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Api Noauth Hunt

CommunityPopular
uphiago
api-noauth-hunt

Use when an API may expose data or privileged operations without authentication.

Overview

Publisheruphiago
Repositoryrecon-skills
Skill nameapi-noauth-hunt
Stars
1.3K
Forks
213
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by uphiago on GitHub. Read the source before you install it.

Installation

Install the Api Noauth Hunt AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/uphiago/recon-skills.git /tmp/recon-skills
mkdir -p .claude/skills
cp -r /tmp/recon-skills/recon/api-noauth-hunt .claude/skills/api-noauth-hunt
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Noauth Hunt in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Api Noauth Hunt on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Api Noauth Hunt is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

API No-Authentication Validation

Identify API operations that may be reachable without the authentication or authorization required by their data and business function. Discovery is read-only by default. Write validation uses synthetic records and requires explicit authorization immediately before execution.

When to Use

  • Port scan reveals HTTP services on non-standard ports (3000, 5000, 8080-8085, 9000).
  • Target has an API subdomain (api.target.com, backend.target.com).
  • JavaScript bundles reference internal API endpoints.
  • After port-service-discovery finds HTTP on unexpected ports.
  • After firebase-supabase-attack identifies backend APIs.

Prerequisites

  • curl, python3, jq installed.
  • Target URL or IP:port of the suspected API.
  • List of common API paths for fuzzing.

How to Run

bash
# Quick API test — try common paths without auth
TARGET="https://api.target.com"
for path in "/" "/api" "/api/v1" "/api/users" "/api/health" "/docs" "/swagger.json"; do
  code=$(curl -sk -o /dev/null -w "%{http_code}" --max-time 5 --connect-timeout 5 "$TARGET$path")
  echo "HTTP $code: $TARGET$path"
done

Quick Reference

SignalWhat It MeansAction
HTTP 200 on /api/users or /api/clientsPossible unauthenticated data accessValidate one bounded sample
HTTP 2xx on POST without authPossible unauthenticated writeStop and obtain write authorization
OpenAPI/Swagger at /docs, /swagger.jsonFull API map exposedEnumerate all endpoints
Stack trace on errorInternal paths, framework versionMap infrastructure
State change via an unexpected methodPossible method-level authorization gapReproduce with a synthetic record
Login without password validationPossible authentication bypassVerify with an approved test account

Procedure

Phase 1 — API Discovery

bash
TARGET="$1"      # URL or IP:port
OUTDIR="$OUTDIR/api_recon"
mkdir -p "$OUTDIR"

echo "[*] API discovery on $TARGET"

# Common API paths
API_PATHS=(
  "/" "/api" "/api/v1" "/api/v2" "/v1" "/v2"
  "/api/users" "/api/clients" "/api/admin" "/api/health"
  "/api/auth" "/api/login" "/api/register"
  "/api/products" "/api/orders" "/api/contracts"
  "/docs" "/swagger.json" "/swagger.yaml" "/openapi.json"
  "/api-docs" "/swagger-ui.html" "/graphql"
  "/health" "/status" "/version" "/info" "/ping"
  "/actuator" "/actuator/health" "/actuator/info" "/actuator/env"
)

for path in "${API_PATHS[@]}"; do
  code=$(curl -sk -o /tmp/api_probe_$$.tmp -w "%{http_code}" --max-time 5 --connect-timeout 5 "$TARGET$path" 2>/dev/null)

  if [[ "$code" == "200" ]]; then
    body=$(cat /tmp/api_probe_$$.tmp)
    content_type=$(file -b --mime-type /tmp/api_probe_$$.tmp 2>/dev/null)

    # Check if it's JSON (likely API)
    if echo "$body" | python3 -c "import sys,json; json.load(sys.stdin)" 2>/dev/null; then
      record_count=$(echo "$body" | python3 -c "import sys,json; d=json.load(sys.stdin); print(len(d) if isinstance(d,list) else 'object')" 2>/dev/null)
      echo "  [API] $path → HTTP 200 (JSON, ${record_count} records)"
    elif echo "$body" | grep -qi "swagger\|openapi"; then
      echo "  [SWAGGER] $path → HTTP 200 (API documentation)"
    elif echo "$body" | grep -qi "graphql"; then
      echo "  [GRAPHQL] $path → HTTP 200"
    else
      echo "  [HTTP] $path → HTTP 200 (${#body} bytes, $content_type)"
    fi
  elif [[ "$code" == "401" || "$code" == "403" ]]; then
    echo "  [AUTH] $path → HTTP $code (protected)"
  elif [[ "$code" == "500" ]]; then
    echo "  [ERROR] $path → HTTP 500 (potential injection point)"
    cat /tmp/api_probe_$$.tmp | head -5
  elif [[ "$code" != "404" && "$code" != "000" ]]; then
    echo "  [$code] $path"
  fi
done
rm -f /tmp/api_probe_$$.tmp

Phase 2 — OpenAPI/Swagger Exploitation

bash
TARGET="$1"

echo "[*] Extracting API schema..."

