Manage AI Exposure

Detect and protect AI workloads running across your endpoints

Developers, teams, and entire organizations are deploying AI tools faster than security teams can see them. Spektion provides continuous runtime visibility into every AI agent, coding assistant, inference server, and AI-generated executable operating across your environment.

The Problem
14
%

Endpoints running unsanctioned AI tools

Observed in early Spektion deployments.

3-10
x

More AI workloads than security teams expect

Runtime discovery baseline across early deployments.

0
visibility

Into AI agents, MCP servers, or AI-generated executables in your current stack

VM tools, scanners, and EDR cannot detect these workloads.

0
%

Of AI runtime behavior is detected by traditional tools

No traditional tool observes what AI workloads are actually doing on endpoints.

AI risk is defined by runtime behavior, not tool names.

AI workloads are expanding your attack surface

Employees are deploying AI tools across endpoints. These workloads behave like any other software process—executing code, accessing credentials, making network requests, and running with elevated privileges.

But most security tools were never designed to understand them.

None of your existing tools can see this risk

Where AI introduces real exposure

These risks exist whether a policy allows them or not.
You can't govern what you can't see.

Dark blue empty rectangular box with rounded corners and a subtle gradient background.Dark gradient background with rounded corners.

1. Coding assistants accessing proprietary source code

2. Inference servers exposed to the network

3. MCP servers storing credentials in plaintext

4. AI agents executing commands with elevated privileges

5. AI-generated executables with no provenance or review

The Runtime Difference

You can't govern what you can't see

Without Spektion

AI runtimes invisible to your VM stack
MCP credentials in plaintext, undetected
Shadow coding assistants with no oversight
AI agents running with elevated privileges
AI-generated executables with no provenance
No governance without inventory

With Spektion

Full inventory of every AI tool and agent
Credential leakage flagged and tracked
Every coding assistant classified: sanctioned vs. shadow
Privilege context and blast radius for AI workloads
AI-generated executables observed and risk-scored
Policy enforcement starts with visibility
Visibility and control over AI risk
Spektion Capabilities

What runtime reveals about AI risk

Five capabilities delivered by the same lightweight agent. No additional deployment required.

Inventory every AI workload at runtime

Spektion continuously discovers and classifies every AI tool, agent, inference server, and model runtime across workstations, servers, and containers—giving security teams a live, always-current view of what's actually running.

A screenshot of a computer screen with a bunch of buttons.

Govern coding assistants and shadow AI

Spektion identifies unauthorized coding assistants—Cursor, Copilot, Claude Code—accessing source code repositories and executing commands, distinguishing sanctioned tools from shadow ones against organizational policy.

Expose credential leakage in AI configurations

Spektion detects plaintext API keys and tokens embedded in AI and MCP server configuration files before they become a breach, and tracks them through to remediation.

Map and secure MCP servers and autonomous agents

Spektion discovers every Model Context Protocol server exposing tools, data, and credentials to AI agents, and inventories multi-agent frameworks executing code and making network requests without human oversight.

Assess exploitability across privilege, exposure, and AI-generated code

Spektion analyzes execution context to flag AI workloads running with excessive privileges, inference servers exposed on open network interfaces, and AI-generated executables with no CVE or signature—scoring risk based on real runtime state.

Customer Quote

"We discovered coding assistants running on dozens of machines we didn't know about. Spektion’s runtime telemetry found them in real time—including several with plaintext API keys.

VP of Security, Fortune 500 Financial Services
How It Works

From shadow AI to continuous observability & governance

Four steps. One agent. No reboot required.

Step 1

Deploy the runtime sensor

Install a lightweight agent across endpoints and servers. Deployment takes under five minutes per endpoint. No reboot required. Supports Intune, SCCM, Ansible, JAMF, Tanium, and CrowdStrike RTR.

Step 2

Continuously discover AI workloads automatically

Spektion identifies every AI agent, inference server, and coding assistant operating across the environment — including tools you didn't know were installed.

Step 3

Assess AI exposure risk

Runtime analysis detects credential exposure, privilege misuse, exposed inference servers, and unauthorized AI tools—scored by actual risk, not guesswork.

Step 4

Prioritize remediation

Security teams receive risk-scored findings and specific recommended remediation actions to satisfy your organizational AI security baseline.

FAQ

Frequently asked questions about runtime risk beyond CVEs.

If you're in a bake-off or building the business case, these are the answers you'll need.

What vulnerabilities do vulnerability scanners miss?

Vulnerability scanners detect known CVEs. They cannot detect risky runtime behavior or exploitable conditions that have not been disclosed. Many exploitable conditions never receive a CVE, because they arise from behavioral weaknesses, supply-chain components, or software that changes after deployment. Any tool that starts with CVE data as its input inherits this structural limitation.

Explore third-party software risk →
Can software be risky without a CVE?

Yes. Many exploitable risks arise from dangerous runtime behavior rather than documented vulnerabilities. Spektion research found that 71% of applications with known exploitable flaws had no CVE assigned. A PDF editor with zero CVEs was observed capturing keystrokes, allocating executable memory with elevated privileges, and creating a remotely accessible named pipe—all mapped to MITRE ATT&CK techniques.

How can security teams detect risks before CVEs exist?

By analyzing runtime activity instead of relying solely on vulnerability disclosures. Spektion observes what software does (system calls, memory operations, network connections, privilege use, file access) and identifies behavioral patterns that indicate exploitability. Spektion identifies exploitable behavior, maps it to CVEs, and integrates with your security.

What is runtime exposure management?

Runtime exposure management analyzes software behavior during execution to detect exploitable conditions that traditional vulnerability tools cannot see. Rather than matching installed software against a CVE database, Spektion observes what software actually does—revealing risky behavior whether or not it has been disclosed, documented, or assigned a CVE ID. It covers both CVE-based risks and the hidden half: the exploitable conditions that will never receive a CVE.

Is this the same as automated pentesting?

No. Automated pentesting tools run exploits against your environment to test exploitability, with associated production risk and point-in-time results. Spektion observes runtime context continuously—what's executing, with what privileges, exhibiting what behavioral patterns—without running exploits. Coverage is continuous and extends to risks no exploit database enumerates.

Can Spektion detect exploitability in AI-generated internal tools?

Yes.  Spektion sees these tools, even if only created and executed by one user on a single asset, as soon as they execute, continuously monitors behavior, and reports on exploitable weakness in near real-time.