SecureLayer7: AI & LLM Pentesting Services

AI-Specific Threats Require Specialized Security Testing

Enterprise AI systems face unique vulnerabilities that bypass traditional security controls. Our tailored assessments identify and mitigate these emerging risks.

Data Extraction & Leakage

High Risk

Business impact: Intellectual property theft, compliance violations

“Our assessment revealed a competitor could extract 78% of training data through carefully crafted queries”

Prompt injection & Jailbreaking

Medium Risk

Business impact: Brand damage, unauthorized actions, policy violations

“We bypassed content filters in a customer service AI, enabling potential fraud scenarios”

Model Manipulation & Poisoning

Low Risk

Business impact: Compromised decision-making, biased outputs

“We demonstrated how an insider could manipulate model outputs to approve fraudulent transactions”

Insecure AI Infrastructure

High Risk

Business impact: Unauthorized access, service disruption

“We identified exposed API endpoints allowing unlimited inference without authentication”

Supply Chain Vulnerabilities

Critical Risk

Business impact: Inherited vulnerabilities, backdoors

“We discovered third-party model components with undisclosed data handling practices”

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

Comprehensive AI Security Assessment Framework

Our modular approach adapts to your specific AI implementation, providing actionable security insights across your entire AI ecosystem.

AI Application Security Testing

Generative AI Red Team Exercises

Model Security Evaluation

Training Pipeline Security Review

Continuous LLM Security Monitoring

What We Assess:

Customer-facing AI tools, chatbots, GPT-powered interfaces

What We Find:

Authentication bypasses, prompt injection vulnerabilities, business logic flaws

Outcome:

Secure AI applications that maintain guardrails under adversarial conditions

Key Features

End-to-end testing of AI-powered applications

GPT-powered tool vulnerability scanning

Chatbot security assessment

Authentication and authorization testing

What We Assess:

LLM implementations across OpenAI, Claude, Mistral, and custom models

What We Find:

Jailbreak vectors, content policy bypasses, harmful output generation

Outcome:

Robust content filtering and improved model alignment with organizational policies

Key Features

Comprehensive jailbreak testing

Output manipulation detection

Prompt injection vulnerability assessment

Cross-model security comparison

What We Assess:

Data sources, preprocessing workflows, and model training infrastructure

What We Find:

Data poisoning opportunities, access control issues, integrity vulnerabilities

Outcome:

Trustworthy training processes and improved model governance

Key Features

Training data quality assessment

Data poisoning vulnerability testing

Source validation and verification

Hyperparameter security review

What We Assess:

Production LLM behavior over time through automated testing

What We Find:

Regression in security controls, new vulnerability patterns, emerging threats

Outcome:

Early detection of security drift with comprehensive security dashboards

Key Features

Monthly security testing

Response manipulation detection

Jailbreak attempt monitoring

Comprehensive security dashboards

AI Security Transformation

How a leading fintech company secured their AI systems before a major product launch.

The Challenge

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.

Our Approach

Conducted comprehensive AI security assessment across all five modules
Performed red team exercises against the LLM implementation
Evaluated the training pipeline for data poisoning risks
Tested model extraction and inversion attack vectors

Results

Critical Vulnerabilities7/0

Data Leakage RiskHigh/Low

Jailbreak Success Rate80%/3%

Business Impact

“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

Enterprise-Grade AI Security Expertise

Our AI security assessments are backed by industry certifications, strict NDAs, and a proven methodology trusted by enterprise security teams.

ISO 27001

SOC 2 Type II

NDA-Backed

CREST Certified

Common Questions

Will testing disrupt our production systems?

Our non-intrusive methodology tests AI systems without service disruption or data integrity risks.

How quickly can we implement findings?

All vulnerabilities include practical remediation steps prioritized by risk level and implementation effort.

Is this just theoretical or academic research?

Our testing simulates real-world attack scenarios based on documented AI security incidents and emerging threat intelligence.

Hear From Our Clients

“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 Company

AI & LLM
Pentesting Services