SKILLEMALL.ai
GitHub ↗ RU Sign in

CC hunt-ldap

Hunt LDAP Injection and XPath Injection

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 3 328 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Hunt LDAP Injection and XPath Injection

As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

ProcedureSecuritytype 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
87/100
safety, quality, tests
Safety 60%
98
Quality 40%
71
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
When it triggers w 12
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: hunt-ldap (sickn33/agentic-awesome-skills)

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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Risky intent intent-offensive-security SKILL.md:35
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      > public platforms (most live on internal-pentest reports). This skill is
    • low Risky intent intent-offensive-security SKILL.md:167
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      password spraying, hash cracking or real attribute extraction without separately

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

    Against the Agent Skills spec

    • warning description-short description under 40 chars: too little signal for triggering
    • note frontmatter-key unknown frontmatter key "risk"
    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "source_repo"
    • note frontmatter-key unknown frontmatter key "source_type"
    • note frontmatter-key unknown frontmatter key "date_added"
    • note frontmatter-key unknown frontmatter key "license_source"
    • note frontmatter-key unknown frontmatter key "sources"
    • note frontmatter-key unknown frontmatter key "report_count"
    • note edit-residue the text marks something as outdated (lines 62): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 60/100

    • 0Result and completion. Does not say what the result is
    • 0When it triggers. No condition that starts the skill
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 21 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3328 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)
    • +3Description length 39: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (4 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.