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BD hunt-sqli

Hunting skill for sqli vulnerabilities. Built from 12 public bug bounty reports including modern NoSQL injection (Rocket.Chat CVE-2021-22911 MongoDB $regex, Mongoose ORM CVE-2024-53900 $where bypass), modern ORM raw-fragment SQLi (Django CVE-2024-42005, Sequelize GHSA-wrh9-cjv3-2hpw), second-order SOQL injection (HackerOne Salesforce), time-based blind SQLi in GraphQL resolvers, and SQLi on OIDC-proxy backends. Use when hunting SQLi on any target. Dedicated NoSQL operator injection (MongoDB/CouchDB $where/$regex/$ne) is owned by hunt-nosqli — NoSQL appears here only as adjacent ORM/WAF context.

elementalsouls/Claude-BugHunter Agent Skills author: elementalsouls 1 file body ≈ 5 306 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Hunting skill for sqli vulnerabilities.

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches

ProcedureMongoDBSalesforceGitHubPostgreSQLSecurityData and analyticsResearchtype 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
87/100
safety, quality, tests
Safety 60%
97
Quality 40%
72
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Risky intent intent-offensive-security SKILL.md:3
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    description: Hunting skill for sqli vulnerabilities. Built from 12 public bug bounty reports including modern NoSQL injection (Rocket.Chat CVE-…911 MongoDB $regex, Mongoose ORM CVE-…900 $w
  • low Risky intent intent-offensive-security SKILL.md:34
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
    SQL injection remains one of the highest-paying vulnerability classes in bug bounty because it directly threatens data confidentiality, integrity, and availability at scale.
    detector
  • low Risky intent intent-offensive-security SKILL.md:379
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
    A company's marketing site ran WordPress with the Huge IT Video Gallery plugin. The plugin's `album_id` parameter was unparameterized. Because the site shared database credentials with other services,
    detector

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

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5306 tokens (recommended < 5000); move details to references/
  • 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 41, 249, 369, 370): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 49/100

  • 0Result and completion. Does not say what the result is
  • 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. 8 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5306 tokens
  • 100Steps. 84 steps
  • 100Consistency. Name and required fields are in place
  • low 11 top-level sections: this looks like several domains in one skill

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 601: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 84 items
  • +4Has examples (19 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.