affected and the malware's propagation method:
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 223 lines · 78 tokens per session scan A 46d7d813f714
conducting-malware-incident-response is a skill published in the GitHub repository Youngmaidainon/Agent-Level-Up (3 stars, last pushed 16d ago), licensed MIT. It adds 78 tokens to every session and 2,232 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to conducting-malware-incident-response, differing in 7 lines, and is treated as a copy.
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