All analysis was generated autonomously, without human review. Scores are analytical opinions drawn from the cited public sources, without hands-on testing. They are not audits, certifications, investment reports, purchasing advice, or evaluations of quality.
Dreadnode raises a rival's cost to build without raising a customer's cost to leave. Building infrastructure for autonomous offensive-security agents draws on specialized expertise in attacking AI systems, and the company pairs that edge with data from its Crucible challenge platform, where more than 1,600 users logged over two hundred thousand attack attempts in its published studies. What it lacks is what turns a hard product into one customers stay with. No named buyer, published attestation, or regulated-enterprise footing appears in the public record, and the pay-as-you-go tier lets a team stop paying the day it stops using the tool. The problem's difficulty and the attack-data store are genuine advantages, yet a customer can still walk away.
| Description | Dreadnode builds an infrastructure platform for security teams to build, evaluate, and deploy offensive security and AI red-teaming agents. | [f1] |
|---|---|---|
| Founded | 2023 | [f2] |
| Funding | $14M total | [f2] |
| Latest funding | Series A (2025) | [f3] |
| Product | What it does |
|---|---|
| Dreadnode Platform | Infrastructure platform to build, evaluate, and deploy security agents, with a CLI, TUI, hosted evaluations, managed sandboxes, and a capability registry of offensive skills and tools. |
| Strikes | An agent training ground focused on offensive cyber security that supplies real-world scenarios to test and evaluate security agents. |
| Spyglass | A product that paired with Strikes to form the core of the Dreadnode platform at the Series A, which the vendor named as a focus of its 2025 go-to-market push. |
| Crucible | An AI hacking sandbox where security practitioners test, learn, and build their AI red-teaming skills against hosted challenges. |
AI Defense Matrix
| Govern | Identify | Protect | Detect | Respond | Recover | |
|---|---|---|---|---|---|---|
| AI-Workload Platforms Inference servers, training platforms, vector DB platforms, and the model-loading supply chain. | ||||||
| AI Orchestration Tools Agentic orchestration tools, plus their plugins, skills, hooks, system prompts, scaffolding, harnesses, configuration settings, and MCP clients on user devices. | ||||||
| AI-Generated Code Code produced by AI tools, AI-assisted reviews, AI-generated infrastructure-as-code and tests, and vibe-coded apps that bypass CI/CD. | ||||||
| AI Gateways & Routers MCP proxies and gateways, LLM routers, outbound AI-service traffic, shadow AI egress, and model-registry traffic. | ||||||
| AI Model Model weights, fine-tuning checkpoints, model cards, registries, AIBOM, and the third-party LLMs your enterprise consumes. | ||||||
| Training Data Datasets used for training, fine-tuning, and continued learning. | ||||||
| Runtime AI Data User prompts, inference inputs, RAG content, vector DB content, persistent agent memory, and interaction history. | ||||||
| AI Agent Identities AI agents as non-human principals, plus credentials, keys, permission scopes, service accounts, and delegation chains across agents and tools. |
The Dreadnode Platform probes foundation models and agentic AI systems with attack strategies including jailbreaks and adversarial algorithms, and is mapped to the AI Defense Matrix. [f4]
How well the company can compete in its security market, scored across eight dimensions against public evidence.
| Dimension | Score |
|---|---|
| Problem Clarity How precisely the company defines its problem, with evidence the problem exists at the scale claimed. | 3/5 |
| Capability Depth How specific the technical capabilities are, with evidence beyond marketing claims such as docs, demos, and third-party validation. | 4/5 |
| Market Timing Whether the market is ready for this product, with evidence that buyers are actively seeking solutions. | 3/5 |
| Team Credibility Demonstrated domain expertise with public signals such as prior exits, publications, and industry recognition. | 3/5 |
| GTM Proof Evidence of actual traction (customers, revenue signals, partnerships) beyond stated intentions. | 3/5 |
| Funding Efficiency Whether funding matches go-to-market ambition, with signs of capital-efficient growth. | 3/5 |
| Category Clarity Whether the company creates or fits a recognizable category that buyers can quickly place in their stack. | 3/5 |
| Incumbent Defensibility How vulnerable the core value proposition is to absorption as a feature by a platform vendor. | 3/5 |
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A closer look at the company's product strategy, measuring how defensible it is against market forces and examining the eight areas behind it.
reinforce or reposition
| Dimension | Score |
|---|---|
| Value Delivery Does the product sell software as the product, or judgment, trust, or accountability with software as the delivery mechanism. | 1/3 |
| Switching Cost How expensive leaving is for a customer: data portability, integrations, learned workflows, network effects, regulatory data residency. | 2/3 |
| Compliance Moat Whether certifications, liability acceptance, or audit trails block an easy replacement. | 1/3 |
| Problem Complexity Whether the product requires ML, optimization, real-time systems, or years of specialized expertise. | 3/3 |
| Buyer Profile Whether buyers are SMB operators, mid-market IT teams, or regulated enterprises and governments with procurement gates. | 2/3 |
| Layer Whether the product is an end-user application, a platform with application features, or infrastructure other applications depend on. | 2/3 |
| Proprietary Data, Content, or IP Whether the product accumulates datasets, content licenses, or IP that a rival cannot recreate from scratch. | 2/3 |
Unlock the Full Analysis
The reasoning for the scores, the strategy deep dive, the business risks, and more. AI access comes with the purchase, so your AI tools can read the full profile too. You keep 12 months of access.
One-time purchase: $20 per profile.
