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mitmproxy-based IDOR detection tool - intercepts traffic and analyzes parameter relationships to find insecure direct object references

Project description

IDOR-otaku (idotaku)

CI Coverage PyPI version Python License: MIT Code style: ruff

IDOR-otaku — A reconnaissance tool that tracks how IDs flow through your API traffic to uncover IDOR attack surfaces. No Burp Suite required.

Unlike fully automated verification tools (Autorize, AuthMatrix), idotaku maps where IDs originate, how they propagate across requests, and which ones appear without a traceable origin — revealing the attack surface before you start testing. The verify command lets you selectively test IDOR candidates with explicit confirmation at every step.

Why idotaku?

  • ID lifecycle visibility — Tracks where IDs are born (responses) and where they travel (requests). Visualizes parameter chains and API sequence diagrams as interactive HTML.
  • No Burp Suite requiredpip install idotaku and go. Works as a standalone CLI tool with mitmproxy.
  • HAR import — Analyze traffic captured from Chrome DevTools, Burp Suite, or any other tool. No proxy setup needed for offline analysis.
  • CI/CD ready — SARIF export integrates directly with GitHub Code Scanning. CSV export for custom pipelines.
  • Built-in verificationverify command sends modified requests with user confirmation at every step. Supports proxy passthrough (Burp/ZAP).

IDOR (Insecure Direct Object Reference) is a vulnerability where an application exposes internal object IDs (user IDs, order numbers, etc.) without proper authorization checks, allowing attackers to access other users' data by manipulating these IDs.

How It Works

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Browser   │────>│  mitmproxy  │────>│  API Server  │
└─────────────┘     └──────┬──────┘     └─────────────┘
                           │
                           v
                    ┌─────────────┐
                    │  idotaku    │
                    │  (tracker)  │
                    └──────┬──────┘
                           │
                           v
                    ┌─────────────┐
                    │   Report    │
                    │   (JSON)    │
                    └─────────────┘
  1. Intercept — Proxies browser traffic via mitmproxy
  2. Track — Records full HTTP data: where IDs first appear (response) and where they are used (request), including headers, body, and status codes
  3. Detect — Flags IDs used in requests that never appeared in any response (IDOR candidates)
  4. Visualize — Renders parameter chains and API sequence diagrams as interactive HTML
  5. Verify — Interactively test IDOR candidates by sending modified requests with user confirmation

Requirements

  • Python 3.12+
  • mitmproxy 11.0+

Installation

pip install idotaku

Quick Start

# Interactive mode (recommended for beginners)
idotaku -i

# Start proxy directly
idotaku

# Analyze report
idotaku report id_tracker_report.json
idotaku chain id_tracker_report.json --html chain.html
idotaku sequence id_tracker_report.json --html sequence.html

# Import HAR file (from Chrome DevTools, Burp Suite, etc.)
idotaku import-har capture.har -o report.json

Demo

Try idotaku with a built-in vulnerable API that demonstrates all detection capabilities:

cd examples/vulnerable_api

# One-command demo (Linux/macOS)
bash run_demo.sh

# Cross-platform (Windows/macOS/Linux)
python run_demo.py

The demo starts a vulnerable FastAPI server, proxies traffic through idotaku, runs an automated attack scenario, and generates analysis reports.

What You'll See

Risk Scoring — Four severity levels from a single test scenario:

Score  Level     ID Value              Type     Factors
─────  ────────  ────────────────────  ───────  ──────────────────────────
89     CRITICAL  1003                  numeric  DELETE, url_path, numeric
65     HIGH      1002                  numeric  PUT, url_path, numeric
46     MEDIUM    b2c3d4e5-f6a7-...     uuid     POST, body, uuid
18     LOW       doc_YzAbCdEfGh...     token    GET, header, token

Risk Scores

Parameter Chains and Sequence Diagrams are exported as interactive HTML:

# Generated by the demo script:
# examples/vulnerable_api/chain.html     — card-based parameter chain tree
# examples/vulnerable_api/sequence.html  — UML-style API sequence diagram

Chain HTML Sequence Diagram

See examples/vulnerable_api/ for details, or the Quick Start Guide for a step-by-step walkthrough.

Commands

Analysis

Command Description
report View IDOR detection report summary
chain Detect parameter chains with --html export and --domains filter
sequence API sequence diagram with --html export and ID highlighting
lifeline Show parameter lifespan analysis
score Risk-score IDOR candidates (critical / high / medium / low)
verify Interactive IDOR verification — send modified requests with user confirmation
auth Detect cross-user access patterns via auth context
diff Compare two reports and show changes
interactive Launch interactive mode with guided menus

Configuration

Command Description
config init Create default idotaku.yaml in the current directory
config show Show effective configuration (defaults + config file)
config get <key> Get a single config value (supports dotted keys: patterns.uuid)
config set <key> <value> Set a config value in the YAML file
config validate Validate config file syntax, types, and regex patterns
config path Print the path to the active config file

Interactive mode (-i) also provides a guided setup wizard for editing settings.

Import & Export

Command Description
import-har Import HAR file and generate idotaku report
csv Export IDOR candidates or flows to CSV
sarif Export findings to SARIF 2.1.0 (GitHub Code Scanning)

Programmatic API

from idotaku.report import load_report, score_all_findings, diff_reports
from idotaku.export import export_csv, export_sarif
from idotaku.import_har import import_har
from idotaku.verify import VerifyHttpClient, compare_responses, suggest_modifications

# Load and score
data = load_report("report.json")
scored = score_all_findings(data.potential_idor)

# Export
export_csv("idor.csv", data, mode="idor")
export_sarif("findings.sarif.json", data)

# Import HAR
report = import_har("capture.har")

# Diff two reports
diff = diff_reports(load_report("old.json"), load_report("new.json"))

# Verification helpers
suggestions = suggest_modifications("12345", "numeric")

Use Cases

Bug Bounty Reconnaissance

Capture traffic while browsing a target, then analyze the report to find IDs that appear in requests without a traceable origin. These are your first IDOR candidates to investigate.

Penetration Test Preparation

Before diving into manual testing, run idotaku to map the full ID landscape. The parameter chain analysis shows which API sequences share IDs — helping you prioritize where to test access controls.

CI/CD Security Gate

Import HAR files from automated browser tests, generate a report, and export to SARIF. Integrate with GitHub Code Scanning to flag new IDOR candidates on every pull request.

Post-Capture Offline Analysis

Already have traffic from Burp, Chrome DevTools, or another proxy? Import the HAR file and analyze it without setting up mitmproxy.

Documentation

Contributing

# Clone and install with dev dependencies
git clone https://github.com/RalianENG/IDOR-otaku.git
cd idotaku
pip install -e ".[dev]"

# Run tests
pytest

# Run tests with coverage
pytest --cov=idotaku

# Lint
ruff check src/

Bug reports and pull requests are welcome on GitHub Issues.

Disclaimer

This tool is intended for authorized security testing and educational purposes only. You must obtain proper authorization before testing any systems you do not own. The authors are not responsible for any misuse or damage caused by this tool. Use at your own risk and in compliance with all applicable laws.

License

MIT

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