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
52
58%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/analyzing-ransomware-network-indicators/SKILL.mdQuality
Discovery
82%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong, highly specific description that clearly identifies concrete capabilities in ransomware network analysis with appropriate domain-specific terminology. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The technical specificity and distinctiveness are excellent.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when analyzing network logs for ransomware indicators, investigating suspicious C2 traffic, or reviewing Zeek/NetFlow data for signs of compromise.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: identifying C2 beaconing patterns, TOR exit node connections, data exfiltration flows, encryption key exchange, and specifies the tools/data sources (Zeek conn.log and NetFlow analysis). | 3 / 3 |
Completeness | Clearly answers 'what does this do' with specific capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The when is only implied by the nature of the actions described. | 2 / 3 |
Trigger Term Quality | Includes strong natural keywords a security analyst would use: 'ransomware', 'C2 beaconing', 'TOR exit node', 'data exfiltration', 'encryption key exchange', 'Zeek conn.log', 'NetFlow'. These are highly specific and natural terms in the cybersecurity domain. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a very clear niche — ransomware network indicator analysis using specific tools (Zeek conn.log, NetFlow). Unlikely to conflict with other skills due to the narrow, specialized domain. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
35%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads more like a high-level procedure outline than an actionable skill. It correctly identifies the key analysis steps for ransomware network indicators but provides no executable code, no concrete thresholds, no example data, and no validation steps. The content describes what to do without showing how to do it, which severely limits its utility for guiding Claude through actual analysis.
Suggestions
Add executable Python code for at least the core steps: parsing Zeek conn.log, calculating beaconing statistics (with specific threshold values like CV < 0.2), and checking IPs against a TOR exit node list.
Include a concrete example showing sample input data (e.g., a few lines of Zeek conn.log) and the expected JSON output format with actual field names and values.
Add validation checkpoints with specific decision criteria, e.g., 'If coefficient of variation > 0.3, likely not beaconing — investigate manually' and 'Verify TOR exit node list freshness: reject if older than 24 hours'.
Remove the 'When to Use' section entirely — it adds no actionable information — and trim the overview to a single sentence.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The 'When to Use' section is largely filler that Claude doesn't need (e.g., 'When investigating security incidents that require analyzing ransomware network indicators' is tautological). The overview also restates what the title already conveys. However, the steps and expected output sections are reasonably tight. | 2 / 3 |
Actionability | There is no executable code, no concrete commands, no example data formats, and no copy-paste ready snippets. The steps are described abstractly ('Calculate connection interval statistics', 'Cross-reference destination IPs') without showing how to actually do any of it. This is a description of a workflow, not an actionable skill. | 1 / 3 |
Workflow Clarity | The steps are listed in a logical sequence and cover the key phases of the analysis. However, there are no validation checkpoints, no error handling guidance, no feedback loops (e.g., what to do if beaconing detection yields false positives), and no thresholds or decision criteria for any step. | 2 / 3 |
Progressive Disclosure | The content is organized into clear sections with reasonable structure for a standalone file. However, given the complexity of the topic (7 multi-step processes each deserving detailed guidance), the skill would benefit from referencing separate files for code examples, IOC lists, or detailed procedures. No bundle files exist to support this. | 2 / 3 |
Total | 7 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- mukul975/Anthropic-Cybersecurity-Skills
- Commit
0445030
- Reviewed
Table of Contents
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