UnlockReading several? Unlock the entire catalog.
| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | https://docs.dreadnode.io | official | 2026-06-24 |
| f2 | Dreadnode founding year (dreadnode.io WHOIS creation date 2023-10-06, an early-stage startup per SecurityWeek) | press | 2026-06-24 |
| f3 | FinTech Global: Dreadnode captures $14m to fortify offensive AI security capabilities | press | 2026-06-24 |
| f4 | https://docs.dreadnode.io/ai-red-teaming/ | official | 2026-06-24 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | Dreadnode: AI Infrastructure for the Security Stack “Build, evaluate, and deploy security agents with confidence.” | official | 2026-06-24 |
| s2 | Dreadnode Documentation: Build with Dreadnode “Terminal-native platform for building, evaluating, and deploying offensive security agents.” | official | 2026-06-24 |
| s3 | Dreadnode: Dreadnode Launches 2.0 “The release introduces hosted evaluations, a model training and optimization pipeline, advanced AI red teaming, capability registries, managed sandboxes, and a new visual frontend.” | official | 2026-06-24 |
| s4 | SecurityWeek: Offensive AI Startup Dreadnode Secures $14M to Stress-Test AI Systems “Dreadnode, an early stage startup specializing in offensive AI security, has raised $14 million in a funding round from an investment group that includes Decibel, Next Frontier Capital, In-Q-Tel (IQT), Sands Capital, and Indie VC.” | press | 2026-06-24 |
| s5 | FinTech Global: Dreadnode captures $14m to fortify offensive AI security capabilities “The company, co-founded by former NVIDIA AI red-team lead Will Pearce and ex-NetSPI VP of Research Nick Landers, positions itself at the forefront of offensive machine learning.” | press | 2026-06-24 |
| s6 | Dreadnode Documentation: Quickstart “Install the CLI, install the web-security capability, point it at a target you are authorized to test, and let the agent work until it produces a report.” | official | 2026-06-24 |
| s7 | arXiv: AIRTBench: Measuring Autonomous AI Red Teaming Capabilities in Language Models “The benchmark consists of 70 realistic black-box capture-the-flag (CTF) challenges from the Crucible challenge environment on the Dreadnode platform, requiring models to write python code to interact with and compromise AI systems.” | research | 2026-06-30 |
| s8 | arXiv: The Automation Advantage in AI Red Teaming “This paper analyzes Large Language Model (LLM) security vulnerabilities based on data from Crucible, encompassing 214,271 attack attempts by 1,674 users across 30 LLM challenges.” | research | 2026-06-30 |
| s9 | CyberMaterial: Dreadnode Secures $14M to Tackle AI Security “Dreadnode, an early-stage startup specializing in offensive AI security, recently secured $14 million in Series A funding.” | press | 2026-06-30 |
| s10 | Dreadnode: AI Infrastructure for Security Agents (homepage attestation probe) “AI-native security can’t happen without infrastructure” | official | 2026-07-02 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | Dreadnode: AI Infrastructure for Security Agents “Build, evaluate, and deploy security agents with confidence.” | official | 2026-07-08 |
| s2 | Dreadnode Documentation: Build with Dreadnode “Terminal-native platform for building, evaluating, and deploying offensive security agents.” | official | 2026-07-08 |
| s3 | Dreadnode: Dreadnode Launches 2.0 “Built by offensive security and AI red team operators from NVIDIA, Microsoft, NetSPI, Meta, and Cohere, Dreadnode provides the complete toolkit teams need to operationalize AI at every step of the development and deployment process.” | official | 2026-07-08 |
| s4 | SecurityWeek: Offensive AI Startup Dreadnode Secures $14M to Stress-Test AI Systems “Dreadnode, an early stage startup specializing in offensive AI security, has raised $14 million in a funding round from an investment group that includes Decibel, Next Frontier Capital, In-Q-Tel (IQT), Sands Capital, and Indie VC.” | press | 2026-07-08 |
| s5 | FinTech Global: Dreadnode captures $14m to fortify offensive AI security capabilities “The company, co-founded by former NVIDIA AI red-team lead Will Pearce and ex-NetSPI VP of Research Nick Landers, positions itself at the forefront of offensive machine learning.” | press | 2026-07-08 |
| s6 | Dreadnode Documentation: Quickstart “Install the CLI, install the web-security capability, point it at a target you're authorized to test, and let the agent work until it produces a report.” | official | 2026-07-08 |
| s7 | arXiv: AIRTBench: Measuring Autonomous AI Red Teaming Capabilities in Language Models “The benchmark consists of 70 realistic black-box capture-the-flag (CTF) challenges from the Crucible challenge environment on the Dreadnode platform, requiring models to write python code to interact with and compromise AI systems.” | research | 2026-07-08 |
| s8 | arXiv: The Automation Advantage in AI Red Teaming “This paper analyzes Large Language Model (LLM) security vulnerabilities based on data from Crucible, encompassing 214,271 attack attempts by 1,674 users across 30 LLM challenges.” | research | 2026-07-08 |
| s9 | CyberMaterial: Dreadnode Secures $14M to Tackle AI Security “Dreadnode, an early-stage startup specializing in offensive AI security, recently secured $14 million in Series A funding.” | press | 2026-07-08 |
| s10 | Dreadnode: Pricing “Pay-as-you-go for credits based on usage. No monthly fee, commitment, or recurring subscription required.” | official | 2026-07-08 |
| s11 | Dreadnode attestation probe, re-run 2026-07-15: trust/security subdomains unresolvable, /security and /trust 404, homepage free of attestation terms “Probe 2026-07-15: trust and security subdomains do not resolve in DNS; /security and /trust return HTTP 404; homepage returns HTTP 200 (sha256 96ead6f9a5490a69) with no SOC 2, ISO 27001, Vanta, Drata, or trust-center terms in its text.” | official | 2026-07-15 |
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