AI Detection & Response (AIDR) platforms inspect prompts, model responses, and agent tool calls as they pass through instrumented channels, blocking injection and redacting sensitive data at the model boundary. Spektion observes the AI workloads themselves as they execute on endpoints and servers: what ran, who ran it, what it did to files, shells, and the network. It detects insecure agent behavior like credential access and novel destinations, with the evidence and recommended actions to mitigate and respond.
AIDR platforms (such as CrowdStrike Falcon AIDR and Zenity) apply the detection-and-response model to the AI interaction layer: collectors placed in the path inspect prompts and model outputs, detect injection and data leakage, and enforce policy before content reaches a model or a user. Spektion detects at the layer AIDR does not natively see: the endpoint OS runtime, where AI tools execute, expanding exposure management beyond vulnerable software to insecure agent behavior. Like every layer Spektion adds, the difference is new data and new outcomes.
New data
First-party runtime observation of AI workloads at the endpoint OS: what executes, under which identity, and what it does (files, shells, connections, novel domains, MCP servers, configuration changes). AIDR collectors inspect interaction content in instrumented channels; they do not observe the process on the host.
New outcomes
Discovery of every AI workload, including shadow AI no collector intercepts. Detection of insecure agent behavior (credential access, novel destinations, privileged execution, boundary violations) with command-line evidence. Response scoped to what was touched, with a recommended action per detection.
AIDR inspects and controls the content of AI interactions. Spektion observes the execution behavior and exposure of the AI workloads themselves. Different layers, different evidence, one program.
AIDR answers a real question: is this interaction with a model safe, and should it proceed? But an AI agent is also a process on a host. When an injected or misbehaving agent acts, the consequences land on the endpoint: files touched, shells run, credentials read, connections opened. That is a different layer of evidence, and it requires observation at the OS runtime.
AIDR sees the content that flows through its collectors: browser extensions, SDKs, gateways, MCP proxies. It can block an injection before it reaches the model. It cannot see the workload that never crosses an instrumented path, or what an agent did to the host after the interaction it inspected.
Spektion discovers AI tools from their execution, records each session as behavior (files, shells, connections, novel domains, MCP usage, configuration changes) and detects when that behavior crosses a security boundary. Every detection is attributed to a named OS identity and asset and carries a recommended action, so response is scoped to what was actually touched.
Block prompt injection and jailbreaks in real time, redact sensitive data before it reaches a model, and enforce AI usage policy across managed browsers, applications, and gateways.
…you need to discover the AI workloads no collector intercepts, detect insecure agent behavior on the host with command-line evidence and a recommended action for every finding, and assess the exploitable conditions AI tools create, from credentials in MCP configs to exposed inference servers.
These layers are complementary. AIDR detects and blocks threats at the model boundary; Spektion detects insecure agent behavior on the host and gives your team the evidence and actions to mitigate it.
We discovered coding assistants running on dozens of machines we didn't know about. Spektion saw them the day it deployed.
No, but Spektion detects too, at a different layer. AIDR platforms inspect and control the content of AI interactions through collectors placed in the interaction path. Spektion detects insecure agent behavior at the endpoint OS runtime: credential access, novel destinations, privileged execution, and boundary violations, each severity-scored with evidence and a recommended action. Spektion expands exposure management beyond vulnerable software to insecure agent behavior; it does not inspect or block prompt content. The layers complement each other.
Falcon AIDR deploys collectors (browser extensions, SDKs, AI gateways, MCP proxies) to inspect AI interactions and enforce policy at the model boundary. Spektion deploys one endpoint sensor and detects at the process level: discovery from execution, severity-scored detections on insecure agent behavior with command-line evidence and recommended actions, and runtime exposure grading of the AI tools themselves. Falcon AIDR detects threats in the conversation; Spektion detects insecure behavior in the process.
Yes. They operate at different layers and strengthen each other. Spektion surfaces the full AI estate so you know what the interaction layer should cover, and when an AIDR detection fires, Spektion supplies the execution record: who ran the agent, on which asset, and what it did on the host.
AI workloads that never cross a collector: local CLI agents, local inference servers, tools running outside managed browsers. Detections on the host-level consequences of agent activity: credential access, first-seen domains, privileged execution, and configuration changes, each with evidence, a recommended action, and attribution to a named OS identity. And the exposure of the AI tools themselves: CVEs, runtime weaknesses, plaintext credentials in MCP configurations, exposed inference ports.
Bring a slice of your environment to a demo and see your full AI workload inventory, live detections on agent behavior, and the exposures your interaction layer can’t reach.