AI Security
Assurance & Evidence.
Turn AI security claims into defensible, audit-ready engineering evidence. We produce the concrete telemetry, control verification matrices, and testing artifacts needed to satisfy enterprise procurement, board committees, and regulatory standards.
"Turn AI security requirements into engineering evidence."
We produce cryptographic traces, test telemetry, and control verification matrices that stand up to enterprise scrutiny.
Independent Framework Alignment
Explore how Navira Security's technical testing directly maps against the primary global AI risk and governance standards:
OWASP Top 10 for LLM & GenAI Applications
8 Key Technical Controls MappedThe industry-standard taxonomy for core security vulnerabilities affecting Large Language Model architectures.
Prompt Injection & Context Hijacking
Direct and indirect prompt injection compromising model reasoning or overriding system policy.
Multi-turn automated and manual injection batteries across user prompts and retrieved RAG context.
Payload traces, prompt divergence logs, and mitigation boundary validation.
Sensitive Information Disclosure
Unintended exposure of PII, internal proprietary code, training secrets, or system prompts in model outputs.
Semantic probe batteries, membership inference attacks, and system prompt extraction sequences.
Data leakage verification transcripts and regex/semantic filter validation logs.
Supply Chain & Third-Party Model Vulnerabilities
Compromised base models, fine-tuned weights, prompt templates, or third-party agent plugins.
Component dependency scanning, fine-tuning artifact validation, and plugin capability auditing.
Third-party AI component BOM (Bill of Materials) and provenance verification records.
Data & Model Poisoning
Adversarial data introduced into training datasets, fine-tuning corpora, or RAG vector indexes.
Poisoned document ingestion testing and semantic boundary integrity evaluation.
Vector search divergence logs and retrieval poisoning exploit traces.
Improper Output Handling & Injection
Unsanitized model outputs passed directly to backend interpreters, browsers (XSS), or SQL engines.
Downstream execution fuzzing, client-side XSS injection, and SSRF payload triggering.
Downstream interpreter execution logs and sanitization verification.
Excessive Agency & Unsafe Tool Execution
Granting AI models broad write access, unverified tool execution, or excessive permissions without human gates.
Autonomous tool escalation simulations, parameter tampering, and boundary bypass tests.
Tool call execution traces and dual-token authorization verification records.
System Prompt Leakage
Extraction of proprietary system prompts, business rules, or internal guidance via adversarial elicitation.
Context boundary probing, token smuggling, and linguistic roleplay extraction.
System prompt defense verification logs and canary token test reports.
Vector & Embedding Weaknesses
Adversarial embedding inversion, cross-tenant vector bleed, and metadata predicate tampering in vector stores.
Nearest-neighbor semantic clustering attacks and cross-tenant namespace probing.
Vector partition verification reports and database query filter audits.
Assurance Deliverables & Audit Packs
Designed to arm enterprise sales teams and satisfy third-party auditors with technical rigor:
Engagement Parameters
Related Technical Research
Explore research and reference labs connected to this security discipline:
Scope Your AI Security Engagement
Configure your production AI architecture to calculate recommended testing depth, duration, and Founding Deal pricing.