SKILLEMALL.ai
RU Sign in

AC SQLMap Database Penetration Testing

This skill should be used when the user asks to "automate SQL injection testing," "enumerate database structure," "extract database credentials using sqlmap," "dump tables and columns from a vulnerable database," or "perform automated database penetration testing." It provides comprehensive guidance for using SQLMap to detect and exploit SQL injection vulnerabilities.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 2 887 tokens Open the sourcegithub.com↗ analyzed 2 d ago

This skill should be used when the user asks to "automate SQL injection testing," "enumerate database structure," "extract database credentials using sqlmap,"…

As a process C 59/100 · Has gaps — weak spots: result and completion, consistency, running it twice

ProcedureSecuritytype 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
A
91/100
safety, quality, tests
Safety 60%
96
Quality 40%
84
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
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:2
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      name: SQLMap Database Penetration Testing
    • low Risky intent intent-offensive-security SKILL.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      description: This skill should be used when the user asks to "automate SQL injection testing," "enumerate database structure," "extract database credentials using sqlmap," "dump tables and columns fro
      quoted
    • low Risky intent intent-offensive-security SKILL.md:9
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # SQLMap Database Penetration Testing
    • low Risky intent intent-offensive-security SKILL.md:21
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - **Authorization**: Written permission for penetration testing activities

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 59/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (SQLMap Database Penetration Testing) differs from the folder (sqlmap-database-pentesting)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 37 steps
    • 100Execution cost. Instruction body is 2887 tokens
    • 100Progress reporting. Reports progress
    • 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +3Description length 370: enough signal without eating the budget
    • +4Structure: 47 headings
    • +3Step-by-step instructions: 37 items
    • +4Has examples (24 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.