Dreadnode vs Enkrypt AI

About Dreadnode

Dreadnode sells an infrastructure platform that gives security teams the means to own, operationalize, and improve agentic cyber capabilities. The Dreadnode Platform equips defenders with ready-to-run capabilities, shared operational knowledge, and the ability to run agents. Dreadnode describes the path to operationalize agents as fragmented and opaque. Dreadnode's capabilities are operator-authored agents for security testing, research, and operations, connected to the tools a team already uses.^[3][5]

Ready-to-run cyber capabilities on the Dreadnode Platform put agents to work on security testing, research, and operations. The Dreadnode Platform supports persistent sessions across web and terminal, with search of past work and sharing with a team. Dreadnode Platform workflows coordinate agents by sequencing tasks, running work in parallel, and branching or combining results. The Dreadnode Platform connects existing command-line tools, MCP servers, and custom integrations. Versioned capabilities on the Dreadnode Platform can be shared with their instructions, tools, and dependency setup.^[4]

Dreadnode Platform agents carry saved project context into new sessions and retrieve findings from earlier work. Dreadnode Platform users can review structured findings and assets with supporting evidence and relationships. The Dreadnode Platform versions and reuses datasets across evaluations, optimization, and training. Dreadnode Platform users can post-train models with demonstrations or rewards and retain the resulting model artifacts.^[4]

Dreadnode combines task evaluations, LLM judges, and AI red teaming so a team can set the criteria for greater responsibility. Dreadnode Platform evaluations benchmark agents against published security tasks and a team's own tasks and environments. Dreadnode uses LLM judges to assess correctness, scope adherence, and signs of cheating against a team's criteria. The Dreadnode Platform probes models, applications, and deployed agents with adversarial attacks across supported languages and modalities. The Dreadnode Platform compares models, prompts, and capability versions with per-sample results and judge reasoning.^[3][4]

Dreadnode Platform observability follows active agent sessions with live progress, metrics, and logs. The Dreadnode Platform inspects nested model and tool calls with their arguments and results. Dreadnode Platform traces connect findings back to the execution that produced them. Dreadnode Platform users can query traces to investigate failures and compare latency, token usage, and cost. Runtime policies in the Dreadnode Platform restrict tool access and check proposed actions against scope, and they allow, block, or request approval.^[4]

Dreadnode offers AI red teaming across AI systems in production today, from traditional machine learning models to multi-agent systems. Dreadnode offers web application penetration testing with 83 attack technique playbooks. Dreadnode describes an autonomous pentester with a built-in headless browser and 84 skills. Dreadnode agents run network discovery and Active Directory assessments, connected to attack-path analysis and C2 tools. Dreadnode's authored capabilities cover web, AI, network, reverse engineering, and forensics.^[2][3][4]

Dreadnode can be deployed on a customer's infrastructure, with application records, execution evidence, and capability artifacts in data stores the customer controls. Dreadnode runs on an existing Kubernetes cluster or on an embedded cluster on a dedicated VM, and offline installation bundles support air-gapped deployments. Dreadnode routes inference to approved providers or to models a customer hosts itself. Dreadnode offers on-prem deployment with the Enterprise plan. Dreadnode states that all evaluation, training, Worlds, and AI red teaming data stays within a customer's organization environment. Dreadnode SaaS meters workloads against a shared organization credit balance. Dreadnode stores secret values without returning them in normal API reads and injects them only into the remote runtimes and evaluations a user selects.^{[3][4][5][6][7]}

Dreadnode treats organizations as an ownership boundary, and workspaces as the main collaboration boundary inside an organization. In SaaS mode, creating or updating workspaces on Dreadnode requires a Pro plan or higher. Dreadnode is SOC 2, ISO 27001:2022, and ISO 27701 compliant. Dreadnode charges a one-time annual fee that varies based on deployment requirements, SLAs, and custom work. Dreadnode built an initial suite of ER-Spatial security tasks during a cyber eval engagement for a tier 1 frontier model provider.^{[3][4][5][8][9][10][11]}