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Hold on to your firewalls, because the bad guys aren’t just coming for your code anymore, they’re targeting your words. With the rise of SaaS platforms powered by Large Language Models, a new and unsettling frontier of cybersecurity is emerging: natural language exploits. This phenomenon will redefine the threat landscape, making exploitation more accessible than ever. We’ll explore natural language vulnerabilities, why they’re dangerous, and what solutions will reshape how we approach cybersecurity.<h3>The Rise of Natural Language Vulnerabilities</h3>Traditional cybersecurity exploits typically rely on vulnerabilities in code: bugs, misconfigurations, or other technical flaws that require a certain level of expertise to exploit. Natural language exploits, however, take a fundamentally different approach. They leverage the inherent complexity of human language, exploiting tone, ambiguity, and context in ways that LLM-powered systems fail to anticipate. What makes these vulnerabilities particularly dangerous is the low barrier to entry. Exploiting them doesn’t require technical expertise; anyone who can type a carefully worded sentence is a potential threat actor. Whether it’s bypassing content filters or manipulating LLM responses, the possibilities are as vast as the nuances of language itself. <h3>Why Traditional Defenses Fall Short </h3>Rule-based firewalls and traditional cybersecurity tools struggle with the complexity of natural language, which is dynamic and context-dependent, unlike strictly structured code. For example, a seemingly benign sentence could mask harmful intent, slipping past a rule-based system undetected. These shortcomings demand a paradigm shift in how we think about cybersecurity in the age of LLMs.<h3>Advanced Solutions: The Next Generation of Defense</h3>To counter natural language exploits, the cybersecurity industry must focus on NL firewalls, a new way of leveraging language understanding to detect and mitigate malicious content. Here are two key approaches we use at IAMONES: Fine-Tuned LLMs for Content Classification This solution involves fine-tuning large language models specifically for content classification tasks. By training these models on datasets rich in malicious and benign language examples, they can learn to recognize subtle indicators of exploitation, such as manipulative phrasing or contextually inappropriate responses. A notable example of this approach is <a data-mce-href="https://ai.meta.com/research/publications/llama-guard-llm-based-input-output-safeguard-for-human-ai-conversations/" href="https://ai.meta.com/research/publications/llama-guard-llm-based-input-output-safeguard-for-human-ai-conversations/" title="**Llama-Guard**" target="_blank" rel="noopener" data-mce-selected="inline-boundary">﻿Llama-Guard</a>, a fine-tuned LLM developed by Meta designed to safeguard human-AI interactions by monitoring input and output for malicious or unsafe content. Encoder-Only Transformer Models While decoder-only architectures dominate the LLM landscape, encoder-only Transformer models (such as BERT) can be a more efficient alternative for classification tasks. These models are optimized for understanding input text and are particularly well-suited for detecting and categorizing malicious content with high precision.<h3>A Sentence as a Weapon</h3>We’ve entered an era where a well-crafted sentence can act as a weapon. Whether it’s convincing an LLM to leak sensitive information, bypass restrictions, or produce harmful content, the potential for harm is significant. But while the risks are real, so are the solutions. By embracing a multi-faceted approach to cybersecurity, we can effectively address the challenge of natural language exploits. The age of natural language vulnerabilities is here, but we are not powerless.

The New Frontier of Cybersecurity: Natural Language Exploits

<h2>NIS2, Third Party Risk, IAM: Connecting dots and DOCS</h2>Third-party risk management is vital for compliance with NIS2. NIS2, as well many other regulations such as DORA, expands its scope to include more organizations and enforces stricter requirements for managing supply chain risks. Third-party identities, especially those of IT consultants, differ from traditional employee identities. While employees follow predictable patterns tied to job roles and HR systems, IT consultants are dynamic, wearing multiple hats, accessing diverse systems, and posing varied risks.<h3>Core Questions for Third-Party IAM</h3>1. Role Clarity:<ul style="list-style-type: circle;" data-mce-style="list-style-type: circle;"><li>Who are the IT consultants?</li><li>What are their tasks and deliverables across projects?</li><li>Which data and IT resources do they access?</li></ul>2. Risk Assessment:<ul style="list-style-type: circle;" data-mce-style="list-style-type: circle;"><li>How are consultants scored or assessed for risk?</li><li>Have any of them been involved in security incidents, such as credential leaks?</li></ul>3. Data Source Integration:<ul style="list-style-type: circle;" data-mce-style="list-style-type: circle;"><li>Where and how is critical information (like project roles, permissions, and risks) captured?</li><li>Can this data be easily extracted and used for compliance and decision-making?</li></ul><h3>The IAMONES Solution</h3>IAMONES brings an innovative approach by leveraging a fine-tuned Large Language Model (LLM) integrated with Retrieval-Augmented Generation (RAG) to address these challenges. Here's how: Unlocking Natural Language InsightsDocuments such as Statements of Work (SoW), Data Processing Agreements (DPA), and Project Documents often hold the key to answering identity-related questions. With IAMONES:<ul style="list-style-type: circle;" data-mce-style="list-style-type: circle;"><li>Document Analysis: The system extracts actionable insights from unstructured text. </li><li>Conversational Queries: Natural language queries like "Who is working on X?"; or "What permissions does Y have?"; are resolved with precision.</li></ul>Enhanced TPRM Through Identity Intelligence <ul style="list-style-type: circle;" data-mce-style="list-style-type: circle;"><li>Comprehensive Consultant Tracking: Understand each consultant's roles, data access, and permissions.</li><li>Real-Time Risk Scoring: Leverage document-derived insights to assess risk dynamically.</li></ul><strong style="font-family: var(--head-fontFamily); font-size: calc(32px * var(--head-fontSize, 1)); font-style: var(--head-fontStyle, normal); background-color: rgba(249,250,251,var(--tw-bg-opacity));" data-mce-style="font-family: var(--head-fontFamily); font-size: calc(32px * var(--head-fontSize, 1)); font-style: var(--head-fontStyle, normal); background-color: rgba(249,250,251,var(--tw-bg-opacity));">Key Benefits1. Efficiency: Eliminate manual processes by automating document analysis and identity verification. 2. Risk Reduction: Proactively address supply chain risks by identifying vulnerabilities in third-party access and credentials. 3. Regulatory Compliance: Ensure adherence to emerging standards with real-time insights and robust documentation.

