Think like an attacker.
Everything you need. Nothing you don't.
Deep Attack Surface Scanning
Automated analysis across seventeen coordinated modules — security headers, TLS, authentication flows, APIs, CORS, cloud configuration drift, input validation, cryptography, dependency risks, sensitive file exposure, DNS reconnaissance, email authentication (SPF/DKIM/DMARC), admin endpoint discovery, information disclosure, technology fingerprinting, HTTPS enforcement, and row-level security testing — so one run mirrors the breadth a red team would cover manually.
AI-Powered Reasoning Engine
Instead of dumping raw findings, RedLens synthesizes evidence the way an experienced tester would: hypothesizing likely weaknesses, validating them with targeted probes, and explaining why each issue matters in the context of your app.
Validated Exploit Chains
Confirmed vulnerabilities are stitched into realistic escalation stories with safe, detection-oriented validation — showing how an attacker could chain smaller issues into meaningful impact rather than leaving you with disconnected alerts.
Deep Reconnaissance
RedLens inspects what is publicly reachable: JavaScript bundles, authentication patterns, shadow APIs, and environmental clues that traditional scanners often skip — all while keeping workloads on RedLens-controlled infrastructure.
Self-Improving Detection
The platform is built to expand coverage as new attack patterns emerge, rolling forward-looking detection modules without waiting for a monolithic scanner release cycle.
Pentest-Grade Reports & Fixes
Deliverables read like consultant output: severity, CWE references, concrete evidence, affected URLs, and AI-authored remediation snippets you can adapt directly in your editor.
MCP & CLI Integrations
Install the local MCP server with `npx @redlens/mcp-server` for IDE and terminal workflows, or attach remote MCP inside hosted AI chats. Documentation and remote endpoints are published alongside the web app so security checks stay inside the tools engineers already use.
Safe-by-Design Operations
Scans emphasize non-destructive probes, rate limits, logging, and cleanup guarantees so production-adjacent testing stays predictable for operators who cannot afford noisy or invasive tooling.
Built to solve a real problem.
Modern attack surfaces sprawl across edge configuration, client-side bundles, APIs, identity flows, and third-party dependencies — yet most automated scanners still behave like glorified checklists. They flood teams with theoretical findings, struggle to narrate multi-step attacker paths, and rarely meet developers inside the editors where fixes actually happen. Manual pentests close the gap but cannot run continuously, leaving long blind spots between engagements.
RedLens unifies high-coverage reconnaissance, AI-driven reasoning, and chain validation in a web-first product hosted at redlens.langelogic.com. Security and platform teams get continuous, pentester-style narratives without self-hosting scanners, while engineers adopt the same workflows through MCP-aware assistants. The result is faster evidence, clearer exploit stories, and remediation guidance that maps to how modern cloud and SPA systems are built.
Frequently asked questions.
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