SKILLEMALL.ai
GitHub ↗ RU Sign in

BC hunt-ssrf

Hunting skill for ssrf vulnerabilities. Built from 15 public bug bounty reports including AWS metadata SSRF (HackerOne $25k Analytics PDF, Shopify Exchange $25k, Capital One 106M-record breach, Dropbox/HelloSign $4,913), GCP metadata SSRF (Snapchat $4k), Azure IMDS SSRF (Azure DevOps $15k chain, ChatGPT Custom Actions MSRC), DNS rebinding SSRF (Concrete CMS, GitLab UrlBlocker), gopher-protocol-to-Redis-RCE (Yahoo Mail $15k), link-preview SSRF (Reddit Matrix $6k), and headless-browser PDF-generator SSRF chains. Use when hunting SSRF on any target — OOB Collaborator confirmation mandatory for blind cases.

elementalsouls/Claude-BugHunter Agent Skills author: elementalsouls 1 file body ≈ 6 633 tokens Open the sourcegithub.com↗ analyzed 3 h ago

Hunting skill for ssrf vulnerabilities.

As a process C 51/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

ProcedureAWSGoogle CloudAzureGitLabInfrastructuretype 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
86/100
safety, quality, tests
Safety 60%
95
Quality 40%
73
Run on models
none yet
Process rating
C
51/100
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

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 · 5

✓ No critical or high findings

Medium and low: 5
  • 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 ssrf vulnerabilities. Built from 15 public bug bounty reports including AWS metadata SSRF (HackerOne $25k Analytics PDF, Shopify Exchange $25k, Capital One 106M-record b
  • low Exfiltration exfil-webhook-url SKILL.md:226
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    curl -s "https://target.com/api/preview?url=…"
    placeholder
  • low Exfiltration exfil-webhook-url SKILL.md:231
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    -d '{"url":"https://YOUR_ID.oast.pro"}'
    placeholder
  • low Risky intent intent-offensive-security SKILL.md:461
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    An attacker who could register a Kubernetes API extension server (metrics-server equivalent) returned `302 Location: http://127.0.0.1:6443/api/v1/secrets` responses to the aggregation layer. Because t
  • low Risky intent intent-offensive-security SKILL.md:509
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - **`cloud-iam-deep`** — SSRF is the canonical entry to cloud metadata service. Chain primitive: SSRF → IMDSv1 token theft → `cloud-iam-deep` privilege escalation reaches `iam:CreateUser` / `sts:Assum

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

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6633 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "sources"
  • note frontmatter-key unknown frontmatter key "report_count"

Process rating: all ten parameters 51/100

  • 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
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 6633 tokens
  • 85Steps. 85 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 tags): a typed call is more reliable

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)
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 610: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 85 items
  • +3Output format is stated explicitly
  • +4Has examples (18 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.