BugTraceAI

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Open-source, self-hosted web pentesting suite with agentic scanning, analyst tools, API testing, model checkpoints and MCP integrations.

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1# BugTraceAI

README.mdMCP server

Transport: stdio
Status: Local

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Server facts

Local

Transport: stdio
License: Apache-2.0
Last checked: 2026-10-28

Stars: 357
Tools: —
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Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install BugTraceAI?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does BugTraceAI need an API key?

No required environment variable is listed on this record.

What transport does BugTraceAI use?

BugTraceAI runs locally over stdio.

When was BugTraceAI last checked?

Last checked 2026-10-28. Open-source, self-hosted web pentesting suite with agentic scanning, analyst tools, API testing, model checkpoints and MCP integrations.

From the publisher

Documentation

I want to…	Start with
Run an agentic web assessment in a terminal, or automate it through REST/MCP	BugTraceAI-CLI
Investigate HTTP traffic, use analyst tools, follow scans and review reports in a browser	BugTraceAI-WEB
Assess an API target with contract-aware discovery and evidence review	BugTraceAI-API
Select modules, configure services and install the suite	BugTraceAI-Launcher
Explore the published BugTraceAI model checkpoints	BugTraceAI Models
Connect additional security tools through MCP	ReconFTW MCP
Practice against a deliberately vulnerable target	BugStore

WEB can connect to the CLI engine for web scans and the API engine for API-target scans. The Launcher lets you choose WEB, CLI, API or a combination.

Proven in the Security Community

CVEs Disclosed

Product	CVE	CVSS
Wallos	CVE-2026-27479	7.7 High
ZoneMinder	CVE-2026-27470	8.8 High
Piwigo	CVE-2026-27834	7.2 High

Presented On Stage

RootedCON 2026, Madrid, Spain
HKOSCon 2026, Hong Kong
DEF CON 34, Las Vegas, USA

See It Working

CLI 4.0.16-beta · interactive terminal workspace

BugTraceAI terminal workspace with Recon, Discovery, Strategy, Exploit, Validate and Report

The real TUI has five views: Pipeline, Findings, Agents, Timeline and Logs. Configure the target, crawl limits, Provider/F7 and Auth/F8 from the workspace. The terminal capture uses the built-in offline demo with sample data. Open the CLI screenshot gallery and installation guide.

WEB captures show the scan and reporting interfaces using the BugStore practice target. Report counts in screenshots describe those example sessions.

BugTraceAI combines AI-guided investigation with deterministic security tools. The AI prioritizes and reasons about hypotheses; tools and evidence validate what is real.

Disclaimer

This platform is provided for educational and authorized security testing purposes only.

Only test applications for which you have explicit, written authorization
AI output may contain inaccuracies, false positives, or false negatives
It is not a substitute for professional security auditing
The creators assume no liability for misuse or damage

Always verify findings manually.

What is BugTraceAI?

BugTraceAI is an open-source, self-hosted web pentesting suite for authorized security research. It combines agentic scanning, an analyst workspace, an independent API-testing engine, published model checkpoints and extensible tools. Its scanning engines connect AI investigation with security checks, validation and reporting.

Its agents plan and prioritize checks, route work to specialists and collect evidence through the scanning tools and validation stages.

Core Principles

Principle	Description
Privacy-First	Self-hosted scanning and report storage; analysis uses your configured LLM provider
Opensource	Apache-2.0 licensed public product repositories
Self-Hosted	Scan reports and local services stay on your infrastructure
Modular	Use components independently or together
Deployment	Local or Docker CLI profiles; full-platform setup through Launcher

The Ecosystem

The suite includes four independently deployable product components, published model checkpoints, MCP integrations and a dedicated practice target:

Component	Description	Repository
BugTraceAI-API	Standalone evidence-first API security testing service over REST and MCP	BugTraceAI-API
BugTraceAI-CLI	Autonomous security scanner with a Textual terminal workspace, REST API and MCP. Multi-agent pipeline with specialist tools and browser validation	BugTraceAI-CLI
BugTraceAI-WEB	Web dashboard with 20+ AI security tools, real-time scan monitoring, and CLI control center	BugTraceAI-WEB
BugTraceAI-Launcher	Guided deployment with CLI TUI/API profiles, local or Docker runtime, optional global btai, service management and an optional AI Setup & Repair Assistant	BugTraceAI-Launcher
MCP Ecosystem	Extensible agent framework using the Model Context Protocol. Includes integrated Kali Linux and ReconFTW agents	reconftw-mcp
BugStore	Deliberately vulnerable practice target used in demos and walkthroughs. Full-featured shop riddled with 32 planted OWASP vulnerabilities	BugTraceAI/BugStore
BugTraceAI Models	Published model checkpoints for bug bounty and web pentesting workflows	BugTraceAI Models

