Recon Skills is a pack of security-testing skills covering reconnaissance, web applications, APIs, authentication, vulnerability validation, cloud infrastructure, and reporting. Security professionals use it for authorized assessments of systems they own or have written permission to test. The catalogue entries are individual skills from the pack.
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 uphiago/recon-skills --skill hunt-schema-enumerationgit clone --depth 1 https://github.com/uphiago/recon-skillsWrote 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/uphiago/recon-skills/hunt-schema-enumeration)<a href="https://agentmods.dev/skills/uphiago/recon-skills/hunt-schema-enumeration"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-schema-enumeration/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/uphiago/recon-skills/hunt-schema-enumeration"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-schema-enumeration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Supply Chain · line 30 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 64 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 64 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00039 | $0.01546 |
| Opus 5 | $0.00019 | $0.00773 |
| Sonnet 5 | $0.00008 | $0.00309 |
| Haiku 4.5 | $0.00004 | $0.00155 |
Grade A, and why
hunt-schema-enumeration scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl --max-time 30 --connect-timeout 10 -sk "${SUPABASE_URL}/rest/v1/${table}?select=*&limit=1" \ How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
The target API returns structured error messages (JSON) that hint at valid table names, field names, or endpoint paths. This is the single most productive black-box recon technique for REST/GraphQL APIs — one fuzz request reveals the entire database schema.
Most common on: PostgREST (Supabase), FastAPI (.NET), Zod (Next.js/Node), tRPC, GraphQL, and any framework with validation error details enabled in production.
Phase 1 — PostgREST Error Hint Enumeration
PostgREST is the REST API layer for Supabase/PostgreSQL. When you query a non-existent table, it returns a hint with the real table name.
SUPABASE_URL="https://PROJECT.supabase.co"
ANON_KEY="eyJ..."
# Fuzz with common table names — read the hints
for table in users profiles posts products orders data config settings; do
echo "=== $table ==="
curl --max-time 30 --connect-timeout 10 -sk "${SUPABASE_URL}/rest/v1/${table}?select=*&limit=1" \
-H "apikey: ${ANON_KEY}" \
-H "Authorization: Bearer ${ANON_KEY}" 2>/dev/null | python3 -c "
import sys,json
d=json.load(sys.stdin)
hint=d.get('hint','')
if hint: print(f' -> {hint}')
"
done
# The response pattern:
# {"hint":"Perhaps you meant the table 'public.real_table_name'"}
# {"hint":"Perhaps you meant the table 'public.user_sessions'"}
Build a wordlist for targeted fuzzing:
# Common patterns found in field:
# - Game apps: hands, scores, sessions, players, items, inventory
# - SaaS: subscriptions, subscribers, billing, invoices, teams, api_keys
# - Health: patients, appointments, assessments, prescriptions
# - Gov: citizens, certificates, documents, protocols
# - Finance: transactions, accounts, wallets, withdrawals, deposits
Phase 2 — Zod/FastAPI Validation Error Mining
Modern frameworks return detailed validation errors exposing all expected fields.
FastAPI (.NET/Go)
# POST with empty body or wrong fields
curl --max-time 30 --connect-timeout 10 -sk -X POST "https://api.target.com/endpoint" \
-H "Content-Type: application/json" -d '{}' 2>/dev/null
# Response reveals ALL required fields:
# {"errors":{"usuario":["required"],"senha":["required"]}}
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.
- 8d ago First seen · 162 lines · 39 tokens per session scan A 1abc5ff9883a
hunt-schema-enumeration is a skill published in the GitHub repository uphiago/recon-skills (1,254 stars, last pushed 10d ago), licensed MIT. It adds 39 tokens to every session and 1,546 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
Other skills, from other repositories
detecting-api-enumeration-attacks
Detect and prevent API enumeration attacks including BOLA and IDOR exploitation by monitoring sequential identifier access patterns and authorization failures.
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performing-aws-account-enumeration-with-scout-suite
Perform comprehensive security posture assessment of AWS accounts using ScoutSuite to enumerate resources, identify misconfigurations, and generate actionable security reports.
graphql-audit
GraphQL security hunting — introspection abuse, field suggestion enumeration (clairvoyance), batching DoS, IDOR via aliasing, auth bypass, injection via arguments, subscription abuse, depth/complexity bombs, and WAF bypass. Covers graphw00f fingerprinting, gqlmap, graphql-cop, and inql. Use when a target exposes a…
hunt-api-misconfig
Hunt API security misconfiguration — mass assignment, prototype pollution, HTTP verb tampering. Mass assignment: send {isadmin:true, role:admin, verified:true} on profile/account/reset endpoints — server blindly applies. JWT signature/crypto forging (alg:none, key confusion, kid/jku) is owned by hunt-jwt-crypto; this…
detecting-broken-object-property-level-authorization
Detect and test for OWASP API3:2023 Broken Object Property Level Authorization vulnerabilities including excessive data exposure and mass assignment attacks.