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BC rafter-security

Security toolkit for AI workflows. Use when scanning code or repos for vulnerabilities, auditing third-party skills/MCPs/agent configs before installing, evaluating shell commands before running them, or generating secure design questions for new features. Provides `rafter run` (remote SAST + SCA, needs RAFTER_API_KEY), `rafter secrets` (offline secrets-only), `rafter agent exec --dry-run` (command-risk classification), and `rafter skill review`.

ClawHub Agent Skills author: Rafter v0.10.3 MIT-0 2 files body ≈ 2 353 tokens Open the sourceclawhub.ai↗ analyzed 10 h ago

Security toolkit for AI workflows.

As a process C 50/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

ProcedureAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
92
Quality 40%
85
Run on models
none yet
Process rating
C
50/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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
    • medium Dangerous commands cmd-pipe-to-shell SKILL.md:97
      Downloads and executes remote code from an unrecognised host (pipe to shell) (documentation of a security skill)
      - **High** (approval required): sudo rm, chmod 777, curl | bash
      security skill
    • low Dangerous commands cmd-privilege SKILL.md:97
      Privilege escalation / world-writable permissions (documentation of a security skill)
      - **High** (approval required): sudo rm, chmod 777, curl | bash
      security skill
    • low Risky intent intent-offensive-security SKILL.md:251
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      - **CRITICAL**: Credential exfiltration, destructive commands without safeguards, privilege escalation, clear malicious intent, severe injection vulnerabilities
      detector

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

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "last_updated"

    Process rating: all ten parameters 50/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 7 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web, git, node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 67 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2353 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 450: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 67 items
    • +3Output format is stated explicitly
    • +4Has examples (15 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This skill is a disclosed security-helper wrapper around the Rafter CLI, with some high-impact capabilities that users should understand before enabling.
    LLM: benign (medium) · VirusTotal: · 12 Sept 2026