Use the CLI TUI locally, its API/MCP for automation, or the Launcher to install independent products or a combination. The WEB connects to the appropriate scanning backend for each engine; API scans use BugTraceAI-API and web scans use the CLI API.

Models and ModelLab

The suite's model ecosystem has three parts:

BugTraceAI Models: published security-focused checkpoints for bug bounty and web pentesting workflows. See the model catalog and individual model cards for requirements and usage.
External providers and models: configurable options supported by each product component. Provider support and model roles vary by module; follow its current configuration guide.
ModelLab: a benchmarking workspace in WEB for comparing selected OpenRouter models and reviewing their results and costs.

Publishing a checkpoint does not imply it is the default model in every component. Check each module's documentation for supported connections and configuration.

Published model families

Family	Focus	Model cards
CORE-Fast	Rapid triage and scanner-output review	CORE-Fast
CORE-Pro	Extended investigation, reporting and remediation support	CORE-Pro
CORE-Ultra	Structured PoC generation and tool-calling workflows	Q4 · Q6
Apex	Offensive security reasoning	Q4 · F16

Consult each model card for serving requirements, formats, license terms and intended use.

Providers by workflow

Workflow	Provider support described by the current public product documentation
CLI web scans	OpenRouter, Anthropic and Z.ai presets; Amazon Bedrock in beta; custom/local OpenAI-compatible presets. See the CLI configuration guide and Bedrock guide.
API-target investigation and AI review	OpenRouter, Anthropic, Z.ai and local Ollama; AI enrichment is optional. See API providers.
WEB analysis tools, chat and AIrepeater	OpenRouter, Anthropic and Z.ai. The provider configured for a connected CLI scan is a separate setting. See WEB setup.
WEB ModelLab	OpenRouter with the module's own key. See WEB workspace.
Launcher AI setup and repair	OpenRouter or Anthropic. Wizard supports Z.ai setup. See the Launcher guide.

Model support depends on the selected component, provider, task and configuration. Bedrock remains beta with real AWS account validation pending, as stated in its release notes.

Architecture

flowchart LR
    TUI[CLI terminal workspace] --> Engine[CLI scan engine]
    WEB[WEB dashboard] --> REST[CLI REST API]
    MCP[CLI MCP clients] --> Engine
    REST --> Engine
    WEB --> API[BugTraceAI-API]
    Engine --> Tools[Specialists and browser validation]
    Engine --> Reports[Scan reports]
    API --> Reports

The CLI stores scan metadata in SQLite and writes report artifacts to disk. The WEB uses PostgreSQL for its own chats, settings and analysis. The Launcher configures service connections and selected ports. Standalone local TUI setup opens the engine without starting an API server.

See the component documentation for deployment details.

Scanning Pipeline

The CLI terminal and WEB display the same six scan phases:

Phase	Purpose
Recon	Crawl the target and discover endpoints
Discovery	Analyze URLs and collect initial findings
Strategy	Consolidate findings and route work to specialists
Exploit	Run specialist checks and collect evidence
Validate	Verify findings through the validation stage
Report	Generate structured and human-readable deliverables

Target authentication supports Bearer tokens and login YAML with optional TOTP/2FA. In the TUI, configure it through Auth/F8, separately from the LLM provider's API key in Provider/F7. See the CLI installation guide.

Current Public Releases

Component	Version	Highlights
CLI	4.0.35-beta	Terminal TUI, web-scanning API/MCP, provider/auth setup and optional global `btai`
WEB	2.0.37-beta	Browser workspace for both scanning engines and reports
API	1.4.11-beta	Independent API-target engine with REST and MCP
Launcher	3.3.35	Universal TUI installer, independent module selection and Wizard or AI setup

CLI 4.0.35-beta fixes Discovery browser lifecycle cleanup and standalone TUI scan controls, and requires Chromium preflight before full scans. Launcher 3.3.35 pins this CLI release. Syntax, manifest consistency and patch whitespace checks completed; a live target scan and a fresh installation have not been run for these releases. WEB and API remain at the companion versions shown above.

