WitnessAI

Adversarial prompting is the deliberate crafting of inputs that push a large language model into behavior the enterprise did not intend. The model may depart from its instructions in ways that affect protected data or downstream actions. Those inputs arrive as ordinary language: a customer chat message, a shared document, an email, or a tool ... Read more » The post What is adversarial prompting? appeared first on WitnessAI .

Autonomous AI agents now call APIs, query production databases, open pull requests, and execute transactions inside Global 2000 environments. AI agent observability records what an agent did, which tools it invoked, the context and sequence of actions that produced the outcome, and who authorized the work. Audit logging preserves those records as tamper-evident evidence that ... Read more » The post AI agent observability and audit logging appeared first on WitnessAI .

The Model Context Protocol lets AI agents reach enterprise tools, and MCP authentication controls which agents can connect. The protocol has specified OAuth 2.1 for that job, but MCP server deployments have moved much faster than adoption of that specification. The result is a widening gap between what the standard requires and what production environments ... Read more » The post MCP authentication and authorization: OAuth for AI agents appeared first on WitnessAI .

MITRE ATLAS names the attack. Naming it does not stop it. Prompt injection defense depends on how quickly detections translate into runtime controls, operational response, and compliance evidence. The gap between taxonomy and response is a runtime security and workflow problem, not simply a taxonomy problem. A crafted email can poison Microsoft 365 Copilot’s retrieved ... Read more » The post MITRE ATLAS and prompt injection: Mapping the techniques to workflows appeared first on WitnessAI .

Customer-facing chatbots and autonomous agents now make commitments and take actions on an enterprise’s behalf. Those interactions may legally bind the enterprise, so they belong on the AI Steering Committee’s agenda. In one case, a tribunal held an airline liable for its chatbot’s fare advice. In another, a dealership’s assistant agreed in writing to sell ... Read more » The post LLM red teaming: how it works appeared first on WitnessAI .

Google Gemini now runs inside the Gmail summarize button and the Google Workspace side panel. It also runs in the Gemini CLI on developer laptops and in the agents enterprises build on Vertex AI. Whether Gemini is safe to use therefore depends on the tier your employee uses and what they send. The model’s permissions ... Read more » The post Is Google Gemini safe to use? appeared first on WitnessAI .

ChatGPT security is already part of daily work across many large enterprises, licensed or not. Employees summarize contracts in ChatGPT, while developers can access it from inside their IDEs. Agent mode extends that activity into connected systems, where it can browse, run code and take action. Enterprise ChatGPT governance establishes the policies that allow employees ... Read more » The post ChatGPT security: an enterprise guide appeared first on WitnessAI .

Model Context Protocol (MCP) servers give AI agents standard access to the enterprise systems where data lives, including code repositories, databases, and cloud consoles. A developer can connect one to Cursor or Claude Desktop by editing a JSON configuration file, often without a procurement step. MCP server security best practices exist because that convenience carries ... Read more » The post How to secure MCP servers: best practices appeared first on WitnessAI .

An employee asks an AI agent to investigate a customer issue. The agent retrieves internal technical context, prepares a plan of action, and attempts to send it through an external tool. The employee has permission to investigate, and the tool is available. But should an agent that has just handled sensitive customer material be allowed ... Read more » The post WitnessAI in SACR’s ARISE Market Map: Why a Unified AI Control Plane Matters appeared first on WitnessAI .

Large language models now sit at the center of daily enterprise work. Employees and developers use chat tools and copilots, while autonomous AI agents call APIs against production systems. Much of that activity happens outside the security stack that governs everything else, which is why LLM security best practices now sit on the board agenda. ... Read more » The post LLM security best practices appeared first on WitnessAI .

A single prompt can send a customer list, a source code snippet, or an unreleased financial figure to a third-party model in seconds, and most security teams have no record of it. AI data classification closes that gap. It inspects prompts, uploads, responses, and tool calls in flight, categorizes what’s sensitive, and gives security teams ... Read more » The post AI data classification: how it works appeared first on WitnessAI .