Continuous attack surface discovery and penetration testing platform
BreachLock operates a hybrid offensive-and-backend engineering stack: Python + FastAPI + Django on PostgreSQL/MongoDB for core services, Kubernetes + Kafka for scaling, and a full arsenal of pentest tools (Burp Suite, Metasploit, Kali Linux) for attack surface work. Active hiring is split across engineering (backend/automation focus), sales, and security roles—typical of a services-plus-platform hybrid scaling from 51–200 headcount. Projects reveal a company pivoting toward product-led delivery: LLM orchestration, RAG pipelines, multi-agent systems, and AEV (attack exposure visualization) POVs suggest an attempt to systematize and scale manual pentest work via AI automation.
BreachLock provides continuous attack surface discovery, penetration testing, and red team services to mid-market and enterprise buyers. Founded in 2019 and based in New York, the company combines human-led offensive security with internal tooling to identify, validate, and help remediate exposures across client infrastructure. The product roadmap and active project list indicate a shift from pure services toward a platform model: internal LLM and multi-agent pipelines suggest automation of reconnaissance and vulnerability identification, while technical demos and new service offerings point to productization of attack surface management.
Backend: Python, FastAPI, Django, PostgreSQL, MongoDB, Dgraph. Infrastructure: GCP, Kubernetes, Kafka, Docker. Frontend: React, Next.js, TypeScript, Tailwind CSS. Offensive tooling: Burp Suite, Metasploit, Kali Linux, Nmap, Wireshark.
Attack surface visualization (AEV) POVs, infrastructure vulnerability scanning, offensive capability development, LLM orchestration and RAG pipelines, multi-agent systems, and internal automation tooling for scaling pentest delivery.
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BreachLock, Inc.'s technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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