General Analysis
An enterprise platform that continuously attacks and monitors your company's AI chatbots and agents in production — the way a security team would stress-test any other system — to catch manipulation attempts before they cause real damage.
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Description
As companies put AI agents into production handling real tasks (customer service, data lookups, automated workflows), those agents become a new attack surface: prompt injection, being tricked into misusing a connected tool, or leaking data they shouldn't. General Analysis runs automated red-teaming campaigns against deployed AI systems — testing for jailbreaks, tool misuse, and data exposure paths using multi-step adversarial reasoning that goes beyond a single crafted prompt — and pairs that with runtime guardrails and real-time observability once the system is live.
It maps findings to recognized frameworks (OWASP, NIST AI RMF) for compliance reporting, and includes a security asset inventory to track what AI systems exist across an organization in the first place — often a gap before any testing can even start. It's aimed at enterprise security teams running AI in regulated or high-stakes sectors (financial, healthcare, legal, media), with custom pricing available only through a sales consultation.
💬 Our review
The short version: General Analysis is positioned for organizations that have moved past "did we test our chatbot once" into needing ongoing, automated adversarial testing plus live monitoring of AI systems already in production — a meaningfully bigger scope than a one-time security scan.
Compared to promptmap, the free open-source alternative covering similar automated-attack territory, General Analysis adds continuous campaigns, runtime guardrails, an asset inventory, and compliance-framework mapping — the kind of operational tooling a security team managing multiple AI deployments actually needs, at enterprise pricing to match. Against Stingrai, which blends AI testing with CREST-certified human pentesters, General Analysis leans more automated and platform-driven rather than hybrid human-AI validation.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Tarification non publiée, démonstration/consultation requise.
Pros
Campagnes de red-teaming continues, pas un test ponctuel
Garde-fous en temps réel et observabilité en production
Mapping vers OWASP et NIST AI RMF pour la conformité
Cons
Aucun tarif public, nécessite une consultation commerciale
Pensé pour des équipes sécurité d'entreprise, pas un usage individuel
Automatisé — pas de validation humaine intégrée contrairement à Stingrai