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AI / LLM Security Assessment
Assess the security of your Artificial Intelligence and Large Language Model implementations against prompt injection, data poisoning, and model evasion.
Overview
Why this assessment matters.
As organizations rapidly integrate AI and LLMs into their products, new attack vectors emerge. Our AI / LLM Security Assessment evaluates your machine learning pipelines and LLM integrations for vulnerabilities defined in the OWASP Top 10 for LLM Applications. We test for Prompt Injection, Insecure Output Handling, Training Data Poisoning, Model Denial of Service, and sensitive information disclosure, ensuring your AI systems are robust, secure, and trustworthy.
Capabilities
What we evaluate
01
Prompt Injection Testing
Attempting to bypass safety filters and manipulate LLM output via crafted inputs.
02
Data Privacy & Leakage
Assessing if the model inappropriately discloses sensitive training data or PII.
03
OWASP LLM Top 10
Comprehensive evaluation against the latest industry standards for AI security.
Methodology
Assessment phases
A structured, repeatable methodology to ensure comprehensive coverage of the attack surface.
01 - Architecture Review
Understanding how the AI/LLM is integrated, including data flows, plugins, and agents.
02 - Adversarial Testing
Crafting sophisticated prompt injections, jailbreaks, and evasion attacks.
03 - Data & Output Validation
Testing for insecure output handling that could lead to XSS or SSRF in the host application.
04 - Reporting
Detailed findings with specific guidance on implementing AI security guardrails.
Expertise
Certifications Our Experts Hold
Our security professionals hold globally recognized certifications across offensive security, application security, cloud, and infrastructure security.
Deliverables
Assessment outcomes
Safely integrate LLMs and AI features into your applications.
Prevent attackers from manipulating AI models to perform unauthorized actions.
Protect sensitive data from being leaked by conversational agents.
Ensure the reliability and integrity of AI-generated outputs.
Use Cases
Who needs this
AI Startups
Enterprises Integrating LLMs
Developers of RAG Applications
FAQ
Common questions
What types of AI models do you test?
We focus primarily on the integration and application security surrounding Large Language Models (LLMs) and conversational AI, including RAG architectures.
Can you fix prompt injection vulnerabilities?
Prompt injection is a complex problem; we provide actionable recommendations on implementing robust input validation, output encoding, and LLM guardrails to mitigate the risk.
Do you test the training process?
We can assess the data pipeline for poisoning risks, but our primary focus is usually on the runtime security and integration of the deployed model.
Discuss Your Cybersecurity Needs
Tell us about your security concerns and systems you want to protect. Our cybersecurity experts will understand your requirements, define the right assessment scope, and provide a clear proposal.
Request Assessment