SKILLEMALL.ai

CC 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.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 2 779 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Analyzes network traffic generated by malware during sandbox execution or live incident response to identify C2 protocols, data exfiltration channels, payload…

As a process C 63/100 · Has gaps — weak spots: failures and branches, running it twice, progress reporting

AnalyzerSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
94
Quality 40%
82
Run on models
none yet
Process rating
C
63/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 6

    ✓ No critical or high findings

    Medium and low: 6
    • low Risky intent intent-offensive-security references/api-reference.md:84
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      msg:"MALWARE C2 Beacon";
      quoted
    • low Risky intent intent-offensive-security SKILL.md:5
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      payload downloads, and lateral movement patterns using Wireshark, Zeek, and Suricata.
    • low Risky intent intent-offensive-security SKILL.md:203
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # C2 beacon detection based on observed URI pattern
    • low Risky intent intent-offensive-security SKILL.md:205
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      msg:"MALWARE MalwareX C2 Beacon";
      quoted
    • low Risky intent intent-offensive-security SKILL.md:256
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | **Beaconing** | Regular periodic connections from malware to C2 server, identifiable by consistent time intervals and packet sizes |
    • low Risky intent intent-offensive-security SKILL.md:276
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      **Context**: Malware communicates with its C2 server using a custom binary protocol over TCP port 8443. Standard HTTP analysis yields no results. The protocol structure needs to be reverse engineered 

    Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 63/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2779 tokens

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 375: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 27 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.