# Try multiple Swagger paths
for sw_path in "/swagger.json" "/swagger.yaml" "/openapi.json" "/api/swagger.json" \
  "/api-docs" "/v2/api-docs" "/v3/api-docs"; do
  schema=$(curl -sk --max-time 10 --connect-timeout 10 "$TARGET$sw_path" 2>/dev/null)

  if echo "$schema" | grep -q '"paths"'; then
    echo "[+] Found OpenAPI spec at $sw_path"

    # Extract all endpoints
    echo "$schema" | python3 -c "
import sys, json
spec = json.load(sys.stdin)
paths = spec.get('paths', {})
for path, methods in paths.items():
    for method in methods.keys():
        if method not in ('parameters',):
            print(f'  {method.upper():7s} {path}')
" 2>/dev/null

    # Save for later use
    echo "$schema" > /tmp/openapi_$$.json
    echo "[+] Schema saved to /tmp/openapi_$$.json"
    break
  fi
done

Phase 3 — Authorized Synthetic CRUD Validation

This phase changes server state. Run it only when the scope explicitly permits write testing and the endpoint stores disposable synthetic records. The guard below is deliberate: do not remove it or substitute an existing object ID.

bash
TARGET="$1"
ENDPOINT="$2"  # approved test collection
OUTPUT_DIR="${OUTPUT_DIR:-./output}"
PROBE_ID="noauth-test-$(date +%s)"

if [[ "${I_HAVE_EXPLICIT_WRITE_AUTHORIZATION:-no}" != "yes" ]]; then
  echo "Refusing state-changing validation without explicit authorization." >&2
  exit 1
fi

mkdir -p "$OUTPUT_DIR/api-validation"

create_body=$(curl -sk --max-time 10 --connect-timeout 5 \
  -X POST "$TARGET$ENDPOINT" \
  -H "Content-Type: application/json" \
  -d "{\"name\":\"$PROBE_ID\",\"test_record\":true}")
printf '%s\n' "$create_body" \
  > "$OUTPUT_DIR/api-validation/create-response.json"

created_id=$(printf '%s' "$create_body" | jq -r '.id // .uuid // empty')
if [[ -z "$created_id" ]]; then
  echo "Create response did not expose a disposable object ID; stop here." >&2
  exit 1
fi

curl -sk --max-time 10 --connect-timeout 5 \
  "$TARGET$ENDPOINT/$created_id" \
  -o "$OUTPUT_DIR/api-validation/read-response.json"

curl -sk --max-time 10 --connect-timeout 5 \
  -X PATCH "$TARGET$ENDPOINT/$created_id" \
  -H "Content-Type: application/json" \
  -d '{"validation_state":"updated"}' \
  -o "$OUTPUT_DIR/api-validation/update-response.json"

curl -sk --max-time 10 --connect-timeout 5 \
  -X DELETE "$TARGET$ENDPOINT/$created_id" \
  -o "$OUTPUT_DIR/api-validation/delete-response.txt"

Phase 4 — Bounded Read Validation

bash
TARGET="$1"
ENDPOINT="$2"  # confirmed no-auth endpoint
OUTPUT_DIR="${OUTPUT_DIR:-./output}"

mkdir -p "$OUTPUT_DIR/api-validation"
curl --max-time 15 --connect-timeout 5 -sk \
  "$TARGET$ENDPOINT?page=1&limit=2" \
  -o "$OUTPUT_DIR/api-validation/bounded-sample.json"

jq 'if type == "array" then .[:2] else . end' \
  "$OUTPUT_DIR/api-validation/bounded-sample.json"

Pitfalls

  • HTTP 200 ≠ API. Some services return HTML on unexpected paths. Verify JSON content type.
  • Pagination can turn validation into collection. Request the smallest page that proves the access-control failure. Do not enumerate the dataset.
  • POST, PATCH, PUT, and DELETE change state. Require explicit authorization and operate only on a synthetic object created for the test.
  • Authentication tests can lock accounts or trigger alerts. Use approved test identities and the agreed request rate.

Verification

  • Confirm that the same operation succeeds without authentication and is rejected by the expected negative control.
  • For reads, retain only the minimum sanitized sample needed to demonstrate the protected data class.
  • For writes, record creation, retrieval, update, deletion, and cleanup of the same synthetic object.
  • Document the URL, method, expected policy, observed behavior, identity, timestamp, control result, and testing limit.

Frequently asked questions

What does the Api Noauth Hunt AI skill do?

Use when an API may expose data or privileged operations without authentication.

Why use Api Noauth Hunt on TypingMind?

Because you install it once and use it with any model. Api Noauth Hunt is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Api Noauth Hunt in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/uphiago/recon-skills/tree/main/recon/api-noauth-hunt. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Api Noauth Hunt?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Api Noauth Hunt?

As many as you like. As long as a model supports skills, you can use Api Noauth Hunt with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Api Noauth Hunt AI skill free?

Yes. It is published on GitHub by uphiago under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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