Sahariar Hossain@sahariar_hossain294

DeepAudit AMD is an autonomous enterprise code security and hardware-aware ROCm performance auditor engineered for the AMD Developer Hackathon ACT III. Powered by AMD Token Factory and Google's Gemma-4-31B-IT hosted on AMD Instinct MI300X accelerators, DeepAudit inspects multi-file enterprise codebases with sub-second latency. THE PROBLEMS WE SOLVE: 1. Silent PyTorch GPU VRAM Leaks: Un-detached computational graph loss tensors in training loops cause catastrophic CUDA/ROCm Out-Of-Memory crashes. 2. AI Supply Chain Attacks: Unsafe model checkpoint loading via Python pickle allows critical Remote Code Execution (CWE-502). 3. Sub-Optimal ROCm Utilization: Missing pinned memory and un-fused kernels bottleneck GPU utilization by up to 40%. CORE ARCHITECTURE & SPONSOR INTEGRATION: - AMD Token Factory & Gemma-4-31B-IT: Deep semantic reasoning pinpointing exact line numbers, severity classifications, and unified git diffs. - Hardware-Aware AST Engine: Evaluates PyTorch autograd retention, unauthenticated deserialization, and SQL query sanitization. - ROCm 6.3 Acceleration Advisor: Delivers non-blocking HIP streams (hipStream_t) and torch.compile inductor kernel fusion guidelines. - Measurable Business ROI: Quantifies downtime risk ($8,400 per incident blocked), accelerates 3.5 hours of manual code review down to 4.6 seconds, and unlocks +38% GPU VRAM throughput. - Cryptographic Human-in-the-Loop Sign-Off: Enforces mandatory lead engineer approval with immutable SHA-256 audit signatures before deployment. TRACKS & PRIZES APPLIED: - Track 1: DevTools & Autonomous Agents ($5,000 AMD Prize) - Google Gemma Partner Award ($5,000) - Vibe Generation Award (AirPods 5) for Business ROI & Human Governance. Live GitHub: https://github.com/sahariarhossain524-sketch/DeepAudit-AMD

### 1. Problem Statement Modern software engineering teams face three compounding crises: developer cognitive overload from context-switching between feature work and security reviews, slow and fragmented onboarding that delays a new hire's first PR by weeks, and manual code review bottlenecks where critical OWASP vulnerabilities slip through to production. Human reviews are inconsistent, expensive, and slow—creating multi-day PR queues and accumulated technical debt. ### 2. Solution: AegisDev + IBM Bob 2.0 AegisDev is an autonomous developer workflow engine and zero-trust quality gate built natively using IBM Bob 2.0 Agent Mode. Instead of merely surfacing lint warnings, AegisDev autonomously reasons through codebases, identifies security vulnerabilities against the OWASP ASVS 4.0 standard, writes production-ready refactor patches, and engineers comprehensive Pytest regression guardrails wired to GitHub Actions CI/CD. ### 3. Target Users - Software Engineers & Teams seeking to eliminate cognitive toil and automate code reviews. - Engineering Leaders & Tech Leads accelerating developer onboarding and team velocity. - Application Security (AppSec) Teams enforcing rigorous zero-trust compliance across microservices without slowing down releases. ### 4. How Users Interact with AegisDev - Interactive Autonomous Quality Gate: Developers trigger the live quality gate simulation or test endpoints via the interactive Swagger UI and real-time execution dashboard. - Git Push & PR Automation: Developers push code normally; IBM Bob 2.0 autonomous pipelines trigger on commit, performing AST analysis, security scanning, and test validation. - Self-Healing PRs & SARIF Reports: AegisDev generates GitHub Security-compliant SARIF 2.1.0 artifacts and comprehensive markdown audit reports documenting exact remediation steps. ### 5. What Makes AegisDev Creative & Unique Unlike passive linters or superficial AI chatbots, AegisDev: - Autonomously Remediates Flaws: It doesn't just warn; it autonomously fixed 11 critical and high vulnerabilities (TD-01 to TD-11), including CWE-798 (hardcoded secrets), CWE-328 (PBKDF2-HMAC password hashing with 600k iterations), CWE-269 (privilege escalation defense), and CWE-613 (token revocation). - Self-Healing QA Guardrails: It generated 125 automated tests achieving 92% test coverage with 0 failures, ensuring zero future regressions. - Fail-Closed Zero-Trust Architecture: Enforces strict environment boundaries, thread-safe data stores, and sanitized error disclosures with correlation IDs. ### 6. Measurable Impact & Resource Efficiency - 11 / 11 Security Findings Remediated: 100% autonomous resolution verified via SARIF 2.1.0. - 125 / 125 Regression Tests Passing: 100% pass rate enforced by a 4-stage GitHub Actions CI/CD pipeline. - Ultra-Efficient Execution: Completed all 3 full hackathon tasks consuming only 10.96 Bobcoins out of the 40 allocated budget (72.6% efficiency savings). - Production-Ready & Live: Deployed live on Vercel Serverless with sub-second cold starts.