NIS2, Third Party Risk, IAM: Connecting dots and DOCS

<h2>Key Features of IAMONES</h2>Recently, NetBR hosted a webinar in collaboration with IAMONES. The event focused on IAMONES' capabilities. Our CEO, Andrea Rossi, shared insights and demonstrated the power of our platform. IAMONES platform, powered by Large Language Models, can augment any IGA solution, where the User Interface is a Conversational Chatbot and the Configuration (rules, workflows, security policies, etc.) is done using Natural Language, not code.Watch the webinar to learn more about IAMONES:<figure id="figure-oqage0dr6pm415ly9r"><iframe id="oqage0dr6pm415ly9r" src="https://www.youtube.com/embed/FMqA2FVzx1Q" class="w-full bg-gray-100 rounded-sm md:rounded-md lg:rounded-lg" style="aspect-ratio: 16/9;" allowfullscreen="" data-url="https://youtu.be/FMqA2FVzx1Q?si=ewCkRZSKsqX4s7Ng" data-corners="default" data-fullwidth="false" data-mce-src="https://www.youtube.com/embed/FMqA2FVzx1Q" data-mce-style="aspect-ratio: 16/9;"></iframe></figure>

Showcasing IAMONES: Highlights from the NetBR Webinar

As AI and Large Language Models (LLMs) continue to evolve, the landscape of Identity and Access Management (IAM) consulting is undergoing a significant transformation. These technologies are not just automating routine tasks; they are also shifting the value proposition for IAM consultants. In this article based on a recent webinar from IAMONES with Andrea Rossi and Rob Byrne , I’ll outline my perspective on how AI will impact the future of IAM consulting and provide predictions on the roles and activities that will disappear, evolve, or emerge.<h3>Automation of Standard IAM Tasks</h3> One of the most significant impacts of AI and LLMs in IAM is the automation of routine operations. Tasks that previously required manual oversight will be handled by AI, freeing up consultants and organizations to focus on more strategic initiatives.Disappearing Activities: Routine access management tasks such as role assignments, permission approvals, and recertification campaigns will no longer require manual intervention. AI will handle these activities, making processes faster and reducing human error.Impact: This automation will drastically reduce operational workload, allowing consultants to concentrate on higher-value tasks.<h3>Easier Integration and Preparation</h3> Integration of IAM solutions is traditionally a complex and time-consuming process. However, AI will simplify this by offering suggestions and predictions, making the process more efficient and accurate.Emerging Activities: AI-powered tools will assist in access mapping, role calculations, data cleansing, and predicting permission assignments. This will reduce technical complexities and errors in IAM deployments, making it easier to integrate these systems into existing environments.Impact: Consultants will need to pivot toward guiding and overseeing AI-driven integration processes rather than performing the manual technical work themselves.<h3>Improved End-User Experience</h3> AI will completely transform how end users interact with IAM systems. Through conversational interfaces and AI-guided user assistance, interacting with IAM systems will become intuitive and seamless.Revolutionized End-User Experience: Conversational AI will allow users to interact with IAM systems using natural language, making access requests, permissions interpretation, creating and evaluating reports easier. This will significantly reduce the need for traditional user support or involvement of specialists.Impact: Consultants will focus on designing user-centric IAM environments that leverage AI, resulting in reduced support demands and more efficient user interactions.<h3>Shifting Up the Value Chain: Strategic Consulting</h3> With routine tasks automated and integration simplified, consultants can now shift their focus toward strategic areas that create real value for businesses.Evolving Roles: The future of IAM consulting will emphasize advising on security strategy, governance models, and regulatory compliance. AI will assist in real-time compliance monitoring and governance, but consultants will provide the expertise needed to tailor these solutions to business objectives.Impact: IAM consultants will play a crucial role in aligning AI-driven IAM systems with the strategic goals of the business, ensuring governance and compliance frameworks are in place and effective.<h3>Final Thoughts</h3> Time is moving on and keeping up with trends and emerging technology is and was always crucial for the consulting business. AI and LLMs are not just tools for automation - they are enablers that allow IAM consultants to move up the value chain and focus on strategic consulting.

