DryRun Security
DryRun Security is an AI-native code security verification platform that provides contextual SAST, PR code reviews, and repository-wide security scanning. The platform understands code intent, validates exploitability, and guides remediation across human and AI-generated code, processing over 500,000 code reviews weekly. It integrates directly with GitHub, GitLab, and Slack to deliver findings where developers already work.
- Artificial Intelligence
- AI Agents
- Cybersecurity
- Developer Tools
- Software Only
Funding
Founders
Product
Problem
Traditional SAST tools rely on regex and pattern libraries that generate high volumes of false positives, forcing security teams to manually triage noise instead of focusing on real risks. These tools lack contextual understanding of how code actually works, making them ineffective at detecting logic bugs, authorization flaws, and injection vulnerabilities that require understanding data flow and application architecture.
Solution
DryRun Security provides an AI-native code security intelligence platform that builds a living knowledge graph of each codebase, mapping architecture, authorization boundaries, data flow, and behavioral history. The platform's Contextual Security Analysis engine uses specialized agents to trace how input, logic, permissions, and data move across applications, validating exploitability and applying confidence scores before raising alerts. DryRun delivers findings directly in pull requests with actionable remediation guidance, acting as a force multiplier for AppSec teams by screening out noise and providing instant feedback to developers. The platform continuously evaluates its multi-model AI engine to ensure accuracy and performance, and it supports custom natural language security policies that are automatically enforced on every code change.
Target Audience
Primary customers are security engineering teams and AppSec professionals at software companies that need to secure both human-written and AI-generated code at scale, particularly organizations with high pull request volumes or those adopting AI coding assistants.
Features
- Contextual Security Analysis engine that inspects data flow across files and services, achieving 2X more accuracy than traditional SAST while reducing noise by 90%
- Continuously updated knowledge graph mapping architecture, code relationships, Git behavior, frameworks, routes, auth, and data flow
- PR Code Review agent that surfaces code context, security findings, and change summaries in every pull request
- DeepScan Agent for full-repository baseline scans that locate structural risks and vulnerabilities across the entire codebase
- Custom Code Policies written in natural language and automatically enforced on every code change with no regex or rule groups to maintain
- Triage & Trends dashboard tracking cumulative findings, triage status, and risk trends across the security program
- Developer Activity monitoring that maps coding patterns, velocity metrics, and recurring risks to the engineers introducing them
- MCP integration supporting AI coding agents including Claude Code, Claude Desktop, Codex, and Cursor
- Multi-language support for Python, JavaScript, TypeScript, Java, C#, Ruby, and Golang
- Integrations with GitHub, GitLab, and Slack for notifications and team collaboration