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BC performing-iot-security-assessment

Performs comprehensive security assessments of IoT devices and their ecosystems by testing hardware interfaces, firmware, network communications, cloud APIs, and companion mobile applications. The tester uses firmware extraction and analysis, hardware debugging via UART and JTAG, network protocol analysis, and runtime exploitation to identify vulnerabilities across all layers of the IoT stack. Activates for requests involving IoT security testing, embedded device assessment, firmware security analysis, or smart device penetration testing.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 2 935 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Performs comprehensive security assessments of IoT devices and their ecosystems by testing hardware interfaces, firmware, network communications, cloud APIs…

As a process C 61/100 · Has gaps — weak spots: failures and branches, running it twice, progress reporting

AnalyzerSecuritytype 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
B
90/100
safety, quality, tests
Safety 60%
96
Quality 40%
82
Run on models
none yet
Process rating
C
61/100
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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Risky intent intent-offensive-security SKILL.md:9
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      security analysis, or smart device penetration testing.
    • low Risky intent intent-offensive-security SKILL.md:121
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - **Lateral movement**: Demonstrate how a compromised IoT device can be used to attack other devices on the network
    • low Risky intent intent-offensive-security SKILL.md:148
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      **Context**: A company plans to deploy 200 IP cameras from a single vendor across its offices. Before deployment, the security team requests a penetration test of the camera to identify vulnerabilitie

    A further 1 matches are quotations in this security skill's documentation and are not counted as findings.

    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 61/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 69 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2935 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 544: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 69 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +1License stated

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