AI Introduces New Attack Surfaces at Every Layer

Challenge

AI systems are no longer confined to one model or dataset. They span layers like foundation models (like Bedrock, Claude, and OpenAI), orchestration frameworks (LangChain, Vertex AI), GPUs, embeddings, and agents that can make autonomous decisions.

Risk

Each layer adds new entry points for attackers and the elevated permissions at which AI agents operate allow attackers to cross security boundaries in seconds— creating a massive blast radius.

Solution

Sweet delivers full-lifecycle AI security from the level of the language model to agent execution in production systems. Through its unified platform, Sweet ensures continuous visibility, provides runtime intelligence, and empowers policy-based control that ensures guardrails and allows AI developers to innovate fast.

From Build to Production. From Models to Agents.

Static

Models

AIBOM

AISPM

AICPA SOC 2 compliance badge with circular design and blue color scheme.

Runtime

Agents/MCP

Control Plane‍

Red Teaming

AIDR

AWS Bedrock

Azure AI Foundry

ChatGPT Enterprise

Copilot Studio

Google Vertex AI

Microsoft 365 Copilot

Power Platform

Salesforce

Salesforce Agentforce

ServiceNow

Visibility and Protection Across Your AI Ecosystem

Models

Build an AI-BOM 
Get a complete bill of materials for your AI ecosystem. Track every model (public or fine-tuned) and dependency with full visibility into origin, version, and risk

Dashboard interface titled AI BOM listing technologies AWS Bedrock, Azure OpenAI Service, OpenAI API, and Custom with associated resource counts.

Models

Strengthen Your AI Posture (AI-SPM) 
Continuously monitor AI components for misconfigurations, exposed endpoints, vulnerabilities and policy violations.

Dashboard panel titled 'Publicly exposed workload running AI applications' showing exposure risk and sensitive data warnings, with general details, description about risks of unauthorized access, and a violations section listing recent checks with timestamps and status indicators.

Agents

Discover Every Agent
Instantly detect all AI agents running in your environment, including shadow or unmanaged ones

Diagram showing a Support Agent connected to Jira API and Owner as triggers, Diagnostics Agent and Triage Agent via A2A, and tools Slack, Snowflake, and Cursor as data sources and interfaces.

Agents

Understand What Each Agent Does
Trace every action and uncover intent across timelines and workflows. Assess the risk of your architecture, whether agents access data sources directly or via secured APIs

Comparison diagram showing two vertical workflows: one with Agent, MCP, DB; the other with Agent, MCP, API, DB.

Agents

Manage Permissions, Access Control and Auditing
Ensure agents operate with minimal permissions. Reveal the blast radius of attacks on every agents and allow for policy enforcement

Agents

Red Teaming
‍Test the behavior of your agents under adversarial conditions to expose vulnerabilities before attackers do.

A security flow diagram labeled AI-DR showing a user sending input to an agent, which passes through a shield performing prompt analysis detecting sensitive data, potential data exfiltration, with policy blocked and logged, before reaching LLM and APIs.

Agents

AIDR (AI Detection & Response)
Detect and block attacks on your AI agents, from prompt injections to hallucinations. Sweet funnels AI agent traffic through its AI Gateway to analyze the prompts and block malicious operations, making it easy to set up guardrails and policies. Sweet also brings its renowned behavioral baseline to AI agents to detect deviations and unexpected workflows.

Diagram illustrating AI-SPM with an adversarial prompt requesting all customer S3 object URLs and full paths, showing observed response with a sample S3 file path, and an agent interacting with LLM and APIs.

Runtime context + control-plane enforcement = precise, real-time protection

Fine-Grained, Per-Operation Control

Ensure authorization enforcement the moment an operation executes, not just when a token is granted.

Prevent blanket access to entire repos through precise, operational-specific permissions

Instant Attack-Chain Cut (Real-Time Operation-Level Enforcement)

Enforce policies at the operation level for each token or identity, revoking only the risky actions in real time.

Instantly block unauthorized actions without terminating the entire session.

Cooperative Protection Between Agentic AI and MCP Gateway

Link workload sensors with the MCP Gateway for contextual enforcement

Traditional gateways see traffic, not intent. In Agentic AI, intent happens inside the MCP.

True least-privilege enforcement and smaller blast radius.

Real-time containment without disrupting valid workflows.

Know every model. See every agent. Control every action.

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Sweet Security is redefining enterprise cloud protection. As the leading provider of Runtime CNAPP and AI Security solutions, Sweet unifies runtime context with advanced AI intelligence to protect the modern enterprise.

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AI Security Platform (AISP)

AI Introduces New Attack Surfaces at Every Layer

From Build to Production. From Models to Agents.

Visibility and Protection Across Your AI Ecosystem

Models

Models

Agents

Agents

Agents

Agents

Agents

Runtime context + control-plane enforcement = precise, real-time protection

Know every model. See every agent. Control every action.