Bedrock beta support and WEB region controls remain available. Real AWS account validation remains pending; see the Bedrock guide.

Demo Report

Want to see what BugTraceAI produces? Try the live demo or download a real scan report generated against BugStore -- our deliberately vulnerable practice app.

Benchmark note: This demo report was produced with an earlier scanner build. Results are useful for exploring the workflow, but should not be treated as a current performance claim for the latest CLI release until re-run under a versioned benchmark protocol.

The zip includes the full markdown report, validated findings JSON, specialist agent results with WET/DRY traceability, reconnaissance data, and PoC enrichment output.

CI/CD Integration Proposal

For CI/CD, automation can call the CLI REST/MCP interfaces for web scans or BugTraceAI-API for API-target testing. Reports and evidence are available for review in the WEB workspace. The diagram below proposes downstream AI review and ticketing integrations; connect them to the selected engine's supported interfaces. This keeps external automation, autonomous scanning, evidence-rich reporting, human review, and remediation coordination connected without hard-coding deployment-specific service endpoints.

Quick Start

Choose your setup

Terminal workspace: Linux and Python 3.10+ for local installation; some specialist tools also use Docker when scanning.
API/MCP or full WEB platform: select the relevant profile and runtime in the installer. Docker deployments need Docker Engine, Compose and Git.
Real scans: configure a supported provider's API key. Opening the TUI or its offline demo does not require starting a scan.

One-Command Install

One-liner (recommended):

curl -fsSL https://raw.githubusercontent.com/BugTraceAI/BugTraceAI-Launcher/main/install.sh | bash

Or clone and run manually:

git clone https://github.com/BugTraceAI/BugTraceAI-Launcher.git ~/bugtraceai-launcher
~/bugtraceai-launcher/launcher.sh

From this ecosystem checkout, ./install.sh opens the same universal menu with full suggested. Component ./install.sh entry points suggest their own product in that menu; they do not deploy a profile without your review.

Enter and verify a provider API key on the first screen, then choose Install with Wizard or Install with AI. Both stay in the TUI. Wizard supports every module combination. AI setup uses OpenRouter or Anthropic provider tokens; use Wizard for Z.ai. See the current Launcher guide for supported module combinations and installation options. The review shows selected modules, runtime, ports and optional WEB toolboxes. Terminal profiles can register a global btai command.

Let your AI coding agent run setup

If you use Codex, Claude Code, Cursor or another local terminal agent, give it this prompt:

Help me install BugTraceAI using the official universal Launcher.

First read:
https://github.com/BugTraceAI/BugTraceAI#readme
https://github.com/BugTraceAI/BugTraceAI-Launcher#readme

Follow those instructions using the official installer:
https://raw.githubusercontent.com/BugTraceAI/BugTraceAI-Launcher/main/install.sh

Ask which independent modules I want: BugTraceAI-WEB, BugTraceAI-CLI,
BugTraceAI-API, or a combination. Install only the modules I choose. Let me
choose Wizard or the built-in AI installer when my selection is supported;
use Wizard for other combinations.

Preserve any existing installation, configuration and data. Run the
Launcher in my local interactive terminal. I will enter and verify the
provider API key there, choose ports and review the plan before installation.
Keep credentials out of chat and logs. Do not start a scan.

Verify the selected services on their configured ports. If I enable the
global btai command, check it from a fresh shell. Report the installation
location, launch commands, checks completed and any checks still pending.

Profile	Installed products	Runtime
`terminal`	CLI terminal TUI	Local Python or Docker
`web`	WEB is preselected; add either or both scanning engines if needed	Docker
`full`	WEB + both scanning engines + CLI terminal TUI	Docker
`server`	CLI web-scanning API/MCP	Local Python or Docker
`terminal-server`	CLI TUI + web-scanning API/MCP, without WEB	Local Python or Docker
`api`	Independent BugTraceAI-API target engine, REST + MCP	Docker

For direct component installation, use each checkout's explicit scripts/install-runtime.sh backend or the documented Python/Compose commands. Follow INSTALLATION.md; a bare WEB docker compose up is not a complete configuration step.

