Hunting skill for graphql vulnerabilities. Built from 12 public bug bounty reports across IDOR via node() / GID, mutation IDOR including AI/LLM features, cross-tenant IDOR, SSRF via argument, batching-DoS, query-cost-bypass, SQLi via argument, broken-object-level-authz, auth-bypass via unscoped mutations, and PII exposure from missing field-level authz. Use when hunting graphql on any target.
72
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Critical
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Security
2 findings: 1 critical severity, 1 high severity. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
The document contains explicit, actionable exploitation techniques (curl/GraphQL payloads and sequences) enabling unauthorized privilege persistence, cross-tenant data access/exfiltration, SSRF to cloud metadata, CI compromise, and account takeover — a high-abuse offensive playbook.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The skill contains multiple curl and API examples that embed Authorization headers and a password field directly in commands/payloads, which instructs including secret tokens/passwords verbatim in outputs and is therefore high-risk credential handling.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
This skill’s required workflow (Step 1/2/3/5/6/7) involves sending GraphQL introspection/queries and replaying mutations to a target URL, meaning any fetched runtime responses/body text (including error messages and “did you mean …” suggestions) returned by the outsider’s GraphQL server can be ingested into the agent/LLM context.
6b9c96e
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