BBOT 30 Unleashed: Recursive Reconnaissance At DEF CON 34 — The Rust-Powered Attack Surface Mapping Revolution + Video

Introduction

In the high-stakes world of offensive security, reconnaissance is the cornerstone of every successful engagement. The difference between a comprehensive attack surface map and a fragmented snapshot often determines whether a penetration test uncovers critical vulnerabilities or misses them entirely. At DEF CON 34’s Recon Village, Black Lantern Security is set to demonstrate BBOT 3.0 — a recursive internet scanner that fundamentally reimagines how security professionals approach OSINT and attack surface mapping.

Learning Objectives

Master the installation, configuration, and execution of BBOT 3.0 for automated reconnaissance and bug bounty workflows
Understand the recursive event-driven architecture that enables continuous discovery without traditional pipeline bottlenecks
Leverage the Rust-powered performance improvements — including BlastDNS and BlastHTTP — to achieve 15× faster DNS resolution and dramatically reduced memory consumption
Integrate BBOT scan results with SIEM platforms, graph databases, and message queues for enterprise-scale attack surface management
Deploy BBOT against live, in-scope targets with a repeatable workflow that produces actionable intelligence

You Should Know

1. The Recursive Philosophy: Beyond Traditional Pipelines

Traditional reconnaissance tools operate in linear phases: enumerate subdomains, then port-scan, then web-spider, then extract metadata. The fundamental flaw in this approach is that discoveries made in later stages — such as a new subdomain uncovered during SSL certificate analysis — never feed back into earlier stages, leaving the attack surface incomplete.

BBOT solves this through recursive event-driven architecture. Every module consumes a specific type of data (an “event”) and emits new events that are redistributed to all other modules. For example, the `nmap` module consumes `DNS_NAME` and produces OPEN_TCP_PORT; the `sslcert` module consumes `OPEN_TCP_PORT` and produces new `DNS_NAME` from certificate data. These two modules alone, when enabled together, feed each other recursively — each new subdomain is scanned for open ports, each open port is checked for SSL certificates, and each certificate may reveal additional hostnames.

With over 100 modules spanning subdomain enumeration, email harvesting, cloud bucket discovery, port scanning, web spidering, and vulnerability scanning (including nuclei integration), BBOT’s recursive approach consistently uncovers 20–50% more subdomains than competing tools — with the gap widening as target scope increases.

Step-by-Step: Understanding the Event Flow

1. Start with a target: evilcorp.com (DNS_NAME event)
2. DNS brute-force module consumes DNS_NAME → produces additional DNS_NAMEs
3. Portscan module consumes each DNS_NAME → produces OPEN_TCP_PORT events
4. SSLCert module consumes OPEN_TCP_PORT → extracts DNS_NAMEs from certificates
5. HTTP module consumes OPEN_TCP_PORT → probes web services, extracts more DNS_NAMEs
6. New DNS_NAMEs feed back to step 2 — the cycle continues until no new data emerges

2. Installation and First Scan: Getting BBOT Running

BBOT 3.0 requires Linux and Python 3.9+. The recommended installation method uses `pipx` for isolated execution:

 Install pipx if not already available
python3 -m pip install --user pipx
python3 -m pipx ensurepath

Install stable BBOT 3.0
pipx install bbot

Install bleeding-edge development branch
pipx install --pip-args '--pre' bbot

For containerized environments, Docker images are available in four flavors: dev, dev-full, stable, and stable-full:

docker pull blacklanternsecurity/bbot:stable
docker run -v $(pwd)/output:/bbot/output blacklanternsecurity/bbot:stable -t evilcorp.com -p subdomain-enum

Speed Tip: BBOT’s DNS resolver (BlastDNS) spins up multiple threads per resolver in /etc/resolv.conf. Adding more unfiltered DNS resolvers dramatically accelerates scans. A sample `resolv.conf` with 50+ resolvers can be found in the BBOT documentation.

First Scan: Subdomain Enumeration

 Passive API sources plus recursive DNS brute-force
bbot -t evilcorp.com -p subdomain-enum

Passive sources only (no active DNS brute-force)
bbot -t evilcorp.com -p subdomain-enum -rf passive

Output unique subdomains to a text file
bbot -t evilcorp.com -p subdomain-enum -m subdomains

Web Spider for Email and Asset Discovery

 Crawl target, extract emails and other intelligence
bbot -t evilcorp.com -p spider

Quick email enumeration with free APIs + scraping
bbot -t evilcorp.com -p email-enum

3. BBOT 3.0’s Rust-Powered Performance Revolution

The most significant advancement in BBOT 3.0 is the complete rewrite of core DNS and HTTP engines in Rust. Black Lantern Security developed two native libraries specifically for BBOT:

BlastDNS: An ultra-fast async DNS resolver with built-in caching, retries, and per-resolver parallelism. It replaces `dnspython` and delivers 15× faster resolution.
BlastHTTP: Replaces both `httpx` and the old subprocess-based HTTP engine with a single, in-process client shared by every module. It drives everything from simple URL probing to full directory brute-forcing at speeds comparable to dedicated tools like FFUF — without ever leaving the BBOT process.

Performance Benchmarks

In testing against `mubi.com` with various profiles, BBOT 3.0 achieved the same results as BBOT 2.x using a fraction of the CPU and memory, completing scans significantly faster. For larger scans focusing on non-active subdomain enumeration, speed essentially evened out, but BBOT 3.0 actually found more subdomains while maintaining improved memory and CPU profiles.