In today's cloud and edge infrastructure, the biggest operational bottlenecks are alert fatigue and sudden downtime caused by schema drift. When a production data pipeline fails at midnight, diagnosing and resolving the issue manually takes hours of critical downtime. On the other hand, letting unconstrained AI models generate direct fixes often introduces hallucinations or destructive code that breaks the system even further. That is why we built AegisMind.OS—an autonomous, zero-hallucination, self-healing infrastructure sentinel built on four robust technological pillars: 1. **Multi-Agent Adversarial Consensus:** The telemetry agent detects anomalies, the diagnostic agent proposes root-cause fixes, and the adversary agent rigorously stress-tests every patch to ensure zero security violations. Execution only occurs after passing the risk guardian. 2. **Sub-millisecond Edge Vision (Intel OpenVINO):** Utilizing Intel INT8 quantized inference, we achieve edge inspection at 0.28 ms latency with a throughput of 3,571 FPS to catch physical and hardware defects in real-time. 3. **Sandboxed Self-Healing Engine:** Validated code patches compile inside an isolated AST bytecode sandbox in just 12.4 ms, dynamically resolving runtime crashes while blocking unauthorized execution. 4. **Speechmatics Real-Time Voice Supervision:** Integrated with real-time voice streaming with a 0.8-second settling filter to eliminate accidental false triggers, allowing human operators to issue emergency voice overrides and safely manage lower-priority tasks. AegisMind.OS ensures cloud and edge environments stay resilient, secure, and operational 24/7.

# Project Overview AlphaQuant AI is an autonomous quantitative options trading copilot built on Alpaca infrastructure for the Alpaca AI Trading Agents Hackathon 2026. It strictly incorporates mandatory US equity options trading (Calls & Puts on NVDA, AAPL, TSLA) powered by the Alpaca Model Context Protocol (MCP) Server. ## Multi-Agent Consensus Swarm AlphaQuant AI deploys 4 specialized AI personas: 1. Technical Analyst: Calculates Wilder RSI(14), EMA(20), and MACD to establish directional Call/Put bias. 2. Macro Sentiment: Evaluates macro trends and Implied Volatility (IV) to prevent entering high IV crush. 3. Risk Guardian: Holds veto power to enforce defined-risk boundaries and strict capital limits. 4. Market Structure: Inspects options liquidity, spreads, and open interest to eliminate slippage. Consensus is aggregated via deterministic mathematical voting (Majority 3/4 or Unanimous 4/4) with zero look-ahead bias. ## Autonomous Options Strategy & Greeks - Bullish Setups (BUY_CALL): Selects ATM/OTM Calls (Delta ≈ 0.50) for leveraged defined upside. - Bearish Setups (BUY_PUT): Selects OTM Puts (Delta ≈ -0.45) for downside hedging. - Theta Protection: Contracts with < 7 days to expiration are rejected to eliminate high time decay. ## Institutional Risk Gates 1. Defined Risk Principle: Maximum loss is strictly capped at 100% of premium paid. 2. Strict "No Naked Selling": Only long calls and puts are permitted. No uncovered short risk. 3. 5% Capital Ceiling: Max $5,000 allocation per position on the $100,000 paper capital. 4. Liquidity Gate: Rejects spreads > 15% or open interest < 200 contracts. ## Alpaca Infrastructure - Alpaca MCP Server (v2.1.0): Full JSON-RPC 2.0 tool execution (alpaca_place_option_order, alpaca_get_options_chain). - Alpaca Paper Trading: Account ID PA3QMVG68GA0 ($100k Equity). - Verification: 56/56 passing tests, Next.js 16, and deployed live on Vercel.

# AegisVoice OS: Sub-Second Voice Fraud Guardian ### 🛡️ The Global Problem Telephony social engineering and voice cloning drain over **$48.8B annually**. Traditional carrier flags fail because they are **passive and post-facto**—once a victim verbally shares an OTP under psychological duress, financial loss is immediate and irreversible. ### ⚡ The Solution: AegisVoice OS AegisVoice OS is an inline, sub-second autonomous voice defense agent that intercepts live telephony streams. Operating at carrier SIP gateways or consumer endpoints, it analyzes conversational speech in flight, detecting credential harvesting, duress, and spoofed authority. When threat intent is identified, AegisVoice executes deterministic defensive agentic tools within **426ms** before fraud occurs. ### 🎙️ Powered by AssemblyAI - **Universal-3 Pro Streaming STT**: Telephony audio is streamed via low-latency WebSockets (16kHz PCM). AssemblyAI delivers real-time streaming transcripts and entity recognition with sub-second turnaround. - **Autonomous Agentic Tools**: 1. `mask_sensitive_token`: Synthesizes inline acoustic blanking over the microphone channel, rendering spoken OTPs inaudible to scammers. 2. `quarantine_call`: Injects an instant guardian IVR warning the victim and safely terminates the adversary line. 3. `escalate_financial_fraud`: Dispatches an encrypted forensic incident dossier directly to bank anti-fraud units. ### 📊 Benchmark Evidence & Explainable Forensics - **426.82ms Defense Loop**: Verified across 50 automated benchmark trials. - **Explainable Threat Scoring (EWTS)**: Mathematical evidence model: $S_{\text{threat}} = 1.0 - \exp(-\sum w_i \tau)$, delivering calibrated threat scores (e.g., 99.2/100) tied directly to conversational forensic markers. ### 💼 Business Model & ROI - **Telecom Carrier SIP**: $0.0018 / min licensing. - **Enterprise Banks**: $15 / seat / mo (34:1 fraud prevention ROI). - **Consumer Guard**: $4.99 / family / mo.

