Large Language Models (LLMs), AI applications, and AI agents are creating new opportunities for organizations. Whether used in help desk systems, knowledge platforms, development assistants, or autonomous agents, AI systems process sensitive data, access internal knowledge sources, and increasingly interact with other applications and services. This creates new attack surfaces.
Challenges of AI Applications
AI systems differ fundamentally from traditional applications. Their behavior is driven by probabilistic models rather than predefined logic, and they often perform autonomous and dynamic interactions with external data sources, tools, and internal systems. As a result, they introduce risks that are often not adequately addressed by conventional security assessments.
Typical risks
- Prompt injection and jailbreak attacks
- Unauthorized access to sensitive information
- Data leakage from RAG systems and knowledge bases
- Abuse of AI agents and tool integrations
- Insecure AI platform configurations
- Weak authorization and access control models
- Circumvention of security and governance controls
Not every AI application is exposed to these risks to the same degree. However, as AI systems become more deeply integrated into business processes, the need of an independent security assessment grows.
Reasons for an AI & LLM Security Assessment
An AI & LLM Security Assessment is particularly valuable if you:
- use AI applications in production environments
- connect AI agents to internal systems
- leverage Retrieval-Augmented Generation (RAG) architectures
- process sensitive data through AI systems
- want an independent security assessment of your AI solution
At the beginning, we work closely with your subject matter experts, developers, and architects to analyze the AI solution and its integration into your existing landscape.
We will review:
- architecture and data flows
- LLMs and AI agents in use
- RAG components and data sources
- tool integrations and MCP integrations
- access control and authorization concepts
Based on this analysis, we identify potential attack vectors and develop realistic attack scenarios.
In the next phase, our experts validate the identified attack scenarios through hands-on testing and perform realistic attack simulations.
All tests are thoroughly documented and evaluated based on their potential impact.
For every identified vulnerability, we develop concrete and practical remediation measures.
The final report includes:
- description of identified vulnerabilities
- technical risk analysis
- documented attack scenarios
- prioritized recommendations for remediation
Practical Example
An internal AI-powered help desk solution answers user requests based on knowledge bases, technical documentation, and internal documents while interacting with additional applications and data sources.
As part of an assessment, we may evaluate whether:
- users can access information they are not authorized to view
- confidential content can be exposed from internal data sources
- security controls can be bypassed through manipulated inputs
- agents can be induced to perform unexpected or unintended actions
- privileges can be escalated or internal systems can be misused
Our assessment goes beyond the large language model itself. We evaluate the entire solution, including data sources, integrations, agent capabilities, and authorization concepts.
Your Benefits
An AI & LLM Security Assessment from Compass Security helps you:
- reduce risks associated with agents and tool integrations
- avoid security incidents and their financial consequences
- improve the security of business-critical processes and sensitive data
- strengthen compliance with regulatory and governance requirements
Why Compass Security
Compass Security has more than 25 years of experience in penetration testing, application security, and offensive security, combined with specialized expertise in AI and LLM security.
Our assessments are aligned with established frameworks such as the OWASP Top 10 for LLM Applications, the OWASP Agentic AI Security Guidance, and MITRE ATLAS.
Our assessments also incorporate the latest research into modern AI systems, AI agents, and AI-powerded development tools.
Proven AI Security Research Expertise
At the international Pwn2Own Berlin 2026 competition, the Compass Security team successfully identified attack paths in Anthropic Claude Code, Cursor, and OpenAI Codex in the AI Coding Agents category, achieving 4th place overall
Day One Results – OpenAI Codex Exploit
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