Memory Optimization: HTTP responses can now spill to disk instead of staying in RAM for the entire scan. CPU-heavy tasks have been moved off the main event loop to keep scans running smoothly.

4. SIEM Integration and Enterprise-Grade Output

BBOT 3.0 transforms reconnaissance output from isolated findings into enterprise-ready intelligence. The `siem_friendly` option is now the default, with output adapted for SQL databases, NoSQL stores, and SIEM platforms out of the box.

Supported Output Modules:

MongoDB
Elasticsearch
Kafka
RabbitMQ
NATS
ZeroMQ
SQL (existing support)

Real-Time SIEM Streaming:

Splunk: Direct streaming via HTTP Event Collector (HEC)
Elasticsearch: Via the HTTP output module

Elastic Integration: BBOT results can be ingested into Elastic for review and analysis, with standardized UTC timestamps and the `reverse_host` field for SIEM compatibility.

Example: Output to Elasticsearch

bbot -t evilcorp.com -p subdomain-enum -m elasticsearch \
--config elasticsearch.host=http://localhost:9200 \
--config elasticsearch.index=bbot_scans

Example: Output to Kafka

bbot -t evilcorp.com -p full-scan -m kafka \
--config kafka.bootstrap_servers=localhost:9092 \
--config kafka.topic=bbot_events

5. Advanced Scanning Profiles and Preset Configuration

BBOT 3.0 introduces strengthened preset validation — errors in presets now display clear error messages with “did you mean…?” hints for typos (e.g., “Did you mean ‘scope.strict’?”).

Preset Example: Subdomain Enumeration (`subdomain-enum.yml`)

description: Enumerate subdomains via APIs and brute-force
flags:
- subdomain-enum
output_modules:
- subdomains
config:
dns:
threads: 25
brute_threads: 1000
 API keys for enrichment modules
 modules:
 github:
 api_key: ""
 chaos:
 api_key: ""
 securitytrails:
 api_key: ""

Preset Example: Web Spider (`spider.yml`)

description: Recursive web spider extracting emails and intelligence
modules:
- http
blacklist:
- "RE:/.(sign|log)[_-]?out"
config:
web:
spider_distance: 2
spider_depth: 4
spider_links_per_page: 25

Running Custom Presets

bbot -t evilcorp.com -c /path/to/custom.yml

The DEF CON 34 Recon Village Workshop: What to Expect

On Friday, August 7, 3:30–6:00 PM at the Recon Village Workshop Area, Las Vegas Convention Center, Mark Gaddy will lead one of only six workshops selected for DEF CON 34. This is a hands-on session against your own targets — not a demo.

Workshop Highlights:

Live Installation and Configuration: Attendees install and configure BBOT on their laptops, then run it live against their own scoped bug bounty targets
BBOT 3.0 Architecture Deep Dive: Mark will cover the Rust rewrite of DNS and HTTP internals, explaining the performance gains and architectural decisions
Repeatable Recon Workflow: You leave with real scan output and a workflow you can reproduce — not slides
The “One Command” Philosophy: Everything BBOT finds becomes the next thing it looks for — no stopping, no handoffs, no gaps

What to Bring:

A laptop with Python installed
An in-scope bug bounty target (or a target you have permission to scan)

The Full Recon Village Lineup:

Supply chain reconnaissance
Threat actor profiling
Live DPRK npm delivery network mapping from public data
ASM ownership attribution with OWASP Amass
Building an OSINT platform with AI coding agents

What Undercode Say:

Recursion is the missing link in modern reconnaissance. Most tools treat recon as a linear pipeline, but real attack surface discovery is cyclical — every new finding should trigger re-evaluation of everything discovered before. BBOT’s event-driven architecture finally operationalizes this principle at scale.
Performance matters more than feature count. BBOT 3.0’s Rust rewrite isn’t just about speed — it’s about sustainability. Lower memory consumption means you can run larger scans without infrastructure costs spiraling out of control. The ability to spill HTTP responses to disk instead of RAM is a game-changer for enterprise-scale recon.
SIEM integration transforms recon from ephemeral to strategic. When scan results flow directly into Elasticsearch or Splunk, they become part of the organization’s permanent security intelligence. This turns one-off bug bounty findings into continuous attack surface monitoring.
The DEF CON 34 workshop is a must-attend for serious practitioners. Hands-on training with the tool’s creators, against your own targets, with a repeatable workflow — this is the kind of knowledge transfer that actually moves the needle for security teams.
BBOT’s recursive approach consistently outperforms traditional tools by 20–50%. The gap widens with larger targets, making it particularly valuable for enterprise ASM programs and large-scale bug bounty operations.

Prediction:

+1 BBOT’s recursive architecture will influence a new generation of reconnaissance tools, moving the industry away from linear pipelines toward event-driven, self-perpetuating discovery engines.
+1 The Rust-powered performance improvements position BBOT as the go-to tool for large-scale attack surface management, potentially displacing slower Python-based alternatives in enterprise environments.
-1 Organizations that fail to adopt recursive reconnaissance methodologies will continue to operate with incomplete attack surface visibility, leaving gaps that attackers will inevitably exploit.
+1 SIEM integration capabilities will drive adoption among security operations teams, bridging the gap between offensive recon findings and defensive monitoring — a crucial step toward proactive security posture management.
+1 The open-source nature of BBOT, combined with its modular architecture, will accelerate community-driven innovation, with new modules continuously expanding its capabilities across emerging threat vectors.

▶️ Related Video (76% Match):

https://www.youtube.com/watch?v=3F5icGjDWfg

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