bifrost security vs Falco

Bifrost Security provides runtime security for containerised workloads, using observed behaviour to assess CVEs and generate workload-specific protections. Its agent monitors system calls, file access, signals, capabilities, and network ports at kernel level without requiring code changes. For each CVE, Bifrost reports whether it is reachable, mitigated by a security profile, or never loaded, and provides evidence for the verdict. The agent collects behavioural metadata only; Bifrost says it does not collect application data or personal information. The product can ingest CycloneDX and SPDX SBOMs and rescan them for CVEs across environments. It also creates default-deny AppArmor profiles from observed workload behaviour. Deployment is as a DaemonSet via Helm, with stated resource use below 200 MB RAM per node and below 1% performance impact. Bifrost supports Kubernetes, Docker Swarm, and Nomad workloads. A 14-day trial includes the full Pro edition and requires no credit card. Pricing is on request. The company is based in Stockholm, Sweden.

Falco is a free, open source runtime security project for Linux and self-hosted environments. It monitors hosts, containers, Kubernetes, and cloud environments for abnormal behavior, potential threats, and compliance violations in real time. Events are compared with built-in detection rules, and users can create rules for their own environments. Sources include Linux kernel system calls, Kubernetes audit logs, cloud events such as AWS CloudTrail, and events from GitHub and Okta. For kernel event monitoring, Falco uses an eBPF driver by default and offers a kernel module for wider compatibility. Installation options cover Linux hosts, Docker containers, and Kubernetes, including official Helm charts; supported architectures include x86_64 and ARM64. Falcosidekick can forward events to more than 50 systems, including email, chat, message queues, serverless functions, and databases. Falco is hosted by the CNCF as a graduated project. Detection depends on having appropriate rules in place, while resource use varies with server load and workload. The project recommends testing performance in the target environment.