Identity threat protection built on recaptured darknet breach and malware data
SpyCloud turns stolen credential, malware and phishing data into identity threat protection for enterprises and government. Its stack pairs Databricks, Spark and Airflow pipelines with PyTorch, AWS Bedrock and LangGraph, pointing to a push into agentic AI on top of breach data. Sales-heavy hiring and repeated federal and partner themes show growth riding on public sector and channel revenue.
SpyCloud, founded in 2016 and headquartered in Austin, Texas, is a privately held cybersecurity company with 201–500 employees. It collects exposed identity data from breaches, infected devices and phishing campaigns and uses it to help organizations prevent account takeover and ransomware, detect insider threats and support cybercrime investigations. Customers include large enterprises, mid-sized companies and government agencies, and its data also feeds third-party dark web monitoring and identity theft protection products. Current hiring is concentrated in the United States.
SpyCloud runs on AWS with Python, Go and TypeScript, using Databricks, Spark, Airflow and Elasticsearch for data, PyTorch, TensorFlow, AWS Bedrock and LangGraph for AI, and Salesforce, HubSpot and Outreach for sales.
Yes. Sales is SpyCloud's largest hiring area, mostly senior roles, with themes around public sector pre-sales and partner revenue, alongside smaller data, engineering, product and security openings in the United States.
Job posts point to AI agent and ML platform integration, a next-generation API architecture, data platform and context hubs, and go-to-market work for federal customers and partners.
Other companies in the same industry, closest in size
SpyCloud'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 →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.