The Future of IAM Consulting

Plain wall with text written LESS IS MORE, small amount or changes can be more effective than big changes, minimal or simplicity or essential things is better than having too much

<h3>How LLMs and RAG Make Identity Governance Simpler, Cheaper and Faster</h3>Managing identity governance has traditionally been a complex, expensive process. However, with advancements in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques, platforms like IAMONES are revolutionizing the way businesses approach Identity Governance and Administration (IGA). By leveraging AI-powered solutions, IAMONES drastically reduces costs, simplifies operations, and enhances security resilience. IAMONES simplifies identity governance with a unique principle: “Ask Anything, Configure Everything using only Your Mother Tongue.” Through conversational AI, users can manage IGA processes with natural language instructions, eliminating the need for technical expertise and cutting costs across the board. Key Advantages of IAMONES 1. UI and Reporting Configuration Efforts DOWN to ZERO<ul style="list-style-type: circle;" data-mce-style="list-style-type: circle;"><li>The platform’s user interface is entirely chatbot-based, meaning all configurations happen through natural language commands.</li><li>Reporting design efforts go to zero—users can generate reports by simply asking for the data they need.</li><li>Multilingual configuration support becomes automatic, reducing the complexity of global implementations.</li></ul>2. Configuration &amp; Support costs DOWN, Efficency UP<ul style="list-style-type: circle;" data-mce-style="list-style-type: circle;"><li>Traditional Help Desk support costs drop by 50% to 70%, as the platform's user-friendly interface minimizes the need for technical troubleshooting</li><li>The "time to right information" accelerates by 30% to 50%, making teams more responsive and efficient</li><li>Policy definition, entitlement enrichment, and workflow configuration require far fewer resources, cutting traditional configuration efforts by 30% to 40%.</li></ul>3. Security Reactivity UP<ul style="list-style-type: circle;" data-mce-style="list-style-type: circle;"><li>Security and risk controls, which once took weeks or even months to implement, can now be activated in just hours using natural language instructions.</li></ul>Seamless Integration of Structured and Unstructured Data IAMONES bridges the gap between structured data sources (like identity warehouses) and unstructured ones (such as project documents and cybersecurity reports). This capability transforms how organizations use data for identity governance. RAG ingests natural language documents in various formats (PDF, Word), allowing organizations to integrate important information into IGA processes that wouldn’t typically be captured in traditional systems. This integration enables deeper insights by combining data from multiple sources, improving overall security resilience.Augment, Not Replace: Protecting Existing Investments One of IAMONES's core advantages is that it enhances, rather than replaces, existing IAM/IGA infrastructure. For organizations with significant investments in legacy systems, IAMONES offers an LLM-powered layer that integrates seamlessly with these platforms.The Future of Identity Governance: Cheaper, Faster, and More Secure IAMONES redefines identity governance by making it faster, cheaper, and more secure. By simplifying configuration and leveraging LLM+RAG for deeper data insights, organizations can manage identity governance more efficiently and adapt quickly to emerging threats—all while preserving existing investments."Ask Anything, Configure Everything using only Your Mother Tongue".The future of identity governance is here, and it’s easier than ever to manage.

From a LOT to a lot LESS

AI Chatbot. Artificial Digital Brain Concepts

As Artificial Intelligence (AI) becomes more pervasive in industries like cybersecurity, identity management and data governance, the question of trust remains central. How can organizations trust that the AI solutions they use, especially in critical areas like Identity Management, will handle their sensitive data responsibly? The key to building trust in AI lies in one transformative approach: RAG (Retrieval-Augmented Generation) and the use of company documents. Let’s explore how this innovation is reshaping the trust landscape in AI.<h3>How IAMONES Leverages RAG and Company Documents </h3>At IAMONES, we’ve adopted RAG to push the boundaries of what's possible in Identity Governance and Administration (IGA). In traditional IGA platforms, implementing risk policies and configuring the system requires manual configuration and deep technical expertise. Current platforms often rely on complex rule-based engines, technical jargon, and predefined workflows, making them inaccessible to non-technical stakeholders. However, with the integration of Large Language Models (LLMs) and RAG, IAMONES has transformed this process by enabling natural language interactions, simplifying the complexity of identity management. Here’s how IAMONES is innovating the space with RAG:1. Natural Language Configuration: Instead of configuring risk policies through cumbersome interfaces, IAMONES allows users to define and implement these policies using everyday language, just in a document;2. Dynamic Risk Assessment: IAMONES leverages RAG to perform dynamic risk assessments based on the latest information available in company records and security reports.By combining the capabilities of LLMs with context-specific data retrieval through RAG, IAMONES provides a transformative solution for organizations seeking a more intelligent, intuitive, and transparent approach to identity management.

How can we trust AI?

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