LLM & AI Audits
AI and LLM systems power chatbots, enterprise platforms, and SaaS workflows, introducing security risks that traditional testing does not cover. Attackers can manipulate models using prompt injection, extract sensitive data, or abuse AI capabilities. Our LLM & AI Security Audits evaluate model inputs, outputs, data handling, and integrations to identify vulnerabilities that could expose confidential information or allow malicious manipulation. We also review deployment controls and governance to ensure AI systems remain secure and reliable.
Engagement Snapshot
A quick view of scope, timeline, and deliverables. Coverage and depth are tailored to your architecture and risk profile.
Timeline
14-21 Business Days
Focus Areas
4 coverage points
Deliverables
4 report assets
Timeline
14-21 Business Days
Key Focus Areas
Deliverables
Methodology Overview
We combine AI threat modeling, prompt injection testing, output analysis, and data leakage assessment with deployment security reviews.
Our Methodology
We follow a systematic, multi-phased approach to ensure every vulnerability is identified, verified, and reported with actionable remediation steps.
AI Threat Modeling
Identifying AI-specific attack vectors and risks
Prompt Injection Testing
Evaluating resistance to malicious prompt manipulation
Output Analysis
Reviewing outputs for unsafe or sensitive content
Data Leakage Assessment
Testing for exposure of confidential training data
Deployment Review
Assessing API access controls and infrastructure security
Frequently Asked Questions
Q.Why do AI systems require security audits?
AI systems generate dynamic outputs based on user input, creating new attack surfaces that traditional testing does not cover.
Q.What is prompt injection?
Prompt injection is an attack technique where malicious instructions are embedded in user inputs to manipulate AI behavior or expose restricted data.
Q.Do AI audits include API security testing?
Yes. AI systems typically depend on APIs and backend services, which are included in the assessment.
Q.Who should perform AI security audits?
Organizations deploying AI chatbots, AI assistants, or LLM-based applications should perform regular security assessments.
Common Vulnerabilities Covered
We test for the full spectrum of modern security threats, ensuring your assets are resilient against real-world exploits.
Prompt Injection
Malicious prompts manipulating AI behavior
Training Data Leakage
Exposure of sensitive training information
Model Misuse
Unintended or harmful use of AI capabilities
Privacy Risks
Potential exposure of user or system data
Missing Governance Controls
Lack of monitoring and policy enforcement
Ready to bulletproof your application?
Our experts are ready to perform a comprehensive security assessment tailored to your needs. Get started today and secure your digital assets.
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