Component entry points suggest their own module. A suggestion only sets the initial checkboxes; review the exact modules before installation.

Documentation

Full documentation is available in the Project Wiki:

Overview -- What BugTraceAI is and who it's for
Architecture -- System design and communication protocols
BugTraceAI-CLI -- Autonomous scanner documentation
BugTraceAI-WEB -- Web dashboard documentation
BugTraceAI-API -- REST/MCP API-security service, evidence artifacts, and deployment guidance
BugTraceAI-API on DeepWiki -- AI-powered codebase documentation and architecture exploration
BugTraceAI-Launcher -- Deployment guide
CLI API Reference -- CLI REST API and WebSocket endpoints
Getting Started -- Installation and first scan

Community & Support

Resource	Link
Website	bugtraceai.com
Wiki	GitHub Wiki
DeepWiki	AI-powered docs
Issues	GitHub Issues
Discord	Join the BugTraceAI community
Twitter	@yz9yt

Contributing

We welcome contributions: bug reports, feature requests, PRs, documentation improvements, and community tools. Open an issue on the respective repository to get started.

License

Apache License 2.0 — BugTraceAI-owned material is free to use, modify, and distribute under the terms of the Apache License, Version 2.0.

See LICENSE file in each repository.

I want to…

Start with

Run an agentic web assessment in a terminal, or automate it through REST/MCP

BugTraceAI-CLI

Investigate HTTP traffic, use analyst tools, follow scans and review reports in a browser

BugTraceAI-WEB

Assess an API target with contract-aware discovery and evidence review

BugTraceAI-API

Select modules, configure services and install the suite

BugTraceAI-Launcher

Explore the published BugTraceAI model checkpoints

BugTraceAI Models

Connect additional security tools through MCP

ReconFTW MCP

Practice against a deliberately vulnerable target

BugStore

Product

CVE

CVSS

Wallos

CVE-2026-27479

7.7 High

ZoneMinder

CVE-2026-27470

8.8 High

Piwigo

CVE-2026-27834

7.2 High

Principle

Description

Privacy-First

Self-hosted scanning and report storage; analysis uses your configured LLM provider

Opensource

Apache-2.0 licensed public product repositories

Self-Hosted

Scan reports and local services stay on your infrastructure

Modular

Use components independently or together

Deployment

Local or Docker CLI profiles; full-platform setup through Launcher

Component

Description

Repository

BugTraceAI-API

Standalone evidence-first API security testing service over REST and MCP

BugTraceAI-API

BugTraceAI-CLI

Autonomous security scanner with a Textual terminal workspace, REST API and MCP. Multi-agent pipeline with specialist tools and browser validation

BugTraceAI-CLI

BugTraceAI-WEB

Web dashboard with 20+ AI security tools, real-time scan monitoring, and CLI control center

BugTraceAI-WEB

BugTraceAI-Launcher

Guided deployment with CLI TUI/API profiles, local or Docker runtime, optional global btai, service management and an optional AI Setup & Repair Assistant

BugTraceAI-Launcher

MCP Ecosystem

Extensible agent framework using the Model Context Protocol. Includes integrated Kali Linux and ReconFTW agents

reconftw-mcp

BugStore

Deliberately vulnerable practice target used in demos and walkthroughs. Full-featured shop riddled with 32 planted OWASP vulnerabilities

BugTraceAI/BugStore

BugTraceAI Models

Published model checkpoints for bug bounty and web pentesting workflows

BugTraceAI Models

Family

Focus

Model cards

CORE-Fast

Rapid triage and scanner-output review

CORE-Fast

CORE-Pro

Extended investigation, reporting and remediation support

CORE-Pro

CORE-Ultra

Structured PoC generation and tool-calling workflows

Q4 · Q6

Apex

Offensive security reasoning

Q4 · F16

Workflow

Provider support described by the current public product documentation

CLI web scans

OpenRouter, Anthropic and Z.ai presets; Amazon Bedrock in beta; custom/local OpenAI-compatible presets. See the CLI configuration guide and Bedrock guide.

