SaaS
Secure the AI in Your SaaS Product. Before Your Customers Ask.
Your customers trust you with their data. When AI features process that data, you need security controls that match the sensitivity. We help SaaS companies ship AI features that are secure by default.
The Challenge
AI Features Expand Your Attack Surface
Every AI feature you ship is a new surface for attackers to probe. Multi-tenant SaaS products face compounded risk when AI processes data from multiple customers through shared infrastructure.
Customer Data in AI Features
When your SaaS product uses AI features that process customer data, every tenant's data flows through shared model infrastructure. A single vulnerability could expose one customer's data to another, or to the model provider.
Multi-Tenant AI Security
AI features in multi-tenant SaaS need strict isolation. Prompt context, conversation history, fine-tuning data, and RAG document stores must be segmented per tenant. Cross-tenant data leakage through AI is a breach your customers will not tolerate.
Prompt Injection in Customer-Facing AI
If your product has a customer-facing AI assistant, chatbot, or copilot, prompt injection is a direct threat. Attackers can manipulate AI behavior to extract system prompts, access unauthorized data, or bypass application controls.
Enterprise Customer Security Requirements
Enterprise buyers run security questionnaires before purchasing. They will ask about your AI security controls, data handling practices, and compliance posture. Having audited, documented AI security practices shortens sales cycles.
How We Help
AI Security for SaaS Products
AI Feature Security Audits
We test your AI features the way attackers would. Prompt injection testing, data leakage assessment, authentication bypass attempts through AI, and abuse scenario testing for every customer-facing AI surface in your product.
Multi-Tenant AI Isolation Review
Detailed assessment of tenant isolation in your AI pipeline. We evaluate context separation, RAG document store segmentation, embedding isolation, conversation history boundaries, and fine-tuning data controls across your multi-tenant architecture.
AI Security Documentation for Sales
Audit-ready security documentation covering your AI features. We help you build the security narrative your enterprise customers need: architecture diagrams, control descriptions, risk assessments, and compliance mappings that close deals faster.
SaaS AI Security FAQ
Traditional penetration tests cover your web application and API layer but miss AI-specific attack vectors. Prompt injection, data leakage through model outputs, multi-tenant context pollution, and AI-driven authentication bypass are all risks that require specialized testing. If your product has AI features that touch customer data, a standard pentest leaves significant blind spots.
Multi-tenant AI security ensures that one customer's data cannot leak to another through shared AI infrastructure. This covers prompt context isolation (preventing one tenant's conversation history from appearing in another's), RAG document store segmentation, embedding space separation, and fine-tuning data controls. Without these controls, a single AI query could inadvertently surface another tenant's confidential data.
We test with a curated library of 200+ injection vectors covering direct injection, indirect injection through document uploads, jailbreak attempts, instruction override, role manipulation, and data extraction techniques. We test both obvious attack paths and subtle vectors like manipulated file uploads or API payloads that reach the AI through non-obvious paths in your application.
Yes. Enterprise buyers increasingly include AI security questions in their vendor security assessments. Having a third-party AI security audit report, documented AI controls, and compliance mappings directly addresses their concerns. We have seen SaaS companies use our audit reports to accelerate enterprise procurement cycles by weeks.
SOC 2 is the baseline for most SaaS companies, and AI systems fall within scope when they process customer data. Beyond SOC 2, relevant frameworks include OWASP LLM Top 10 (the industry standard for LLM security), NIST AI RMF, ISO 42001 for AI management systems, and GDPR or CCPA for data privacy. For SaaS serving specific verticals, add HIPAA (healthcare) or PCI DSS (payments).
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