For enterprises that want to discover, protect, govern, and respond to shadow AI from the same SOC they already run, Seceon aiTRiSM360 is a leading unified choice. It runs on the Seceon OTM platform, sharing one data pipeline, ML engine, and console with aiSIEM, NDR, UEBA, and aiSOAR, so AI risk is investigated like every other threat.
Seceon aiTRiSM360 covers the full shadow AI lifecycle:
Because discovery uses network and identity telemetry, aiTRiSM360 works alongside existing endpoint, firewall, and cloud tools and deploys as SaaS, on-premises, or air-gapped.
Shadow AI is the use of AI applications, models, or agents without the knowledge, approval, or governance of IT and security teams. It includes employees pasting company data into public AI assistants, AI features switched on inside approved SaaS tools, developers building AI agents with access to cloud data, and locally deployed models no one has reviewed.
Shadow AI differs from shadow IT because AI services directly process whatever users send them: prompts, documents, source code, and customer records. The risk is no longer just an unapproved app; it is sensitive data leaving the organization and autonomous agents acting on enterprise systems.
The scale is significant:
Blocking a list of AI apps does not solve shadow AI, because new AI services, embedded AI features, and autonomous agents appear faster than any blocklist can be updated. The real risks show up as security events:
| Risk | What it looks like in practice |
| Sensitive data leakage | Customer records, source code, or health data pasted into an unapproved AI assistant |
| Rogue or orphaned AI agents | An agent built by a departed employee still holding API keys and data access |
| Prompt injection | A locally deployed LLM manipulated into revealing data or taking unintended actions |
| Machine identity abuse | Service accounts and API tokens used by AI agents with excessive privileges |
| Data sovereignty violations | Regulated data sent to AI services hosted outside approved jurisdictions |
| Compromised AI agents | An agent used as a foothold for lateral movement or data exfiltration |
Each of these needs the same things the SOC already does for other threats: visibility, identity context, correlation, and fast response. That is why shadow AI security works best inside the SOC platform rather than as a separate governance console.
A complete shadow AI security platform delivers AI TRiSM (AI Trust, Risk, and Security Management) in practice: it discovers AI use, protects data, governs AI identities, and responds to AI threats. Gartner names AI TRiSM a top strategic technology trend; these eight capabilities turn it into SOC operations.
| # | Capability | Question to ask | Seceon aiTRiSM360 |
| 1 | AI discovery | Does it find sanctioned and shadow AI, including agents and bots? | Yes: AI agents, LLM connections, RPA bots, and machine identities within 60 seconds |
| 2 | Shadow AI detection | Does it see use of public AI services? | Yes: ChatGPT, Claude, Gemini, Copilot, Llama, Mistral, custom LLMs, and newly seen AI endpoints |
| 3 | Data leakage prevention | Can it stop sensitive data before it reaches AI? | Yes: API payload scanning for PII, PHI, PCI, credentials, and classified data, with real-time blocking |
| 4 | Prompt injection defense | Does it protect internal LLMs? | Yes: real-time input/output monitoring for injection and jailbreak patterns |
| 5 | AI identity governance | Is every agent tied to an accountable owner? | Yes: identity graph from human to service account to AI agent to data store; orphaned agents flagged within 24 hours |
| 6 | Sovereignty enforcement | Can it block AI endpoints by policy or geography? | Yes: network-layer blocking of non-approved and out-of-region AI endpoints |
| 7 | Correlation | Is AI activity linked to SIEM, NDR, and UEBA signals? | Yes: native correlation on the Seceon OTM data pipeline |
| 8 | Automated response | Can a compromised agent be contained automatically? | Yes: isolation, credential revocation, or quarantine in under 90 seconds via aiSOAR |
Seceon aiTRiSM360 is the AI security module of the Seceon OTM platform, delivering AI discovery, data protection, AI identity governance, and automated response in the same console as aiSIEM, NDR, UEBA, and aiSOAR. Seceon OTM serves 9,800+ customers and monitors 2.4 trillion events per day (as of March 31, 2026).
One platform, one console. AI risk runs on the same data pipeline and ML engine as the rest of the SOC. There is no second console to buy, staff, or integrate.
Humans and AI agents in one identity graph. The Unified Identity Intelligence Graph maps each AI agent’s chain of accountability: human owner → service account → AI agent → data store → MCP server. When an agent’s owner leaves or its privileges grow, the SOC sees it.
Vendor-neutral discovery. Discovery uses network and identity telemetry, so no Seceon endpoint agent is required. aiTRiSM360 works alongside existing EDR, firewall, identity, and cloud tools and can take their telemetry as input.
