Protect your AI systems and chatbots against a new generation of threats. Our AI pentest services help uncover LLM vulnerabilities, strengthen GenAI security, and ensure your organization’s information security and operations remain protected.
What is an LLM and Why is it a Security Risk?
A language model (LLM) is an artificial intelligence technology capable of processing and generating text in a human-like manner. It is widely used in chatbots, virtual assistants, process automation, and enterprise AI applications.
However, its architecture introduces new AI security risks. Unlike traditional systems, LLMs can be manipulated through attacks such as prompt injection, induced to reveal sensitive data, or exploited to access internal systems if proper security controls are not in place.
These LLM vulnerabilities make AI systems a new attack surface that many organizations are not yet properly evaluating through AI security testing or AI risk assessment processes.
What Do We Assess in an AI Pentest?
We assess the security of your LLM-based applications through a comprehensive AI pentest, taking an adversarial approach to analyze how your systems can be manipulated, exploited, or used beyond their intended purpose.
Our AI security testing simulates real-world attack scenarios to identify critical LLM vulnerabilities, including prompt injection, sensitive data exposure, control bypass, unauthorized actions, and insecure interactions with external systems and APIs.
Beyond the model itself, we evaluate the full AI ecosystem, including integrations, data flows, chatbots, and business logic, to uncover security gaps that can significantly impact your organization and require immediate AI risk assessment.
Our AI Security Testing Methodology
Our LLM penetration testing is based on internationally recognized frameworks and a practical, risk-driven approach focused on real business impact. We combine advanced AI security testing methodologies with offensive cybersecurity techniques to comprehensively assess your applications and identify critical LLM vulnerabilities.
We use the OWASP Top 10 for LLMs v2.0 (2025) as a core reference, identifying key risks such as prompt injection, data leakage, insecure output handling, and unauthorized actions in AI systems.
We complement this approach with the Secure AI Framework (SAIF), enabling us to evaluate security controls from the design phase, as well as governance, AI risk assessment, and protection of data in GenAI environments.
Additionally, we leverage ATLAS, a specialized framework focused on adversarial tactics and techniques used in attacks against AI systems, allowing us to simulate realistic and advanced threat scenarios as part of our AI pentest process.
This combination enables us to deliver AI security assessments aligned with industry standards while focusing on identifying exploitable vulnerabilities and providing actionable recommendations to strengthen your GenAI security posture.
What Do You Get?
You will gain a clear understanding of the security level of your artificial intelligence applications and the risks associated with the use of language models within your organization.
We deliver a report with both executive and technical perspectives, including detailed findings, proof of exploitation, and practical recommendations to mitigate each identified vulnerability.
Beyond a diagnosis, we provide a solid foundation to make informed decisions and continuously strengthen the security of your AI solutions.
Why Choose Kolibërs for AI Security Testing?
At Kolibërs, we understand that artificial intelligence security cannot be effectively assessed using traditional approaches. We combine deep expertise in offensive cybersecurity with a specialized focus on LLMs to deliver advanced AI security testing and AI pentest services aligned with real business risks.
Our approach enables us to identify critical LLM vulnerabilities, including prompt injection, data leakage, and insecure chatbot behavior, uncovering risks that conventional assessments often overlook.
We understand the real challenges faced by SMEs and NGOs: limited resources, high exposure, and the need for clear, actionable solutions. That’s why our AI risk assessment and GenAI security services are tailored to be practical, accessible, and aligned with your specific context.
AI security risks for businessess
Businessess adopting AI face growing AI security risks, including:
- Prompt Injection Attacks
- Data leakage and privacy breaches
- Unauthorized actions by AI agents
- Exposure of internal systems
- Lack of proper AI risk assessment
Is AI penetration testing mandatory in Mexico?
Currently, there is no specific regulation in Mexico that explicitly requires AI pentesting or AI security testing for language models (LLMs). However, data protection laws such as the Federal Law on the Protection of Personal Data (LFPDPPP) require organizations to safeguard sensitive information.
In addition, international frameworks such as OWASP and NIST already address AI security risks, including LLM vulnerabilities, prompt injection, and data leakage, encouraging organizations to adopt proactive AI risk assessment practices.
If your organization uses AI systems or chatbots that process sensitive data, conducting an AI pentest or AI security assessment is highly recommended to comply with best practices, strengthen your GenAI security, and reduce the risk of data breaches or regulatory penalties.
How to secure LLM agents with API access?
LLM agents with API access introduce high-risk AI security challenges, specially around unauthorized actions.
to secure them:
- Enforce strict access controls and authentication
- Apply the principle of least privilege to APIs
- Validate and anitize all inputs (prevent prompt injection)
- Restrict what actions the model can execute
- Monitor and log all agent activity
This is a key area in AI security testing, as misconfigured agents can lead to severe business impact and data exposure.
Is my chatbot secure?
Most AI chatbots have hidden LLM vulnerabilities that are not visible without proper testing.
To determine if your chatbot is secure:
- Conduct an AI pentest
- Test for prompt injection
- Evaluate data exposure risks
- Perform an AI risk assessment
If your chatbot handles sensitive data, AI security testing is essential.
Take the next step toward securing your AI systems and reducing risk. Schedule your AI security consultation
