Jetstack, OpenCredo and Cygnacom funded at Machine Identity Protection Live
Venafi®, the inventor and leading provider of machine identity protection, today announced the launch of the Machine Identity Protection Development Fund at Machine Identity Protection Live. The first $12.5 million tranche of the fund provides developers with direct sponsorship from Venafi to help accelerate the delivery of comprehensive protection for all machine identities.
Venafi will use the Machine Identity Protection Development Fund to sponsor a range of developers, including consultants, systems integrators, fast-moving startups, open-source developers and other cybersecurity vendors. Funded developers will create integrations that ensure every new machine identity is automatically updated in the Venafi Platform.
“The Machine Identity Protection Development Fund is the next logical step for cybersecurity,” said Kevin Bocek, vice president of security strategy and threat intelligence for Venafi. “While we spend over $8 billion protecting the identities of humans on our networks, we invest very little in time, resources and money to safeguard the identities of machines, especially those used in the cloud, in DevOps environments and on IoT devices. As the volume, velocity, variety and volatility of machines continue to increase, the need for comprehensive machine identity protection grows exponentially. By providing developers with direct sponsorship, Venafi is accelerating the rate at which these complex problems are solved for the Global 5000 and, at the same time, expanding their strong, thriving partner ecosystem.”
At Machine Identity Protection Live, Venafi also named the first three developers to receive sponsorships:
- Jetstack, an open-source developer and innovator, helps organizations deploy Kubernetes at scale in production environments. The company will use the funds to make their cert-manager automation framework ready for production workloads with TLS machine identities that are delivered and secured by the Venafi Platform. This will allow DevOps teams that use Kubernetes to move quickly while security teams can rest assured that enterprise security policies for machine identities are being enforced. Using the power of the Venafi Platform, Jetstack will achieve another industry first: enabling security administrators to validate and audit the current state of certificates used in Kubernetes. This is something that cannot be accomplished by humans or traditional network scanners in dynamic microservices and containerized environments.
- OpenCredo, a software consultancy specializing in machine learning, cloud and DevOps applications, will use the funds to create the industry’s first open-source Kafka connector for SSH. The connector will leverage machine identity intelligence from the Venafi Platform to feed graph databases. This will enable organizations to identify SSH machine identity risks, vulnerabilities and anomalies in real time.
- Cygnacom is a global leader in developing and deploying public key infrastructure (PKI) and identity and access management for the world’s most security-conscious government and commercial organizations. Using the Venafi Adaptable Certificate Authority Driver interface, Cygnacom built its eConnector, which integrates Entrust Authority Security Manager for PKI with the Venafi Platform and is used in production by Venafi customers. Cygnacom will use the funds to extend its eConnector product line and automate the machine identity life cycle for IBM System Z mainframes running RACF CA.
The Machine Identity Protection Development Fund encourages recipients to build integrations that deliver greater visibility, intelligence and automation across any technology that creates or consumes machine identities including:
- Cloud and hybrid cloud infrastructure
- DevOps
- Containerization
- Secure Shell (SSH)
- Code-signing
- Enterprise mobility management (EMM) and mobile device management (MDM)
- Artificial intelligence, machine learning and big data analytics
- IoT
- Blockchain distributed ledger technology