Alert AI – Gen AI, Agentic AI security platform & services – 1
INTEROPERABLE, END-TO-END, EASY TO DEPLOY AND MANAGEALERT AI | GEN AI, AGENTIC AI, & DATA SECURITY PLATFORM MADE FOR ENTERPRISESecurity platform for Generative AI applications Alert AI GenAI &Agentic AI security platform Services AI Visibility and AI Asset Access Usage Analytics Tracking and Lineage Analysis Adversarial ML Detections in AI Footprint Alert Engine Data [...]
Layers of GenAI Apps, AI Agents with Data integrations
Layers of GenAI Apps, AI Agents with Data integrations AI/ML stacks refer to the layers of technologies and tools used to build, deploy, and manage AI/ML models. Key components include: Data Layer: Tools for data collection, storage, and preprocessing (e.g., databases, data lakes, ETL tools). Feature Engineering: Tools and frameworks for transforming raw data […]
Data Poisoning: Understanding Spills, Leaks, Contamination in AI Pipelines
Understanding Data Poisoning: Data Spills, Leaks, Contamination in AI Pipelines And, Detection and Alerts from Data Curation to Data Lineage, And Adversarial Data attacks. Data breaches have been significantly increasing. Records of confidential Data prior to the digital period were prone to security breach through hardcore in person theft. With the evolving digital world, […]
Prompt Security and Risk detection strategies in LLM application security
Prompt security and Tokenizer security Tokenizer manipulation attacks Adversaries can modify tokenizers configuration to corrupt the output of the model Recommendations Tokenizer manipulation Detection Versioning tokenizers Auditing tokenizers Logging In Large language models (LLMs): 1. Prompts are passed through Tokenizer 2. Tokenizer creates an array of token IDs a list of integers 3. LLM outputs [...]
Breaking down Vulnerabilities in Generative AI Applications and Strategies for Risks
Generative AI Vulnerability Database An GenAI vulnerability database is a repository that catalogs known vulnerabilities and security issues in Generative AI applications. These databases help researchers, developers, and organizations to: Identify Common Vulnerabilities: Understand frequent weaknesses in AI systems, such as data poisoning, adversarial attacks, and model inversion. Mitigate Risks: Implement best practices […]
Retrieval Augumented Generation (RAG) Model and Risks
Alerts and Risks in Generative AI applications and workflows Metric events , logs, events, traces Anomalies Vulnerabilities Risks Threats Introduction Generative AI Large language models (LLMs) are deep learning algorithms that can generate new content, such as text, images, music, or code. Using very large datasets they can recognize, summarize, translate, predict, and generate [...]
Understanding Moving parts of GenAI & Agentic AI Data environments – Turn Complexity into Clarity
Generative AI environments and ML systems and Data integration gets really complex with a lot of moving parts. What makes AI security complicated? The Answer is moving parts. Best way to secure AI is to start right now…and..see where you are. AI Environments are Complex. AI Environments are Multi-pronged. To secure AI, First need […]
GenAI Security, Agentic AI Security platform Service
GenAI and Agentic AI Security platform as Service Effective enterprise architecture practices deliver remarkable IT and business benefits. Today’s Enterprise Architectures are driving Organizations AI Transformation. A remarkable pattern of Enterprise Architecture is Architectural layers and Separation of Concerns. When it comes to Generative AI in Business, Enterprise architecture layers are Business, Data, Technology, […]
OWASP Top 10 LLM Security Measures
OWASP's Top 10 LLM risks Generative AI applications using LLM models, pose a new class of Risks and attack vector. OWASP's Top 10 LLM risks OWASP is an Open Source Web Applications Security Project has formulated the standards,methodologies and documented the Top 10 LLM model threats for organizations to adopt,conceive and acquire the [...]
Adversarial threat landscape MITRE ATLAS adversary tactics and techniques
In the emerging world of Generative AI and ML applications with Generative AI and ML Systems used to train data, craft a model and obtain model inference are open to serious security threats in the real world when exposed publicly.. The train data may relate to personal data and or confidential data of an organization [...]