# Project Overview NeuralRoute AMD is an enterprise-grade intelligent model routing gateway and token optimizer engineered to eliminate commercial LLM cost barriers using AMD's open ROCm ecosystem and Instinct™ GPU hardware. Commercial enterprise AI adoption faces severe API cost inefficiencies: over 80% of routine developer queries sent to expensive frontier cloud models ($5.00/1M tokens) can be handled with identical fidelity by optimized open-source models ($0.15/1M tokens) on local AMD hardware clusters. NeuralRoute AMD dynamically classifies semantic query complexity in real-time, executing cost-effective local inference on AMD ROCm while routing only high-complexity reasoning tasks to frontier clouds. # Key Features & Innovation - **Real-Time Semantic Classifier:** Token-aware, multi-dimensional complexity analyzer evaluating mathematical depth, code syntax, and context to score prompts deterministically. - **Dynamic Policy Dispatcher:** Configurable policies (Cost-Optimized, Ultra-Fast, Accuracy-First) matching enterprise SLOs. - **ROCm Hardware Telemetry:** Integrated Prometheus profiler tracking AMD Instinct™ MI300X VRAM allocation, 5.3 TB/s HBM3 bandwidth, and throughput. - **Enterprise Cost & Savings Dashboard:** Real-time financial analytics tracking token spend and quantifying net savings. - **Resilient Circuit Breaker:** Graceful failover logic with AbortController ensuring 99.99% gateway availability. # AMD Technology Stack & Economics - **Compute Architecture:** AMD Instinct™ MI300X (192 GB HBM3, 304 CUs), AMD ROCm™ 6.2.1, PyTorch ROCm HIP, vLLM ROCm PagedAttention. - **Cost Reduction:** Slashes token expenses from $5.00/1M to $0.15/1M (78.2% average net enterprise savings). - **Inference Latency & Speed:** Sub-25ms local execution with over 150 tokens/sec sustained throughput on AMD CDNA 3.

Six Matches. One leaderboard. Build on AMD, earn points and compete for prizes.

🌎 Hybrid Hackathon | 💻 Online Build: 3–8 November 2026 | On-site Phase: 8 November 2026 📍 On-site Venue: Pierpont Place 163 W Pierpont Ave, Salt Lake City, UT 84101, USA ✨ Please note that travel and accommodation are not covered.

🌎 Hybrid Hackathon | 💻 Online Build: October 16–19, 2026 | 📍 On-site: October 19–20, 2026 The official hackathon of AI & Big Data Expo Europe, organized by TechEx Events and lablab.ai. Build AI applications and agents across AI, cybersecurity, cloud, IoT, automation, edge computing, digital transformation, and data infrastructure, then showcase your project live at one of Europe's largest enterprise technology events. 📍 On-site Venue (October 19–20): RAI Amsterdam Europaplein 24, 1078 GZ Amsterdam, Netherlands 📍 If approved for the on-site experience, you'll also have the opportunity to showcase your project live. Travel and accommodation will not be covered.

🌎 Hybrid Hackathon | 💻 Online Build: 12-17 October 2026 | On-site phase: 17-18 October 2026 To participate in the hackathon, simply click Sign up with AMD. If you are not already a member of the AMD AI Developer Program (ADP), you will need to create an account. The AMD Developer Hackathon: ACT III is a hands-on event for developers, founders, engineers and builders who want to push what’s possible with AI on real infrastructure. 📍 If approved for the on-site experience, you'll also have the opportunity to showcase your project live. Travel and accommodation will not be covered.

🌎 Online Hackathon | 💻 Online Build: Sept 26 - Oct 5, 2026 A virtual, global hackathon. Build from anywhere in the world. Dark Factory is the official hackathon of WeAreDevelopers World Congress North America, presented by BAND, but you don't need to be in San Jose to take part. For one week, you build a software factory in BAND Desktop: a band of coding agents that plans work, implements it and checks its own results. 🎟️ Bonus for sign-ups: you are eligible for a free ticket to WeAreDevelopers World Congress North America in San Jose (Sep 23–25). If you do go, stop by the BAND booth: a surprise is waiting for you.