Employees connect SaaS tools and AI applications to corporate credentials with no install, no managed device, and no agent to catch it. Mitiga discovers both from cloud and identity signals, then watches what each one does in runtime.
Zero-Impact Breach Prevention, in runtime.
EDR protects the endpoint. Mitiga protects everything else, cloud, SaaS, identity, AI, and third-party services.
Unsanctioned SaaS apps and AI tools are multiplying across the enterprise, connected by employees with work identities and invisible to every endpoint agent, CASB, and network proxy. Security teams can name the sanctioned list. Everything else is growing in the dark.
Endpoint agents and CASBs watch devices and managed network traffic. A SaaS app or AI tool authorized through OAuth never touches either one. The connection is identity to app, cloud to cloud.
Most enterprises have sanctioned, unsanctioned, and entirely unknown applications running at the same time. Shadow SaaS is the gap between what IT approved and what employees are actually using.
AI tools process data, record conversations, and act on instructions. A meeting transcription tool records every call it attends. Shadow AI is not just an inventory problem. It is a behavioral risk that compounds with every adoption.
Both spread through identity. Both bypass endpoint and CASB controls. But they behave differently after the grant, and both require continuous monitoring to understand the actual exposure.
File sharing, project management, collaboration, and productivity tools employees connect without IT approval. Discovered only from the OAuth grants and cloud API activity they leave behind. Risk grows as permissions accumulate and tokens go unrevoked.
General-purpose assistants, meeting recorders, code copilots, and embedded AI agents that employees adopt or that operate autonomously with enterprise credentials. Unlike Shadow SaaS, these tools process and generate content from corporate data, record interactions, and in the case of AI agents, take actions. The blast radius from a single unsanctioned adoption is broader.
Shadow SaaS and AI discovery is the identification of SaaS applications and AI tools employees have connected to corporate identities without security or IT approval, found from cloud and identity signals rather than device agents.
It surfaces three categories: sanctioned apps used in unsanctioned ways, unsanctioned apps nobody approved, and applications and AI tools security teams do not yet know exist. OAuth grants and cloud API activity leave a trail no endpoint tool sees.
Discovery alone produces an inventory. Mitiga also watches what each discovered app or AI tool does after the grant: the data it reaches, the permissions it holds, the actions it takes, and when behavior changes in ways that signal active risk.
Mitiga finds shadow apps from the same signals they leave in the cloud and identity layer: OAuth grants, API activity, and the behavioral traces every connected app produces. No agents, no proxies, no configuration required.
Mitiga discovers SaaS applications and AI tools, in runtime, from OAuth grants and cloud API activity, not device agents or network proxies. It sees apps that never touch a managed laptop and AI tools that operate cloud to cloud.
After discovery, Mitiga monitors what each SaaS app does: the data it accesses, the permissions it holds, and how long its token remains valid. A low-risk app that starts behaving differently gets flagged before the exposure grows.
Mitiga surfaces AI tools employees have connected with work identities, including general-purpose assistants like ChatGPT, Claude, and Gemini, productivity AI like Microsoft Copilot and Agentforce, meeting recorders, code assistants, and embedded chatbots. It monitors the calls they make, the data they access, and the outputs they generate.
AI agents, copilots, and autonomous systems operate with their own credentials and permissions, entirely outside the view of tools built for human users. Mitiga extends behavioral detection to every non-human identity, surfacing the access patterns and trust relationships that make AI agent compromise so difficult to detect by other means.
Mitiga flags approved apps used outside their intended purpose. A sanctioned file-sharing tool exporting records it was never scoped to touch, or a sanctioned AI assistant pointed at sensitive data outside its intended use, both surface through continuous monitoring after the initial grant.
Mitiga connects discovered app activity to identity and cloud evidence, building one incident instead of an isolated inventory entry. A Shadow AI tool exfiltrating conversation data and a compromised service account accessing the same records appear as one connected attack. All activity is retained for 1,000+ days in the Cloud Security Data Lake, forensic-grade and investigation-ready.
Surface every SaaS application and AI tool connected to corporate identities, with or without IT approval.
Monitor behavior continuously after discovery so exposure is caught before it becomes an incident and causes business impact.
Correlate shadow app activity with identity and cloud evidence to confirm impact, trace the blast radius, and support investigation, disclosure, and breach prevention.
In recent deployments, Mitiga surfaced more unauthorized SaaS applications than the agent-based endpoint security already in place. Shadow SaaS and Shadow AI are identity-driven and cloud-native. They never generate a tell-tale endpoint signal.
detections in the Agentic Detection Factory, growing by hundreds monthly
days of contextualized, normalized, investigation-ready log history retained
surfaced per deployment than agent-based endpoint tools
Endpoint agents see the device an employee logs in from. CASBs watch managed proxies and known traffic patterns. Neither sees an OAuth grant made browser to app, a cloud-to-cloud API connection between two services, or an AI agent operating on credentials it was given directly. The connection never touches the managed surface these tools were built to monitor.
Posture and configuration tools check permissions and settings at a point in time. They do not watch what a connected app is doing right now, or flag the meeting recorder that has been attending executive calls for three months. An inventory of unknown apps is a starting point. Behavioral monitoring in runtime after discovery is the actual security control.
Discovery tells you the app exists. Behavioral monitoring tells you what it has been doing since you gave it access.
Mitiga discovers apps from cloud API activity and identity signals, OAuth grants tied to a work identity, cloud-to-cloud connections, and token usage patterns. It sees apps that never touch a managed device and AI tools that operate entirely in the cloud.
Shadow SaaS covers unsanctioned applications employees connect for collaboration, file sharing, and productivity. Shadow AI covers AI tools and agents, from general-purpose assistants to meeting recorders to autonomous copilots, that employees adopt without security review or that operate on enterprise data using their own credentials. The distinction matters because AI tools process and generate content from corporate data, record interactions, and in some cases take actions autonomously. The blast radius from a single Shadow AI adoption can be significantly broader.
No. An inventory tells you an app exists. Mitiga monitors behavior after discovery: the data the app accesses, the permissions it holds, and how its activity changes over time. A meeting transcription tool looks different at day one than it does after attending 400 executive calls.
Yes. Mitiga surfaces AI agents, copilots, embedded chatbots, and autonomous systems acting with their own credentials. That includes workforce AI like ChatGPT Enterprise, Microsoft Copilot, and Agentforce, and AI infrastructure like Bedrock, Vertex, and Azure AI. It monitors the calls they make, the data they reach, and the trust relationships that let them act.
Mitiga flags those too. A sanctioned file-sharing tool exporting records outside its intended scope, or a sanctioned AI assistant pointed at sensitive data it was never approved to access, both surface through continuous behavioral monitoring after the initial grant.
Discovery runs on the same identity and cloud signals that power Mitiga's ITDR. When a discovered app becomes part of an active identity attack, the discovery context and the attack timeline appear in one incident. All activity is retained in the Cloud Security Data Lake for 1,000+ days, normalized and investigation-ready, so behavioral changes and late-discovered compromise can be traced as far back as the investigation requires.
CASBs require a network proxy or agent to see app traffic. SaaS posture tools check configurations at a point in time. Mitiga discovers apps from identity signals, which means it sees OAuth-authorized tools that bypass managed network paths entirely. And unlike posture tools, Mitiga watches behavior continuously after discovery, so the app that looked safe at onboarding gets flagged when it starts doing something it has never done.
From the first OAuth grant to continuous behavioral monitoring across every connected SaaS app and AI tool, Mitiga gives your team visibility into what endpoint tools miss and the context to act before a shadow app becomes an active incident.
