SUNNYVALE — Armorblox says it has closed Series A funding with $16.5 million led by General Catalyst. The startup announced it has built the world’s first natural language understanding (NLU) platform for cybersecurity, analyzing sensitive information in emails and documents, and providing a new way to intelligently detect, alert and protect against identity-related attacks and data loss.
Other investors include Ramu Arunachalam (A Capital), Ron Conway (SV Angel), Point72 Ventures, Robin Vasan, John Thompson, Gerhard Eschelbeck, Oliver Friedrichs, and DJ Patil.
“Armorblox is using NLU to solve the number one challenge for CSOs: the human layer,” said Maurice Stebila, CISO for Harman, a Samsung company. “By applying NLU, Armorblox is able to address a whole new layer of security that has been inaccessible to other security solutions: the content and context of communications. This has been the biggest challenge and attack vector because hackers know that they can exploit this weakness.”
With employees communicating through emails and documents on a daily basis, people-hacking has become the top attack vector for stealing data. Even when organizations heavily invest in security solutions and employee training, email continues to be the biggest attack vector, responsible for 94%1 of all attacks. Hackers are bypassing traditional metadata-based email security solutions through social engineering. It is also easy for employees to make mistakes, such as sending a sensitive document to the wrong person.
“We see Armorblox as a valuable platform using AI to analyze the way people write, and what they write, to catch possible business email compromises that we could not catch otherwise,” said Chuck Drobny, president and CEO of GlobaLogix. “Armorblox found an email spoofing me as the CEO, asking my CFO to make a payment. Other solutions missed it, and this could have resulted in us cutting a check to someone that wasn’t authorized.”
Armorblox uses deep learning and NLU to detect, respond and protect against identity-related attacks and data loss. It also provides fine-grained visibility into sensitive data flowing across an organization.
- A natural language engine that derives new insights from enterprise communications and data.
- Automated policy recommendations by learning what is important for the organization.
- An alert remediation framework that distributes context-sensitive alerts to the relevant users, saving time for the security team.