PentesterFlow is a terminal-based AI assistant for authorized penetration testing and bug hunting, guiding analysts through reconnaissance, testing, evidence gathering, and reporting while requiring human approval for sensitive actions. Security engineers use it with local or hosted language models and real security tools, and the catalogue add-ons extend its workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add PentesterFlow/agent --skill graphqlgit clone --depth 1 https://github.com/PentesterFlow/agentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pentesterflow/agent/graphql)<a href="https://agentmods.dev/skills/pentesterflow/agent/graphql"><img src="https://agentmods.dev/badge/skills/pentesterflow/agent/graphql/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pentesterflow/agent/graphql"><img src="https://agentmods.dev/badge/skills/pentesterflow/agent/graphql.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.01383 |
| Opus 5.5 | $0.00030 | $0.00553 |
| Sonnet 5.5 | $0.00015 | $0.00277 |
| Haiku 4.5 | $0.00007 | $0.00138 |
Grade A, and why
graphql scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Execution rule: resolve the real GraphQL endpoint first, then run concrete `http`/curl requests against it. Never write literal placeholders such as `<other-id>` to files; ask once if required IDs or sessions are missing How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GraphQL playbook
Execution rule: resolve the real GraphQL endpoint first, then run concrete http/curl requests against it. Never write literal placeholders such as <other-id> to files; ask once if required IDs or sessions are missing.
Standard endpoints to probe first (use http with GET / POST):
/graphql, /graphiql, /api/graphql, /v1/graphql, /v2/graphql, /query, /api/query.
1. Confirm it's GraphQL
POST a tiny query — every implementation answers this:
{"query":"{__typename}"}
A reply containing {"data":{"__typename":"Query"}} confirms the endpoint. Note the response shape: { "data": ..., "errors": [...] }.
2. Schema discovery
2a. Introspection (the easy path)
{"query":"query IntrospectionQuery { __schema { queryType { name } mutationType { name } subscriptionType { name } types { ...FullType } } } fragment FullType on __Type { kind name description fields(includeDeprecated: true) { name description args { ...InputValue } type { ...TypeRef } isDeprecated deprecationReason } inputFields { ...InputValue } interfaces { ...TypeRef } enumValues(includeDeprecated: true) { name } possibleTypes { ...TypeRef } } fragment InputValue on __InputValue { name description type { ...TypeRef } defaultValue } fragment TypeRef on __Type { kind name ofType { kind name ofType { kind name ofType { kind name ofType { kind name ofType { kind name ofType { kind name ofType { kind name } } } } } } } }"}
Save the response — every later attack starts from this schema. Use file_write to keep it next to the engagement notes.
2b. Introspection disabled? Use field suggestions
Apollo and most other servers leak field names through error messages:
{"query":"{ user { secrt } }"}
Reply often contains Did you mean "secret"?. Iterate to enumerate the schema field-by-field. Read read_payloads(skill="graphql", file="field-suggestion-probes.txt") for a starter list.
2c. Aliased introspection bypass
Some WAFs / middleware block the __schema keyword. Bypass with an alias:
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 138 lines · 75 tokens per session scan A 19bd471187b9
graphql is a skill published in the GitHub repository PentesterFlow/agent (1,402 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 75 tokens to every session and 1,383 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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