analyzing-network-traffic-of-malware
Analyzes network traffic generated by malware during sandbox execution or live incident response to identify C2 protocols, data exfiltration channels, payload downloads, and lateral movement patterns using Wireshark, Zeek, and Suricata. Activates for requests involving malware network analysis, C2 traffic decoding, malware PCAP analysis, or network-based malware detection.
85
82%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%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 an excellent skill description that clearly articulates specific capabilities (C2 identification, exfiltration detection, payload analysis, lateral movement detection), names concrete tools, and provides explicit trigger conditions. It uses proper third-person voice and covers both the 'what' and 'when' comprehensively with natural trigger terms that security analysts would use.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'identify C2 protocols, data exfiltration channels, payload downloads, and lateral movement patterns' using named tools (Wireshark, Zeek, Suricata). Also specifies contexts like 'sandbox execution or live incident response.' | 3 / 3 |
Completeness | Clearly answers both 'what' (analyzes network traffic to identify C2 protocols, exfiltration, payloads, lateral movement using specific tools) and 'when' ('Activates for requests involving malware network analysis, C2 traffic decoding, malware PCAP analysis, or network-based malware detection'). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'malware network analysis', 'C2 traffic decoding', 'malware PCAP analysis', 'network-based malware detection', 'C2 protocols', 'data exfiltration', 'Wireshark', 'Zeek', 'Suricata'. These cover common variations a security analyst would use. | 3 / 3 |
Distinctiveness Conflict Risk | Occupies a very clear niche: malware-specific network traffic analysis. The combination of malware focus, network traffic analysis, and specific tools (Wireshark, Zeek, Suricata) makes it highly distinct and unlikely to conflict with general networking or general malware analysis skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a highly actionable skill with excellent executable examples covering the full malware network analysis workflow. Its main weaknesses are verbosity (glossary tables and tool descriptions Claude doesn't need), lack of validation checkpoints in the workflow (e.g., verifying Suricata rules compile, confirming file extraction integrity), and a monolithic structure that could benefit from splitting reference material into separate files.
Suggestions
Add validation checkpoints: verify Suricata rules compile with 'suricata -T -S custom_malware.rules', verify extracted file integrity, and confirm Zeek log generation succeeded before proceeding to analysis.
Remove or drastically reduce the 'Key Concepts' glossary and 'Tools & Systems' sections — Claude already knows what Wireshark, Zeek, DGA, and DNS tunneling are.
Split the Common Scenarios, Output Format template, and reference material into separate linked files to reduce the main skill's token footprint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly comprehensive but includes some unnecessary sections like the 'Key Concepts' glossary table and 'Tools & Systems' descriptions that explain things Claude already knows (e.g., what Wireshark or Scapy are). The output format template is lengthy. However, the core workflow commands are lean and useful. | 2 / 3 |
Actionability | Excellent actionability throughout — every step includes fully executable bash commands and Python scripts that are copy-paste ready. The tshark commands, Scapy beacon detection script, DGA entropy detection script, and Suricata rule examples are all concrete and complete. | 3 / 3 |
Workflow Clarity | The 6-step workflow is clearly sequenced and logically ordered from initial overview through signature generation. However, there are no explicit validation checkpoints or feedback loops — for example, no step to verify extracted files aren't corrupted, no validation that Suricata rules compile correctly ('suricata -T -c ... -S custom_malware.rules'), and no error recovery guidance between steps. | 2 / 3 |
Progressive Disclosure | The content is a monolithic document with no references to external files for detailed content. The Key Concepts table, Tools & Systems section, Common Scenarios, and Output Format could be split into separate reference files. The document is quite long (~250 lines) and would benefit from a concise overview with links to detailed guides. | 2 / 3 |
Total | 9 / 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
888bbe4
- Reviewed
Table of Contents
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