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 analyzing-ransomware-network-indicatorsgit 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/analyzing-ransomware-network-indicators)<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/analyzing-ransomware-network-indicators"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-ransomware-network-indicators/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/analyzing-ransomware-network-indicators"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-ransomware-network-indicators.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 | $0.00072 | $0.00751 |
| Opus 5 | $0.00036 | $0.00376 |
| Sonnet 5 | $0.00014 | $0.00150 |
| Haiku 4.5 | $0.00007 | $0.00075 |
Grade A, and why
analyzing-ransomware-network-indicators 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
94% identical to analyzing-ransomware-network-indicators — 4 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.
What it actually says
Analyzing Ransomware Network Indicators
Overview
Before and during ransomware execution, adversaries establish C2 channels, exfiltrate data, and download encryption keys. This skill analyzes Zeek conn.log and NetFlow data to detect beaconing patterns (regular-interval callbacks), connections to known TOR exit nodes, large outbound data transfers, and suspicious DNS activity associated with ransomware families.
When to Use
- When investigating security incidents that require analyzing ransomware network indicators
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Zeek conn.log files or NetFlow CSV/JSON exports
- Python 3.8+ with standard library
- TOR exit node list (fetched from Tor Project or threat intel feeds)
- Optional: Known ransomware C2 IOC list
Steps
- Parse Connection Logs — Ingest Zeek conn.log (TSV) or NetFlow records into structured format
- Detect Beaconing Patterns — Calculate connection interval statistics (mean, stddev, coefficient of variation) to identify periodic callbacks
- Check TOR Exit Node Connections — Cross-reference destination IPs against current TOR exit node list
- Identify Data Exfiltration — Flag connections with unusually high outbound byte ratios to external IPs
- Analyze DNS Patterns — Detect DGA-like domain queries and high-entropy subdomains
- Score and Correlate — Apply composite risk scoring across all indicator types
- Generate Report — Produce structured report with timeline and MITRE ATT&CK mapping
Expected Output
- JSON report with beaconing detections and interval statistics
- TOR exit node connection alerts
- Data exfiltration flow analysis
- Composite ransomware risk score with MITRE mapping (T1071, T1573, T1041)
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 · 91 lines · 72 tokens per session scan A 1e1c08200fe8
analyzing-ransomware-network-indicators is a skill published in the GitHub repository Youngmaidainon/Agent-Level-Up (3 stars, last pushed 16d ago), licensed MIT. It adds 72 tokens to every session and 751 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to analyzing-ransomware-network-indicators, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
analyzing-ransomware-network-indicators
Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis.
analyzing-ransomware-network-indicators
Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis.
analyzing-ransomware-network-indicators
Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis.
analyzing-ransomware-network-indicators
Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis.
analyzing-ransomware-network-indicators
Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis.
analyzing-ransomware-network-indicators
Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis.