Embrace GenAI while mitigating security risks
Generative Artificial Intelligence (GenAI) is rapidly transforming industries, and organizations are increasingly integrating Large Language Models (LLMs) into their services and products. Whether using off-the-shelf models, customizing pre-trained solutions, or developing proprietary AI, the transformative power of these technologies is undeniable.
While GenAI should be recognized and embraced as a game-changer for business innovation, it’s essential to be aware of the potential cybersecurity risks beyond the hype.
We see the majority of cybersecurity risks stemming from how AI models are integrated into systems and workflows rather than from the models themselves.
Failing to address these risks can expose your organization and customers to various threats, including data breaches, unauthorized access, and compliance violations.
We can help you address the practical risks associated with integrating GenAI into enterprise systems and workflows. As a leading cybersecurity assurance testing company, we have extensive experience in helping organizations navigate the complexities of adopting new technologies such as GenAI and LLMs.
Common pitfalls in the use of GenAI
Practical risks associated with GenAI don’t exist in isolation but are mostly related to the context in which the organization is using it. When building GenAI and LLM integrations, it’s crucial to consider the potential security risks and implement robust safeguards from the outset.
These are the most common security pitfalls that we have identified associated with the use of AI for businesses.
Jailbreak and prompt injection attacks
Malicious actors attempt to “jailbreak” an LLM by injecting carefully crafted prompts, tricking it into executing unauthorized actions or revealing sensitive information.
Excessive agency and
malicious intent
GenAI systems with excessive agency get manipulated by attackers (via jailbreak and prompt injection attacks) causing the system to execute malicious actions and posing significant security risks.
Insecure tool/
plugin design
When tools, plugins, or integrations for LLMs are poorly designed or insecurely implemented, they can introduce significant vulnerabilities leading to unauthorized access and data breaches.
Insufficient monitoring, logging, and rate limiting
Inadequate monitoring, logging, and rate-limiting mechanisms hinder the detection of malicious activity, making it challenging to identify and respond to security incidents promptly.
Lack of
output validation
Failure to validate and sanitize the output from GenAI models can lead to the disclosure of confidential information or the introduction of client-side vulnerabilities like Cross-Site Scripting (XSS).
Ensure the security of your LLMs and GenAI solutions
Whether your organization is in the early stages of planning or developing GenAI-powered solutions, or already deploying these integrations or custom solutions, our consultants can help you identify and address potential cyber risks every step of the way.
We can support your organization in adopting and integrating AI securely by assessing the potential security flaws of the GenAI/ LLM integrations and interaction to your systems and workflows and providing recommendations on secure deployment.
Depending on your use case, the different assessment approaches may include any of the below.
Contact us to discuss the best approach for your specific case!
Governance, risk and threat modeling for AI
Our services to support you in the planning phase.
AI Governance
Defining the AI adoption objectives and acceptable use cases.
Adapting or creating ad-hoc risk management frameworks based on your organization’s needs and regulatory requirements.
AI Risk Modeling
Identifying and prioritizing security risks at an organizational and use case level.
Creating a shared risk understanding between development teams, cybersecurity, and business units.
AI Threat Modeling
Identifying the most relevant attack paths based on risk prioritization technical analysis.
Identifying control gaps and prioritizing control implementations through cost/ benefit analysis.
Implementation and integration of AI solutions
Our services to support you in the implementation phase.
Pentesting LLM Applications
Identifying and addressing the cybersecurity weaknesses in your organization’s LLM applications and integrations.
Understanding the exploit vulnerabilities of the LLM applications, the specific cyber risks they pose, and the attacker goals that will most likely lead to them being targeted.
Pentesting AI-supporting Infrastructure
Identifying high risk attack paths leading to your AI-powered applications and offering recommendations to protect these.
Ensuring secure hosting and AI-management, protecting AI data and access points.
LLM applications security canvas
Here you can download our LLM Application Security Canvas.
It condenses our battle-tested approach to help clients harness the transformative power of LLMs and safely deploy their application to production by implementing security controls at all stages of the LLM pipelines.
Click to download our LLM application security controls canvas.
We can help
We are the trusted cybersecurity partner and industry-accredited, global provider of cybersecurity assurance services, with over 30 years of experience. We understand the unique challenges that arise during the development and implementation of AI-powered solutions.
That’s why we offer comprehensive cybersecurity consulting services to support you every step of the way.
Our experienced and specialized team can help your organization leverage the full potential of AI technology while maintaining a resilient and secure infrastructure.
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