Cryptocurrency hacks list
Cryptocurrency risk scoring services list
Agent observability and guardrails for OpenClaw — risk scoring, audit trails, dashboard.
国内公募基金数据采集与AI辅助分析工具 — 全栈FastAPI+React，集成AKShare多源数据、风险评分引擎、回测验证、LLM可选分析
Phoneint-OSINT-Toolkit — a privacy-first phone-number OSINT toolkit (CLI + minimal GUI). Parses and normalizes numbers (E.164), enriches with deterministic metadata, runs optional async adapters (DuckDuckGo, Google, public datasets), computes explainable risk scores and owner intelligence, and exports JSON/CSV/PDF reports.
Edge AI and V2X proof-of-concept for predictive risk mitigation in heavy commercial vehicles using camera, GPS, telemetry, and real-time risk scoring.
A complete Web3 security toolkit combining AI-powered token auditing, ML-based deployer reputation scoring, and live Etherscan V2 data. Includes static analysis for rugpull detection, RandomForest reputation modeling, contract-fetching automation, and Solidity on-chain registries for transparent, reproducible security insights.
A deep technical article exploring how AI, feature engineering, and static smart-contract analysis uncover rugpull risks before humans detect them. Covers Solidity pattern mining, mint abuse detection, blacklist/fee manipulation signals, ML-inspired scoring models, and how to quantify ERC-20 token scam probability.
AI-powered real-time smart contract scanner that connects Machine Learning with Etherscan V2 to analyze newly deployed contracts instantly. Fetches verified Solidity code, performs static risk analysis, computes ML-driven deployer trust scores, and generates full security intelligence pipelines for Web3 threat detection.
A hybrid Solidity + Python security toolkit that analyzes ERC-20 token contracts using static pattern extraction and ML-inspired scoring. Detects mint backdoors, blacklist controls, fee manipulation, trading locks, and rugpull mechanics. Outputs interpretable risk scores, labels, and structured features for deeper analysis.
A deep exploration of how human psychology shapes fraud behavior and how those patterns become measurable signals in transaction data. This article reveals the behavioral, cognitive, and economic forces behind fraud, explaining how ML models detect deviations, anomalies, and intent hidden within financial transactions.
A deep technical exploration of how malicious smart-contract developers weaponize fee logic in ERC-20 tokens. Covers dynamic tax flipping, hidden sell traps, fee obfuscation, whitelist-based bypasses, liquidity-drain funnels, attack timelines, forensic analysis, mathematical modeling, and ML-powered detection strategies for tax abuse.
A customer intelligence engine that predicts subscription probability, models purchase frequency, and computes a unified loyalty risk score. Includes explainability, segment insights, and a scenario simulator, all integrated into an interactive Streamlit dashboard.
A research-grade framework for extracting, classifying, and analyzing the “genetic” behavior of smart contract tokens. Identifies economic traits, supply mutations, fee patterns, permission risks, upgradeability vectors, and scam species using a structured gene taxonomy with risk scoring, HTML reports, and token comparison tools.
IP threat detection with automatic blacklisting
AI-powered KYC automation platform with adaptive risk scoring, multi-layer biometrics, OCR, deepfake detection, and cryptographic credentialing. Reduces verification time from 48–72 hours to 8–12 minutes while improving fraud detection to 98.5%.
Rust CLI for auditing Solana wallets, token authorities, delegate approvals, upgradeable program exposure, and known risky address interactions.
AAPP‑MART is an open-source cybersecurity engine for offensive security, AI-powered attack path prediction, autonomous red team simulation, automated threat modeling, adversary emulation, attack graph analysis, exposure management, vulnerability assessment, cyber risk assessment, risk scoring, and MITRE ATT&CK-aligned security validation.
Prioritize vulnerabilities by real risk, not just CVSS
Discover and audit MCP servers for security vulnerabilities across Claude Code, Cursor, VS Code, and more
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