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.
One adversarial agent built by General Analysis persuaded 50 of 55 live customer-service bots to hand out more than $10 million in fake perks, each within minutes. The San Francisco startup, backed by Y Combinator and a $10 million seed led by Altos Ventures, runs these simulated attacks on enterprise AI agents and then hardens them with runtime guardrails. Security researcher Simon Willison cited a separate constructed attack scenario in which a Supabase database connected to the Cursor coding agent could be leaked through a single malicious support ticket. General Analysis has far less to show commercially. It names no customer publicly, and a co-founder told Axios it is targeting $2 million in revenue within 12 to 18 months.
| Description | General Analysis runs automated adversarial red teaming against enterprise AI agents and turns the findings into runtime guardrails, detection, and monitoring for models, tools, and MCP servers. | [f1] |
|---|---|---|
| HQ | San Francisco, California, USA | [f2] |
| Funding | $10M total | [f2] |
| Latest funding | Seed, $10M (April 2026) | [f3] |
| Product | What it does |
|---|---|
| Automated AI Red Teaming | Context-aware adversarial testing that maps an agent's tool and permission graphs and generates multi-step exploit chains before release. |
| Runtime Guardrails and Observability | Runtime guardrail models and monitoring that screen prompts, responses, and tool calls and watch for poisoning and drift. |
| MCP Guard | A guard that inspects and controls calls to MCP servers to protect MCP-based agents from injection and data exfiltration. |
| AI Security Asset Management | Inventories models, knowledge bases, MCP servers, and agent pipelines while scanning for prompt injection and data leaks. |
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. |
Automated AI Red Teaming maps an agent's tool and permission graphs and generates multi-step exploits, while Runtime Guardrails, MCP Guard, and AI Detection and Response screen prompts, tool calls, and MCP traffic and contain risky agent behavior. These lines are mapped to the AI Defense Matrix. [f1]
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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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.
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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.
pivot urgently
| 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. | 1/3 |
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 | About General Analysis (what the company does) | official | 2026-07-03 |
| f2 | General Analysis seed announcement (location) | official | 2026-07-03 |
| f3 | Tech Startups: General Analysis raises $10M seed (investors) | press | 2026-07-03 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | General Analysis homepage “General Analysis helps security teams adversarially test, monitor, and protect AI agents and systems in production.” | official | 2026-07-03 |
| s2 | About General Analysis (approach) “We train proprietary adversarial agents that digest a customer's runtime environment, map the full graph of tools and permissions, and generate multi-step exploits that target the seams between components.” | official | 2026-07-03 |
| s3 | General Analysis seed announcement (founding team) “Our founding team of top AI safety and security researchers has built RL infrastructure at DeepMind, trained state-of-the-art models at Jane Street, NVIDIA, and Cohere, and published leading research at top conferences, including NeurIPS, ICLR, ICML, and more.” | official | 2026-07-03 |
| s4 | General Analysis guardrails documentation “Our safety stack ships in two guard families, both trained on the same adversarial pipelines we run for production deployments. Public guards, Open checkpoints published on Hugging Face. Custom enterprise guards, Bespoke detectors we train against your policies and red-team data.” | official | 2026-07-03 |
| s5 | General Analysis MCP Guard documentation “You'll be automatically enrolled in a 30-day free trial for Guardrail Basic. No payment method required! The GA CLI and MCP Guard proxy are implemented in Python.” | official | 2026-07-03 |
| s6 | Axios: Agentic AI security startup General Analysis raises $10M “General Analysis, which helps companies safely deploy agentic AI, has raised $10 million in seed funding led by Altos Ventures, co-founder Rez Havaei tells Axios Pro. The company aims to hit $2 million in revenue in the next 12 to 18 months and then will look to raise a Series A.” | press | 2026-07-03 |
| s7 | Tech Startups: General Analysis red-team demonstration “In March, a single adversarial agent persuaded 50 live customer service bots to hand out more than $10 million in fake perks. Million-dollar gift cards. Years of free services. Anything it could extract. Each target took only a few minutes. Out of 55 systems tested, just five held the line.” | press | 2026-07-03 |
| s8 | Simon Willison: Supabase MCP can leak your entire SQL database “In this case, General Analysis identify all three components in a single MCP, the Supabase MCP. They imagine a scenario where a developer asks Cursor, running the Supabase MCP, to list the latest support tickets.” | press | 2026-07-03 |
| s9 | General Analysis raises $10M seed (location and investors) “General Analysis, a San Francisco startup building security infrastructure for agentic AI. The round included participation from 645 Ventures, Menlo Ventures, Y Combinator, and other strategic investors and angels.” | press | 2026-07-03 |
| s10 | General Analysis homepage trust probe 2026-07-03 (footer badges, /security and /trust paths, trust subdomains), no SOC 2 or ISO attestation found “Understand your AI risk.” | official | 2026-07-03 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | General Analysis homepage “General Analysis helps security teams adversarially test, monitor, and protect AI agents and systems in production.” | official | 2026-07-03 |
| s2 | About General Analysis (approach) “We train proprietary adversarial agents that digest a customer's runtime environment, map the full graph of tools and permissions, and generate multi-step exploits that target the seams between components.” | official | 2026-07-03 |
| s3 | General Analysis seed announcement (founding team) “Our founding team of top AI safety and security researchers has built RL infrastructure at DeepMind, trained state-of-the-art models at Jane Street, NVIDIA, and Cohere, and published leading research at top conferences, including NeurIPS, ICLR, ICML, and more.” | official | 2026-07-03 |
| s4 | General Analysis guardrails documentation “Our safety stack ships in two guard families, both trained on the same adversarial pipelines we run for production deployments. Public guards, Open checkpoints published on Hugging Face. Custom enterprise guards, Bespoke detectors we train against your policies and red-team data.” | official | 2026-07-03 |
| s5 | General Analysis MCP Guard documentation “You'll be automatically enrolled in a 30-day free trial for Guardrail Basic. No payment method required! The GA CLI and MCP Guard proxy are implemented in Python.” | official | 2026-07-03 |
| s6 | Axios: Agentic AI security startup General Analysis raises $10M “General Analysis, which helps companies safely deploy agentic AI, has raised $10 million in seed funding led by Altos Ventures, co-founder Rez Havaei tells Axios Pro. The company aims to hit $2 million in revenue in the next 12 to 18 months and then will look to raise a Series A.” | press | 2026-07-03 |
| s7 | Tech Startups: General Analysis red-team demonstration “In March, a single adversarial agent persuaded 50 live customer service bots to hand out more than $10 million in fake perks. Million-dollar gift cards. Years of free services. Anything it could extract. Each target took only a few minutes. Out of 55 systems tested, just five held the line.” | press | 2026-07-03 |
| s8 | Simon Willison: Supabase MCP can leak your entire SQL database “In this case, General Analysis identify all three components in a single MCP, the Supabase MCP. They imagine a scenario where a developer asks Cursor, running the Supabase MCP, to list the latest support tickets.” | press | 2026-07-03 |
| s9 | General Analysis raises $10M seed (location and investors) “General Analysis, a San Francisco startup building security infrastructure for agentic AI. The round included participation from 645 Ventures, Menlo Ventures, Y Combinator, and other strategic investors and angels.” | press | 2026-07-03 |
| s10 | General Analysis homepage trust probe, re-run 2026-07-15 (footer badges, /security and /trust paths, trust subdomains), no SOC 2 or ISO attestation found “Understand your AI risk.” | official | 2026-07-03 |
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