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CB hunting-for-beaconing-with-frequency-analysis

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 8 files · 2 scripts body ≈ 1 792 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of…

As a process B 72/100 · Nearly there — weak spots: when it triggers, failures and branches

AnalyzerPeople and hiringtype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
86/100
safety, quality, tests
Safety 60%
92
Quality 40%
78
Run on models
none yet
Process rating
B
72/100
Nearly there
Failures and branches w 10
0
When it triggers w 12
20
Result and completion w 14
60
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 · 8

    ✓ No critical or high findings

    Medium and low: 8
    • low Risky intent intent-offensive-security references/api-reference.md:27
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      | < 5% | HIGH | Automated C2 beacon |
      detector
    • low Risky intent intent-offensive-security references/api-reference.md:100
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Common C2 Beacon Intervals
    • low Risky intent intent-offensive-security references/standards.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## MITRE ATT&CK Command and Control (TA0011)
    • low Risky intent intent-offensive-security references/standards.md:30
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Known C2 Framework Default Beacon Profiles
    • low Risky intent intent-offensive-security references/standards.md:40
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | Covenant | 10s | 10% | HTTP/S | .NET-based C2 framework |
    • low Risky intent intent-offensive-security references/workflows.md:143
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      5. Check for associated lateral movement or tool transfers
    • low Risky intent intent-offensive-security SKILL.md:80
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | JA3/JA4 Fingerprinting | TLS client fingerprinting to identify C2 framework signatures |
    • low Risky intent intent-offensive-security SKILL.md:156
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      4. **Sliver C2**: Modern C2 framework with HTTPS, mTLS, and WireGuard protocols, configurable beacon intervals with built-in jitter support.

    Files scanned: 8. 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 "d3fend_techniques"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 72/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 24 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1792 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    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
    • +4Description does not say when NOT to use the skill (false activations)
    • -43 reference files, but SKILL.md never points to them: the model will not open them
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 224: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 24 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.