Intelligent Code Security Review
Deep semantic and data-flow auditing directly within your modern developer workflows.
Tracks true data flows and cross-file call hierarchies to deliver validated fixes directly into Pull Requests.
Traditional Static Application Security Testing (SAST) tools drown software engineering teams in false alarms because they rely on simple regex checks and lack architectural awareness.
Supradim Intelligent Code Review combines graph-based taint analysis with context-aware LLMs to trace complete data flows across files and services, identifying genuine vulnerabilities and generating developer-ready pull request diffs.
HIGH · CWE-639
Validate tenant boundary before querying record.
− Order.findById(id);+ Order.findOne({+ id, tenant: user.tenantId+ });Key Capabilities & Deep Dive
Cross-File Taint & Data Flow Analysis
Maps untrusted inputs from entry routes through service transformations to sensitive database sinks.
- Pinpoints injection flaws (SQLi, Command Injection, SSRF, Deserialization)
- Understands custom frameworks, microservice RPC bridges, and ORMs
- Filters out sanitized paths to maintain an ultra-low false alarm rate
Native Developer & Pull Request Integration
Seamlessly embeds into GitHub, GitLab, and CI pipelines, providing contextual reviews where developers work.
- Comments directly on relevant Pull Request code lines with one-click patch proposals
- Incremental diff scanning completing within seconds during pull request checks
- Non-blocking feedback loops keeping developer velocity at its peak
Automated Patch Generation with Verified Safety
Synthesizes context-compliant code remedies matching your repository’s coding standards.
- Generates ready-to-merge unit test cases and bug fixes
- Validates that patches fix the vulnerability without breaking business functionality
- Provides educational explanations for engineering team upskilling
How the System Works
Semantic Graph Compilation
Constructs Code Property Graphs (CPGs) combining ASTs, Control Flow Graphs, and Data Dependency Graphs.
Taint Propagation Analysis
Traces sources of untrusted external input to dangerous sinks across function boundaries.
LLM Contextual Verification
Employs a specialized security LLM to inspect sanitizers, business authorization checks, and logic flow.
Pull Request Remediation Bot
Posts clean, actionable patch suggestions and reproduction tests directly to the developer workflow.
Technical Specifications
Supported Languages & Frameworks
Analysis Metrics
Frequently Asked Questions
Q: How does Supradim avoid flooding developers with thousands of false positives?
Unlike legacy SAST scanners that match keyword patterns, our engine tracks complete taint propagation paths and uses LLM verification to verify whether input validation or sanitization occurs anywhere along the execution route.
Q: Does Supradim require uploading our entire proprietary source code?
No. Supradim can be deployed entirely on-premise or within your own private VPC. All code parsing, graph indexing, and model inferences remain strictly inside your security perimeter.
AI Pentesting & Autonomous Exploit Platform
State-of-the-art AI pentesting that autonomously maps attack surfaces, reasons through multi-step logic flaws, and provides verified proof-of-concepts.
004AI Honeypot & Agent Deception System
An intelligent AI honeypot deploying high-fidelity synthetic decoys to intercept automated bots, reverse attack TTPs, and drain LLM tokens with 0% false positives.
003Security for AI & Agents
Secures LLM applications against prompt injections, tool privilege escalation, and sensitive data leakage.