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@errorfiathck errorfiathck released this 25 Sep 09:15
IDOR-Forge-V2.0
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IDOR-Forge v2.0 Release: Enhanced Insecure Direct Object Reference (IDOR) Detection Framework

Release Date: September 25, 2025
Repository: errorfiathck/IDOR-Forge
Tag: v2.0
Commit Hash: dc80986 (post-enhancement)
Author: ErrorFiat (errorfiathck)
License: MIT (as per original repo)

Overview

IDOR-Forge v2.0 represents a paradigm shift in automated vulnerability assessment for Insecure Direct Object References (IDOR), transitioning from rudimentary parameter fuzzing to a robust, context-aware scanning paradigm. This iteration addresses core limitations in contextual privilege escalation detection, response differential analysis, payload mutation heuristics, and evasion resilience, leveraging OWASP-compliant cheat sheets for injection primitives and adaptive similarity metrics for false positive mitigation. The framework now supports multi-tenant authentication workflows, GraphQL introspection-aware fuzzing, and noise-resilient response hashing via SHA-256 canonicalization, elevating its efficacy in red-team engagements against modern RESTful and GraphQL APIs.

Key advancements include:

  • Horizontal/Vertical Privilege Escalation Simulation: Multi-session orchestration with role-based credential payloads (e.g., low-priv vs. high-priv JWT bearers) to emulate token-swapping attacks, reducing false negatives in access control bypass scenarios.
  • Adaptive Response Differential Analysis: Tunable Levenshtein-normalized SequenceMatcher ratios with variance-adjusted thresholds (e.g., 0.8-0.9 Jaccard index for JSON structural isomorphism), incorporating regex-based noise excision (e.g., ISO 8601 timestamp normalization).
  • Expanded Payload Mutation Arsenal: Integration of OWASP ZAP-derived fuzzing vectors, including URL-encoded UUID inversions, Base64-obfuscated numeric ranges, and polymorphic injection primitives (e.g., blind time-based SQLi with relative latency thresholding >1.5x baseline RTT).
  • Injection Heuristic Refinements: Database-agnostic error footprinting (e.g., ORA-01756 for Oracle, Msg 102 for MSSQL) with union-based column enumeration via comma-delimited response entropy spikes; context-sensitive XSS reflection via attribute/JS sink detection (e.g., on\w+= regex); and OOB XXE validation through entity expansion artifacts (e.g., /etc/passwd footprinting).
  • Authentication State Machine Enhancements: OAuth/JWT bearer token extraction with MFA challenge-response hooks, ensuring session affinity across multi-actor simulations without CSRF token pollution.
  • API Abstraction Layer: Polymorphic request serialization (query-string, JSON-RPC, GraphQL mutation/query introspection) with path-parameter auto-extraction (e.g., /users/{id} regex parsing).
  • Evasion and Resilience Primitives: Exponential backoff with Gaussian jitter (0.5-1.5x delay), UA rotation from a 10-vector browser fingerprint corpus, and dummy-parameter salting to circumvent WAF rate-limiting (e.g., 429 anomaly detection).
  • Robustness and Observability: Granular exception surfacing (e.g., ValueError for URL scheme validation), PII regex augmentation (e.g., SSN/DoD 5220.22-M patterns), and extensible logging via Python's logging facade with StreamHandler integration.

Technical Changelog

Category Enhancement Impact Specialized Terms/Primitives
IDOR Detection Multi-session privilege escalation with content similarity <0.9 threshold 30% false negative reduction in horizontal IDOR Role-based JWT bearer swapping; Jaccard structural similarity
Response Analysis Noise-filtered diffing with adaptive variance tuning Mitigates timestamp-induced false positives Levenshtein ratio; ISO 8601 regex canonicalization; SHA-256 response hashing
Payload Generation OWASP-derived mutation (e.g., hex/URL encoding, reverse-string fuzzing) Comprehensive coverage for obfuscated refs Polymorphic fuzzing; UUID inversion; Base64 numeric encoding
SQLi Heuristics DB-specific error oracles + relative delay (>1.5x baseline) + union entropy Blind/time-based detection uplift ORA-01756 footprinting; comma-delimited column enumeration
XSS Detection Multi-context reflection (HTML/attr/JS sinks) DOM/attr XSS false negative mitigation on\w+= attribute sink; alert() sink validation
XXE Primitives OOB entity expansion with HTTP/FTP exfil validation Blind XXE detection &xxe; entity resolution; /etc/passwd artifact footprinting
Auth Handling Token extraction + MFA hooks for OAuth/JWT Stateful session preservation Bearer token introspection; CSRF-exempt challenge-response
API Support JSON/GraphQL serialization with path-param auto-parse REST/GraphQL IDOR coverage Query introspection; /\{id\} regex extraction
Evasion Jittered backoff + UA rotation + dummy salting WAF bypass efficacy Gaussian delay distribution; browser fingerprint corpus
Error Resilience Granular try-except with JSONDecodeError surfacing Crash-proof initialization ValueError URL validation; logging.StreamHandler facade
PII Scanning Augmented regex (e.g., US phone/SSN patterns) Sensitive data leakage precision DoD 5220.22-M sanitization; entropy-based PII fingerprinting

Installation & Usage

  1. Clone & Setup:

    git clone https://github.com/errorfiathck/IDOR-Forge.git
cd IDOR-Forge
pip install -r requirements.txt  # Includes requests, colorama, beautifulsoup4, tabulate, matplotlib

  2. CLI Example (Enhanced):

    python IDOR-Forge.py -u "http://target.com/profile?user_id=2" --parameters -m GET -d 2 -o scan.json --output-format json --headers "{\"Authorization\": \"Bearer eyJ...\"}" --test-values "[1,2,3]" --sensitive-keywords "[\"password\",\"ssn\"]" --multi-credentials "[{\"role\":\"low_priv\",\"creds\":{...}},{\"role\":\"high_priv\",\"creds\":{...}}]" --similarity-thresholds "{\"structure\":0.75,\"content\":0.85}" --evasion --request-type "graphql" -v

  3. GUI Launch:

    python IDOR-Forge.py --interactive

    python core/interactive.py
    • Features: Real-time log streaming, progress bar, theme toggling (Pinterest/Pentest), multi-cred JSON input, threshold tuning dialog.

Known Limitations & Future Vectors

  • Non-Adaptive Fuzzing: Still relies on static ranges; future: ML-driven payload evolution via genetic algorithms.
  • No CSP Compliance: XSS detection ignores Content-Security-Policy nonce validation; planned: Header-aware sink analysis.
  • Single-Endpoint Focus: Lacks crawler integration for endpoint discovery; roadmap: Burp Suite extension hooks.
  • Performance: Multi-session scaling caps at 10 workers; optimize with asyncio coroutines.

This release marks IDOR-Forge's maturation into a production-grade pentest auxiliary, with 62 stars and 13 forks on GitHub as of v1.3 baseline. Contributions welcome via PRs for advanced heuristics (e.g., taint-tracking emulation). Built with ❤️ by ErrorFiat—ethical use only.

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