Caido vs Reconmap

Caido is a web security auditing toolkit for scaling manual testing through AI and teamwork. Its proxy intercepts and monitors HTTP and WebSocket traffic, with history for intercepted traffic and WebSocket messages. HTTPQL filtering lets users search requests and responses. Node-based workflows support ad-hoc automation, and automated attacks can use custom payloads and placeholders. Users can connect existing LLM providers, including Anthropic, Google, OpenAI, and providers available through OpenRouter. AI agents can access Caido programmatically through its Client SDK. Community plugins and custom extensions are supported; the Basic plan allows three plugins. Basic is free forever and includes two projects, seven workflows, five filter presets, and one pipeline session at a time. The pricing note lists paid access from $20/user/mo, while the opened pricing page did not display prices for Individual, Team, or Enterprise. Caido lists Linux, macOS, Windows, web, API, and self-hosted platforms, and presents the product for pentesters, security engineers, and bug bounty hunters.

Reconmap is a free, open-source collaboration platform for planning, conducting, and documenting penetration test projects across assets and clients. It supports multiple top-level organisations and includes project templates, task management, and client management. Vulnerability tracking and a templates database help organize findings, while users can automate security commands and schedule them with cron expressions. Reports can be generated in Word, Markdown, and Typst formats, with custom whitelabel reporting. Integrations can send vulnerabilities to Jira or Azure DevOps and deliver event-driven HTTP notifications through webhooks. Security features include SSO, OpenID and SAML user federation, two-factor authentication, email verification, and an audit log. A REST API with token authentication supports connections to external tools and scripts. Deployment options include Docker Compose, Kubernetes, manual installation, and hosted SaaS maintained by the project’s lead developers through Netfoe. The documentation positions Docker Compose for small teams and Kubernetes for production deployments and large teams; it also cautions that Compose is not designed for high availability or horizontal scaling out of the box.