Product Introduction

1. Almanax is an AI-powered security engineering platform designed to enhance code security throughout the software development lifecycle. It integrates directly into CI/CD pipelines to continuously scan source code and dependencies for vulnerabilities, triage alerts from third-party security tools, and deploy automated fixes before code reaches production. The platform specializes in reducing security risks in Web3, blockchain, and decentralized application (dApp) environments by addressing both code-level flaws and supply-chain threats.
2. The core value of Almanax lies in its ability to act as an autonomous security engineer, streamlining vulnerability detection and remediation without requiring manual intervention. By combining LLM-based analysis with traditional scanning methods, it significantly reduces false positives, accelerates remediation timelines, and enables development teams to maintain velocity while adhering to security best practices. This approach directly addresses the inefficiencies of legacy security tools and the growing complexity of modern codebases.

Main Features

1. LLM-based Detection: Almanax employs large language models (LLMs) trained on security-specific datasets to identify complex vulnerabilities that traditional static analysis tools miss, such as logic flaws, race conditions, and context-specific risks in smart contracts. The system analyzes code semantics and execution paths rather than relying solely on pattern matching, enabling it to detect issues like improper access controls or arithmetic overflows in Web3 applications.
2. Dependency Scanning: The platform performs automated supply-chain risk assessments through one-click scans of dependency trees, identifying vulnerable third-party components and license compliance issues. It cross-references packages against real-time threat intelligence feeds and maintains a historical database of compromised modules, providing severity scores and remediation paths for detected risks.
3. Alerts Filtering: Almanax integrates with existing security tools like Snyk and Socket to ingest alerts, then applies machine learning classifiers to eliminate false positives. The system contextualizes warnings against project-specific code patterns, deployment environments, and historical vulnerability data, reducing alert noise by up to 95% while maintaining 99% precision in critical vulnerability identification.

Problems Solved

1. High False Positive Rates: Traditional security scanners generate excessive false alerts (95% industry average), causing alert fatigue and wasted engineering resources. Almanax solves this through contextual analysis and LLM-powered validation, ensuring teams focus only on actionable security risks.
2. Scalability Challenges: Security teams struggle to audit the increasing volume of code produced by AI-assisted development tools like Cursor, which enable engineers to generate 100x more code. Almanax automates triage and remediation at scale, functioning as a force multiplier for understaffed security operations.
3. Web3 Security Gaps: Manual audits fail to catch 91% of smart contract vulnerabilities according to 2022 data, while decentralized systems require specialized security approaches. The platform provides continuous, AI-driven audits tailored to blockchain architectures, detecting risks like reentrancy attacks or oracle manipulation that conventional tools overlook.

Unique Advantages

1. Automated Fix Generation: Unlike passive scanners, Almanax ships code patches for identified vulnerabilities through pull requests or direct CI/CD integration. The system generates context-aware fixes that preserve original functionality while addressing security flaws, reducing mean time to repair (MTTR) from days to minutes.
2. Adaptive Learning Architecture: The platform continuously improves its detection capabilities through feedback loops from resolved alerts and user validation. Security findings from one organization's codebase enhance detection accuracy across all customers without compromising data privacy.
3. Web3 Specialization: While generic tools focus on traditional application security, Almanax incorporates domain-specific knowledge for smart contracts, tokenomics, and decentralized governance models. It detects 23% more blockchain-specific vulnerabilities than competitors through custom detection rules for Solidity, Vyper, and Rust-based blockchain runtimes.

Frequently Asked Questions (FAQ)

1. How does Almanax reduce false positives compared to traditional scanners?
   Almanax combines LLM-based semantic analysis with project-specific context to validate alerts, achieving a 95% reduction in false positives. The system cross-references potential vulnerabilities against code execution paths, dependency relationships, and historical project data to eliminate irrelevant warnings while maintaining high recall rates for critical issues.

2. Can Almanax integrate with our existing CI/CD pipeline and security tools?
   Yes, the platform provides pre-built integrations for GitHub Actions, GitLab CI, Jenkins, and major cloud providers. It supports bidirectional communication with Snyk, Socket, and other scanners through standardized APIs, allowing centralized alert management without disrupting existing workflows.

3. What programming languages and blockchain platforms does Almanax support?
   Almanax currently supports Solidity, Vyper, Rust, Python, JavaScript, and TypeScript, with specialized detection rules for Ethereum, Solana, and Cosmos-based chains. The system is framework-agnostic, providing analysis for smart contracts, backend services, and infrastructure-as-code configurations across Web2 and Web3 environments.