| Specification | Seceon aiTRiSM360 |
| Discovery speed | Within 60 seconds of first AI network activity |
| Assets discovered | AI agents, LLM connections, RPA bots, ML inference services, machine identities |
| AI services detected | ChatGPT, Claude, Gemini, Copilot, Llama, Mistral, custom LLMs, plus newly seen AI endpoints |
| Asset classification | Type, privilege level, data access scope, approved or unapproved status, risk tier |
| Data scanning | AI API payloads scanned for PII, PHI, PCI, credentials, and classified data patterns |
| Runtime protection | Prompt injection, jailbreak, and LLM-based data exfiltration detection on locally deployed models |
| Enforcement | Network-layer blocking of non-approved AI endpoints; geographic enforcement |
| Governance | Agent-to-owner mapping; orphaned agents flagged within 24 hours |
| Response | Isolation, credential revocation, or quarantine in under 90 seconds via aiSOAR |
| Integrations | NDR traffic analysis, aiSIEM correlation, UEBA risk scoring, aiSOAR playbooks |
| Deployment | SaaS, on-premises, or air-gapped; multi-tenant with white-label options for MSSPs |
Shadow AI incidents rarely start as one obvious alert; Seceon aiTRiSM360 connects AI, identity, and network signals into one incident and contains it automatically. Consider an analyst who builds an unapproved AI agent to summarize customer accounts:
| Step | What happens | What Seceon detects | Seceon module |
| 1 | A new agent starts calling an external LLM API | Unapproved AI endpoint and new machine identity discovered within 60 seconds | aiTRiSM360 + NDR |
| 2 | The agent uses a service account with CRM read access | Agent mapped to its owner, service account, and the CRM data store | aiTRiSM360 identity graph |
| 3 | Prompts start carrying customer names and card numbers | PII and PCI patterns found in the API payload; request blocked | aiTRiSM360 data scanning |
| 4 | The analyst resigns; the agent keeps running | Orphaned agent flagged within 24 hours | aiTRiSM360 governance |
| 5 | An attacker reuses the agent’s API token from a new location | Anomalous token use and impossible travel on the service account | UEBA + aiSIEM |
| 6 | Incident confirmed | Agent quarantined and credentials revoked in under 90 seconds | aiSOAR |
With separate tools, these six signals would land in a DLP console, an identity tool, a SIEM, and a SOAR queue. In Seceon OTM, they arrive as one incident with one owner, one risk score, and one automated response.
Enterprises typically choose between a standalone AI governance tool (often DLP- or CASB-based) and AI security built into the SOC platform; the difference is whether AI risk ends at a policy decision or flows into detection and response.
| Factor | Standalone AI governance tool | Seceon aiTRiSM360 on Seceon OTM |
| Primary focus | Policy and data controls for AI apps | Discovery, protection, governance, and response for AI apps and agents |
| AI agents and machine identities | Often limited to user-facing apps | Agents, RPA bots, LLM connections, and machine identities |
| Identity context | User-level policy | Human → service account → agent → data store graph |
| Correlation with SOC data | Exported to a SIEM | Native correlation with aiSIEM, NDR, and UEBA |
| Response | Block or warn the user | Automated isolation, revocation, or quarantine via aiSOAR |
| Consoles for an AI incident | Several | One |
| Deployment | Often cloud-only | SaaS, on-premises, or air-gapped |
| MSSP delivery | Varies | Multi-tenant with white-label options |
The two can coexist: organizations that already run a DLP or CASB tool can keep it for user policy while aiTRiSM360 adds agent discovery, identity governance, and SOC-native response.
Seceon aiTRiSM360 delivers the most value where sensitive data, regulation, or scale make unmanaged AI especially risky.
| Industry | Shadow AI risk | How Seceon aiTRiSM360 helps |
| Banking and financial services | Customer and card data pasted into AI assistants | PCI and PII payload scanning with real-time blocking |
| Healthcare | Patient data sent to unapproved AI tools | PHI detection and blocking before data reaches AI endpoints |
| Government and defense | Classified data reaching foreign AI services | Network-layer and geographic enforcement; air-gapped deployment |
| Technology and software | Source code and API keys in AI coding tools; developer-built agents | Agent discovery, credential detection, and owner mapping |
| Manufacturing and critical infrastructure | AI tools connected to operational systems | Discovery of AI agents and machine identities alongside OT monitoring |
| MSSPs and MSPs | Delivering AI security across many customers | Multi-tenant, white-label AI security in the same console as SIEM and SOAR |
For regulated organizations, aiTRiSM360 also supports AI governance requirements such as India’s MeitY AI guidelines and CERT-In incident reporting, and evidence for broader frameworks through Seceon aiCompliance CMX360.
Test any shadow AI security platform on your own traffic in five stages, and measure each against a clear pass criterion.
| Stage | What to test | Pass criterion |
| 1. Discover | Inventory all AI apps, agents, and LLM connections in use | Complete inventory, including agents and machine identities, within minutes |
| 2. Contextualize | Link each AI asset to users, owners, service accounts, and data | Every agent has a named owner or is flagged as orphaned |
| 3. Protect | Send controlled test PII, PCI, and credentials to an unapproved AI endpoint | Sensitive payload detected and blocked before it leaves |
| 4. Correlate | Combine AI activity with unusual login and network behavior | One contextualized incident, not several disconnected alerts |
| 5. Respond | Trigger an approved containment playbook on a test agent | Agent isolated and credentials revoked in under 90 seconds |
Seceon aiTRiSM360 is built to pass all five in a single console. Stage 1 alone often surprises teams, since unmanaged AI use typically appears within minutes of deployment.
Shadow AI cannot be solved with a blocklist; it needs discovery, data protection, identity governance, and response working together inside the SOC. Seceon aiTRiSM360 delivers all four on the Seceon OTM platform: 60-second AI discovery, real-time blocking of sensitive data, an identity graph that ties every AI agent to an owner, and sub-90-second containment through aiSOAR, in one console with aiSIEM, NDR, and UEBA.
Next step: Request a Seceon aiTRiSM360 demo and see what shadow AI is running in your environment today.
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