We identify critical vulnerabilities in production LLMs and AI systems that expose novel attack paths. Our threat-informed adversarial testing uncovers risks conventional tools miss and helps neutralize them before breaches occur.
Enterprise AI systems face unique vulnerabilities that bypass traditional security controls. Our tailored assessments identify and mitigate these emerging risks.
High Risk
Business impact: Intellectual property theft, compliance violations
Medium Risk
Business impact: Brand damage, unauthorized actions, policy violations
Low Risk
Business impact: Compromised decision-making, biased outputs
High Risk
Business impact: Unauthorized access, service disruption
Critical Risk
Business impact: Inherited vulnerabilities, backdoors
Security Aspect | Traditional AppSec | AI Security Assessment |
---|---|---|
Input Validation | Tests for SQL injection, XSS | Tests for prompt injection, jailbreaking techniques |
Data Protection | Focuses on database security | Evaluates model inversion, training data extraction |
Authentication | Tests user authentication flows | Tests model API authentication, rate limiting, inference controls |
Business Logic | Tests predefined logic paths | Tests emergent behaviors, hallucinations, bias exploitation |
Our modular approach adapts to your specific AI implementation, providing actionable security insights across your entire AI ecosystem.
Customer-facing AI tools, chatbots, GPT-powered interfaces
Authentication bypasses, prompt injection vulnerabilities, business logic flaws
Secure AI applications that maintain guardrails under adversarial conditions
End-to-end
testing of AI-powered applications
GPT-powered tool
vulnerability scanning
Chatbot security
assessment
Authentication
and authorization testing
LLM implementations across OpenAI, Claude, Mistral, and custom models
Jailbreak vectors, content policy bypasses, harmful output generation
Robust content filtering and improved model alignment with organizational policies
Comprehensive
jailbreak testing
Output
manipulation detection
Prompt injection
vulnerability assessment
Cross-model
security comparison
Proprietary ML/LLM models and their inference endpoints
Model extraction vulnerabilities, adversarial examples, inference attacks
Protected intellectual property and resilient model performance
Model inversion
attack simulation
Inference attack
testing
Extraction
vulnerability assessment
Evasion
technique evaluation
Data sources, preprocessing workflows, and model training infrastructure
Data poisoning opportunities, access control issues, integrity vulnerabilities
Trustworthy training processes and improved model governance
Training data
quality assessment
Data poisoning
vulnerability testing
Source
validation and verification
Hyperparameter
security review
Production LLM behavior over time through automated testing
Regression in security controls, new vulnerability patterns, emerging threats
Early detection of security drift with comprehensive security dashboards
Monthly security
testing
Response
manipulation detection
Jailbreak
attempt monitoring
Comprehensive
security dashboards
Quickly assess your AI system’s security posture with these critical questions
How a leading fintech company secured their AI systems before a major product launch.
A fintech company was preparing to launch an AI-powered financial advisor that would have access to sensitive customer financial data and make investment recommendations.
“SecureLayer7’s assessment prevented what could have been a catastrophic data breach. Their remediation guidance allowed us to launch on schedule with confidence in our AI security posture.”
— CISO, Global Fintech Company
Our AI security assessments are backed by industry certifications, strict NDAs, and a proven methodology trusted by enterprise security teams.
Our non-intrusive methodology tests AI systems without service disruption or data integrity risks.
All vulnerabilities include practical remediation steps prioritized by risk level and implementation effort.
Our testing simulates real-world attack scenarios based on documented AI security incidents and emerging threat intelligence.
“SecureLayer7’s AI Security Assessment uncovered 3 critical vulnerabilities in our LLM implementation that would have exposed customer data. Their remediation guidance helped us secure our systems without disrupting our product roadmap.”
— CISO, Enterprise AI Platform“Their methodology for testing AI systems is unlike anything else in the market. They identified subtle vulnerabilities in our model that could have led to PII exposure in patient records.”
— VP of Security, Healthcare AI CompanySecure your assessment timeline before your next AI deployment or update.