Build my first saas tool .

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github

Tom Wartenberg  • Peerlist

AegisPlay is a snippet-first code audit and security testing playground for developers.It helps you paste a small piece of code, choose between Code Audit and Security Test, and receive readable What / Where / Why / Fix-style findings instead of cryptic scanner output.I built AegisPlay because many code review and security tools feel too heavy for quick snippet checks, while plain AI chats can be too vague or too confident. AegisPlay tries to sit between those worlds: fast enough for everyday developer use, structured enough to be useful, and honest about its limits.The product has two separate workflows:Code Audit focuses on maintainability, readability, correctness, structure, production-readiness, and general code quality.Security Test focuses on exploitability-related issues such as injection risks, unsafe execution, secrets, debug exposure, dangerous runtime patterns, and security-sensitive behavior.AegisPlay combines deterministic checks, context classification, sandbox-aware runtime handling, and AI-assisted explanations. Python receives the deepest runtime-aware analysis, while JavaScript, CSS, HTML, and configuration snippets are handled through static review with clear limitations.It is not meant to replace enterprise SAST platforms, full repository scanning, professional AppSec review, or manual audits. It is designed as a fast first-pass tool for developers, indie hackers, freelancers, and small teams who want to understand risky or messy code faster.Free scans are available after registration.Live product: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://aegisplay.net">https://aegisplay.net</a> Public feedback hub: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/TomWartenberg-IRN/aegisplay">https://github.com/TomWartenberg-IRN/aegisplay</a>

AegisPlay

This project outlines a high-impact offensive security blueprint developed for structured injection and access control bypasses within federated systems. It includes symbolic abstraction layers, multi-phase escalation logic, and contextual payload chaining tailored for real-world cloud environments. The framework has been officially accepted by Crowdfense and reached Director-Level classification within 3 days. While the asset remains exclusive and is currently awaiting buyer allocation, the technical evaluation confirms its operational relevance and strategic exploit value. Core focus: Symbol-based privilege bypass mechanisms Federated access routing structures Proof-of-Concept methodology aligned with legal disclosure frameworks Internal architecture layering for real-time escalation modeling Fully documented under a controlled and ethical submission protocol

Cloud-Integrated Vulnerability Framework | Of

EchoPulse-KEM is a next-generation key encapsulation system built to resist post-quantum threats through symbolic encoding and multi-layered memory-safe design. The protocol leverages a Rust-based cryptographic core (KeyGen, Encaps, Decaps), combined with symbolic entropy injection, deterministic flow routing, and customizable slot architecture. It is tailored for deployment in high-resilience systems, supporting integration into secure communication frameworks, firmware-level agents, or AI defense tooling. Project components include: Modular Rust implementation (B1–B5) Benchmark & Resource Profile (C-Series) Symbolic Metadata Management (D-Series) Entropy Pathing & Replay Resistance Prepared for CTD regulatory alignment (EMA/FDA-ready blueprint) EchoPulse was developed as part of a larger symbolic defense initiative and is fully documented in a standalone technical dossier.

EchoPulse-KEM: Post-Quantum Symbolic Key Enca

Submitted a symbolic prompt injection scenario to Grammarly via HackerOne. The report demonstrated context-level behavior modification through structured role drift and language modulation. Despite being reproducible and potentially privacy-relevant, the case was closed as "informative" without follow-up. This example highlights the current blind spot in major AI security programs: symbolic exploits and emergent behavior are not yet taken seriously. Attached image shows the final response. Case filed under symbolic exploit research.

Grammarly LLM Exploit Submission – Rejected D

This work documents the extended version of the IRN theory (Information-Based Reality & Structural Resonance) – an independent scientific model that describes reality as a structured matrix of information.The theory is based on a non-binary resonance model that explains physical, communicative, and systemic processes through path structures. It combines mathematical formulas, symbolic encoding, simulation tests, and application-oriented scenarios.In Version 2, in addition to the core modules (IRN X1–X17), two new components were added:– IRN_X19: Post-Structural Existence– IRN_X20: Communication Resonance ModelFurthermore, this release includes a draft of potential patents for technical and information-theoretical implementations based on the IRN approach.Target group: Researchers, institutes, developers, and anyone interested in AI and technology.Created by: Tom Wartenberg (Initiator, Developer, Researcher)Publication: 2025-04-05License: (please select at Zenodo – e.g., CC-BY-NC 4.0)

IRN-Theorie

Independently developed encryption architecture submitted to the NATO Innovation Hub. Combines symbolic systems theory, entropy-based mutation cycles, and LLM-resistant encryption logic. Fully documented through 10 iterations (v1–v10) including executive brief, cover letter, and a strategic deployment roadmap. Relevant to: tactical communications, AI defense, UAV systems, embedded secure hardware (TrustZone, FPGA, etc.)

PolySignX – Symbolic AI-Resistant Encryption 

Shield Enterprise is a modular security framework designed for AI systems and large language models (LLMs). It combines threat filtering, risk scoring, policy enforcement, and GDPR-compliant audit logging to enable secure enterprise-grade LLM deployments. Key features include: – Dynamic rule-based moderation – Enterprise-ready SIEM integration (Splunk, Sentinel, Elastic) – ISO/FINRA/HIPAA/GDPR logging extensions – Risk-based output scoring and response control The public version (v1.0) is available on GitHub. 🔗 pitchhut.com/project/shield-enterprise-security-framework 🔗 github.com/TomWartenberg-IRN/Shield-Enterprise

Shield Enterprise – Modular AI Threat Governa

Submitted a symbolic adversarial defense methodology focusing on language-model exploitation patterns, multi-layer input drift, and context destabilization. Currently under technical review by the lead of the MITRE ATT&CK framework. The submission aims to extend ATT&CK with a novel symbolic category for emergent prompt-based threat vectors.