---
title: "Reports: PharosOne data on the AI security market and our research"
canonical: https://pharosone.ai/knowledge/reports
publisher: PharosOne (Agentic Mind, Inc.)
updated: 2026-10-23
license: "Open for reuse: crawling, copying, quoting, summarising and model training permitted without asking; citation of the title and canonical URL requested (see https://pharosone.ai/terms#reuse)"
cite_as: "\"Reports: PharosOne data on the AI security market and our research\". PharosOne, 2026-10-23. https://pharosone.ai/knowledge/reports"
---

# Reports: PharosOne data on the AI security market and our research

> Original PharosOne data: what 100 AI security vendors sell, what an AI agent pentest costs in 2026, which LLMs resist prompt injection, how runtime guards compare, how AI assistants choose sources, and how we audit our own numbers.

URL: https://pharosone.ai/knowledge/reports · Reports: 6 reports

Reports built on data only we hold: the market we mapped, the prices we collected, the models and guards we compared, and how our own numbers are audited and corrected. Each one names its sample and its date.

- [What 100 AI security vendors sell in 2026: 13 capabilities counted.](https://pharosone.ai/knowledge/ai-security-market-2026.md), 7 min read, updated 23 Oct 2026: A sample of 100 AI security vendors, 77 of them exhibitors at two European events: who sells guardrails, who tests agents via tools and MCP, who was acquired.
- [AI pentest prices in 2026: $3,000 autonomous tests to €20,000 agents.](https://pharosone.ai/knowledge/ai-agent-pentest-cost-2026.md), 8 min read, updated 23 Oct 2026: Dated prices from vendors' own pages: autonomous web pentests at $3,000–4,000, human tests of AI agents at €4,800–20,000, red teams and day rates.
- [Which LLMs resist prompt injection as agents: 5 models, 1,470 runs.](https://pharosone.ai/knowledge/which-llms-resist-prompt-injection-in-agents.md), 8 min read, updated 23 Oct 2026: October 2026: Claude Haiku 5.5 and GPT-6 Luna resisted best (8.8%, 11.2%, not separable), Qwen3.5-9B worst (25.2%). A third of runs unlabelled; bounds inside.
- [AI agent runtime guards compared: filters, gateways, monitors, hooks.](https://pharosone.ai/knowledge/runtime-guards-compared.md), 8 min read, updated 23 Oct 2026: What each guard sees and stops. A research prototype, not Pharos Radar, cut attack success from 18.3% to 0.1% on one agent and blocked 1.5% of clean messages.
- [How AI assistants choose sources: a four-model simulated-search pilot.](https://pharosone.ai/knowledge/how-ai-search-assistants-choose-sources.md), 8 min read, updated 23 Oct 2026: Four API models searched fixed result pools 32 times: they chose pages from title and description, cited 89% of what they opened, and flagged vendor pages.
- [Five ways AI security detection numbers mislead, from our own audit.](https://pharosone.ai/knowledge/what-we-retracted-and-why.md), 10 min read, updated 23 Oct 2026: Wrong negative population, wrong configuration, leaked labels, imputed coverage, unfixed averaging: each caught in our audit, with the question that exposes it.

Source: PharosOne, "Reports: PharosOne data on the AI security market and our research", https://pharosone.ai/knowledge/reports, updated 2026-10-23.

---

PharosOne is a product of Agentic Mind, Inc., an independent AI agent security company. Site map for agents: https://pharosone.ai/llms.txt