API-target investigation and AI review

OpenRouter, Anthropic, Z.ai and local Ollama; AI enrichment is optional. See API providers.

WEB analysis tools, chat and AIrepeater

OpenRouter, Anthropic and Z.ai. The provider configured for a connected CLI scan is a separate setting. See WEB setup.

WEB ModelLab

OpenRouter with the module's own key. See WEB workspace.

Launcher AI setup and repair

OpenRouter or Anthropic. Wizard supports Z.ai setup. See the Launcher guide.

flowchart LR TUI[CLI terminal workspace] --> Engine[CLI scan engine] WEB[WEB dashboard] --> REST[CLI REST API] MCP[CLI MCP clients] --> Engine REST --> Engine WEB --> API[BugTraceAI-API] Engine --> Tools[Specialists and browser validation] Engine --> Reports[Scan reports] API --> Reports

Phase

Purpose

Recon

Crawl the target and discover endpoints

Discovery

Analyze URLs and collect initial findings

Strategy

Consolidate findings and route work to specialists

Exploit

Run specialist checks and collect evidence

Validate

Verify findings through the validation stage

Report

Generate structured and human-readable deliverables

Component

Version

Highlights

CLI

4.0.35-beta

Terminal TUI, web-scanning API/MCP, provider/auth setup and optional global btai

WEB

2.0.37-beta

Browser workspace for both scanning engines and reports

API

1.4.11-beta

Independent API-target engine with REST and MCP

Launcher

3.3.35

Universal TUI installer, independent module selection and Wizard or AI setup

Help me install BugTraceAI using the official universal Launcher. First read: https://github.com/BugTraceAI/BugTraceAI#readme https://github.com/BugTraceAI/BugTraceAI-Launcher#readme Follow those instructions using the official installer: https://raw.githubusercontent.com/BugTraceAI/BugTraceAI-Launcher/main/install.sh Ask which independent modules I want: BugTraceAI-WEB, BugTraceAI-CLI, BugTraceAI-API, or a combination. Install only the modules I choose. Let me choose Wizard or the built-in AI installer when my selection is supported; use Wizard for other combinations. Preserve any existing installation, configuration and data. Run the Launcher in my local interactive terminal. I will enter and verify the provider API key there, choose ports and review the plan before installation. Keep credentials out of chat and logs. Do not start a scan. Verify the selected services on their configured ports. If I enable the global btai command, check it from a fresh shell. Report the installation location, launch commands, checks completed and any checks still pending.

Profile

Installed products

Runtime

terminal

CLI terminal TUI

Local Python or Docker

web

WEB is preselected; add either or both scanning engines if needed

Docker

full

WEB + both scanning engines + CLI terminal TUI

Docker

server

CLI web-scanning API/MCP

Local Python or Docker

terminal-server

CLI TUI + web-scanning API/MCP, without WEB

Local Python or Docker

api

Independent BugTraceAI-API target engine, REST + MCP

Docker

Resource

Link

Website

Wiki

DeepWiki

Issues

Discord

Join the BugTraceAI community

Twitter

@yz9yt

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install BugTraceAI?

Does BugTraceAI need an API key?

What transport does BugTraceAI use?

When was BugTraceAI last checked?

Documentation

Jump To

Proven in the Security Community

CVEs Disclosed

Presented On Stage

See It Working

Disclaimer

What is BugTraceAI?

Core Principles

The Ecosystem

Models and ModelLab

Published model families

Providers by workflow

Architecture

Scanning Pipeline

Current Public Releases

Demo Report

CI/CD Integration Proposal

Quick Start

Choose your setup

One-Command Install

Let your AI coding agent run setup

Documentation

Community & Support

Contributing

License

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install BugTraceAI?

Does BugTraceAI need an API key?

What transport does BugTraceAI use?

When was BugTraceAI last checked?

Documentation

Jump To

Proven in the Security Community

CVEs Disclosed

Presented On Stage

See It Working

Disclaimer

What is BugTraceAI?

Core Principles

The Ecosystem

Models and ModelLab

Published model families

Providers by workflow

Architecture

Scanning Pipeline

Current Public Releases

Demo Report

CI/CD Integration Proposal

Quick Start

Choose your setup

One-Command Install

Let your AI coding agent run setup

Documentation

Community & Support

Contributing

License