AI-powered attack simulation platform for enterprise security validation
Pentera automates penetration testing and breach simulation across on-premises, cloud, and external infrastructure using Python, C/C++, Go, and security tools like Metasploit, Cobalt Strike, and Impacket. The project list reveals active work on advanced attack path logic, AI-driven decision modules, and scalable backend systems — infrastructure-heavy priorities that align with their stated focus on production-grade attack simulation. Hiring is accelerating across engineering, security research, and a newly-built procurement function, suggesting operational scaling alongside product maturation.
Pentera builds an automated security validation platform designed for enterprise security teams. The product emulates real-world attacks across hybrid environments to identify exploitable vulnerabilities, rank remediation by actual risk impact, and demonstrate measurable security improvements to leadership. Founded in 2015 and headquartered in Burlington, Massachusetts, Pentera operates across 201–500 employees with active hiring in the United States, Israel, Germany, Spain, Singapore, and the UAE. The company is addressing internal scaling challenges around backend systems, customer success operations, and vendor management as customer relationships expand.
Pentera's stack includes AWS, Azure, Python, C/C++, Go, and security-focused tools: Metasploit, Cobalt Strike, Impacket, Burp Suite, IDA, and Ghidra. Core infrastructure runs on MongoDB Atlas, Docker, Ansible, and Ubuntu.
Pentera is headquartered in Burlington, Massachusetts. The company hires across multiple regions including Israel, Germany, Spain, Singapore, and the UAE alongside the United States.
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Pentera'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.