How traditional threat intelligence measures up to adversary-generated threat intelligence.
Examples of security use cases cyber deception is ideal for.
Examples of the detailed threat intel deception provides, including IoCs and TTPs.

How threat intelligence powered by deception technology delivers proactive protection of critical assets without burdening regular service operations.
Threat intelligence is information that helps security teams understand attacker behavior, including tactics, techniques, procedures (TTPs), intent, and indicators of compromise (IoCs). It matters because it helps teams prioritize real risk, respond faster, and make decisions based on evidence rather than assumptions.
CounterCraft generates threat intelligence from real attacker interaction inside decoy environments. Unlike third-party feeds or heuristic signals, this intelligence reflects how adversaries actually behave against your own systems, not generic indicators.
CounterCraft provides insight into attacker behavior, lateral movement, reconnaissance activity, insider misuse, and decision-making during an intrusion. These insights help teams understand what an attacker is doing and what they are likely to do next.
CounterCraft deploys decoy systems, credentials, and services that mirror real infrastructure. When attackers interact with these assets, their actions are captured and converted into real-time, specific, and actionable intelligence for security teams.
Yes. Because detection is based on attacker behavior rather than known signatures, CounterCraft can surface previously unseen techniques that rule-based tools may miss.
Threat intelligence from CounterCraft feeds into existing SOC workflows and tools such as SIEM and SOAR, helping teams prioritize alerts and respond faster without changing their core stack.
SOC teams, incident responders, threat hunters, and CTI researchers benefit most, especially in environments exposed to targeted attacks, insider threats, or complex intrusion paths.
Threat intelligence generation begins immediately once deception assets are deployed. As soon as attackers interact with decoy systems, the platform captures their behavior and converts it into actionable intelligence. Organizations typically start receiving high-confidence threat data within the first weeks of deployment, though the timing depends on when attackers begin reconnaissance or lateral movement in the environment.
Threat data is raw information such as IPs or hashes. Threat intelligence adds context, intent, and relevance so teams can act on it.
By prioritizing intelligence derived from direct attacker activity instead of relying only on external feeds.
Feeds provide broad context. Deception-based intelligence provides direct evidence of attacker behavior inside your environment. Most teams use both, but for detection and response, behavior-based intelligence is more actionable. Find out how AI-powered deception works with a demo.