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AI / LLM Security Audit
Navigating the complex AI threat landscape with
expert-led, multi-layered security evaluations that safeguard your GenAI deployments with
precision-driven VAPT.
100+
AI Models Tested
92%
Vulnerability Rate in Prompt Manipulation
30+
Attack Scenarios
Our AI / LLM Security Approach
Our approach provides a structured and defensible framework for
evaluating the security of AI driven systems. It helps organizations understand risk, validate security
controls, and strengthen trust without disrupting business operations. Aligned with enterprise security
expectations and evolving threat landscapes, the approach enables consistent and repeatable security
assurance across AI environments.
OWASP
LLMMITRE
ATLASNIST
AI RMF
1. Reconnaissance & Asset Mapping
Identify AI components, data flows, and integration points across your AI ecosystem, including APIs,
model endpoints, and training pipelines. We create comprehensive inventories of your AI
infrastructure to ensure nothing escapes scrutiny.
2. Threat Modelling & Attack Surface Analysis
Leverage OWASP GenAI Top 10 and bespoke AI risk frameworks to pinpoint critical vulnerabilities
specific to LLMs and AI agents. Our analysis reveals hidden exposure points unique to generative AI
architectures.
3. Adversarial Testing & Exploit Simulation
Execute targeted prompt injection, data poisoning, and model manipulation attacks to simulate
real-world adversarial scenarios. We think like attackers to uncover exploits before malicious
actors do.
4. Reporting, Remediation & Continuous Monitoring
Deliver actionable mitigation strategies and integrate AI specific continuous threat exposure
management for evolving risk landscapes. Our partnership extends beyond testing to ongoing
resilience.
AI / LLM Attack Surface – Layered Vulnerabilities Explored
AI-powered systems introduce multiple attack surfaces that extend beyond traditional applications.
Security risks can emerge at different points across user interaction, model behaviour, data handling,
and operational infrastructure. Our assessment looks at these layers to understand where weaknesses
exist and how they can be exploited.
01 Application & Interface Layer
Application & Interface Layer (User Entry Points)
This is where users and systems interact with the AI through chat interfaces, applications,
APIs, and session-handling mechanisms. Since all inputs pass through this layer, it is often
the first target for manipulation and unauthorized access.
LAYER VULNERABILITY VECTORS
Prompt Injection INPUT
Jailbreaking BYPASS
Indirect Prompt Injection CONTEXT
Context Manipulation STATE
Interface Access Control Issues AUTH
02 Model & Logic Layer
Model & Logic Layer (Decision Engine)
This layer represents the core intelligence of the system, whether it is a proprietary model,
a fine-tuned open-source model, or a third-party LLM. The model’s internal logic and system
instructions determine how inputs are interpreted and responses are generated.
LAYER VULNERABILITY VECTORS
Model Extraction THEFT
System Prompt Disclosure LEAK
Model Denial of Service DOS
Hallucination Exploitation LOGIC
Bias Manipulation OUTPUT
03 Data & Training Layer
Data & Training Layer (Knowledge Supply Chain)
Model behavior is shaped by the data used for training, fine-tuning, and retrieval. This
includes datasets, validation pipelines, and vector databases. Weaknesses in data handling
can directly affect accuracy, reliability, and security.
AI systems operate within broader environments that include cloud infrastructure, APIs,
plugins, and external services. As systems gain the ability to take actions, securing
integrations and access boundaries becomes critical.
LAYER VULNERABILITY VECTORS
Excessive Agency & Plugin Abuse AGENCY
Supply Chain Vulnerabilities SUPPLY
Cloud Environment Pivoting PIVOT
Insecure Infra Configuration CONFIG
Benefits of Our AI/LLM Audits
1. Uncover Hidden AI Specific Vulnerabilities
Detect subtle attack vectors invisible to conventional security tools, including zero day prompt
exploits and model manipulation techniques that standard scanners miss entirely.
2. Enhance Trust & Compliance
Align with emerging AI governance frameworks and OWASP GenAI security standards to meet regulatory
and ethical requirements whilst demonstrating due diligence to stakeholders.
3. Reduce Risk of AI-Driven Business Disruption
Prevent costly data leaks, reputational damage, and operational failures caused by adversarial AI
attacks that could undermine your competitive advantage and customer confidence.
4. Continuous, Adaptive Security Posture
Move beyond periodic testing with AI-tailored continuous monitoring and threat exposure management.
Our approach evolves with your AI systems and the threat landscape.
5. Expertise in Cutting-Edge AI Threats
Benefit from penetration testers trained in attacker mindset for AI, combining technical exploits
with strategic kill-chain simulations informed by real world incident analysis.
Get your bSAFE Score
bSAFE provides a comprehensive maturity score for your web application security, aligning with OWASP ASVS standards to guide improvements and ensure continuous security enhancement.
Initial Assessment
After Reassessment
Your Overall bSAFE Rating
Fragile
ExtremeSafe
Your initial assessment identified a Fragile security posture, requiring strategic remediation.
Understanding the bSAFE Model
Detailed Analysis
Key Remediation Steps
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