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
66
58%
Does it follow best practices?
Impact
Pending
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 technically strong and highly specific description that clearly communicates concrete capabilities in ransomware network analysis. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The domain-specific terminology is excellent for distinguishing it from other security or network analysis skills.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when investigating ransomware incidents, analyzing suspicious network traffic for C2 activity, or reviewing Zeek/NetFlow logs for indicators of compromise.'
Consider adding common user-facing variations like 'malware network analysis', 'IOC detection', or 'network forensics' to broaden trigger coverage for users who may not use the most specific terminology.
| 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 | Excellent coverage of natural terms 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 keywords in the cybersecurity domain. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a very clear niche: ransomware-specific network indicator analysis using Zeek and NetFlow. The combination of ransomware focus, specific indicator types, and named tools makes it extremely unlikely to conflict with other skills. | 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 analytical steps for ransomware network indicator detection but provides zero executable code, no concrete thresholds or detection logic, and no examples of input/output data. For a technically complex, multi-step analysis workflow, the absence of concrete implementation details severely limits its utility.
Suggestions
Add executable Python code for at least the core steps: parsing Zeek conn.log, calculating beaconing statistics with specific threshold values (e.g., coefficient of variation < 0.2), and cross-referencing TOR exit nodes.
Include a concrete input/output example showing a sample conn.log snippet and the expected JSON report structure with actual field names and values.
Add validation checkpoints such as verifying log format before parsing, confirming TOR exit node list freshness, and sanity-checking beaconing detection results against known benign periodic connections (e.g., NTP, heartbeat services).
Remove the generic 'When to Use' section and fold any essential context into the overview to improve conciseness.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is reasonably structured but includes some unnecessary filler (e.g., the 'When to Use' section with generic bullet points that don't add value for Claude, and the overview restates what the steps already convey). Could be tightened. | 2 / 3 |
Actionability | No executable code, no concrete commands, no specific examples of parsing Zeek conn.log, no actual beaconing detection logic, no threshold values, no sample queries. The steps are entirely descriptive rather than instructive — they describe what to do without showing how. | 1 / 3 |
Workflow Clarity | Steps are listed in a logical sequence, but there are no validation checkpoints, no error handling guidance, no feedback loops for false positives, and no thresholds or decision criteria (e.g., what coefficient of variation indicates beaconing). For a multi-step analytical workflow involving security-critical decisions, this lacks the rigor needed for a score of 3. | 2 / 3 |
Progressive Disclosure | The content has some structural organization with sections, but everything is inline with no references to external files for detailed content (e.g., a separate file for TOR exit node fetching, beaconing detection code, or IOC lists). The skill would benefit from splitting detailed implementation into referenced files. | 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
c15f73d
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.