Deploys decoys that simulate real network assets, adapting in real time to adversaries' movements and TTPs for maximum believability.
Continuously learns from adversary interactions to improve detection accuracy without requiring manual rule updates.
Generates alerts only when adversaries engage with decoys, eliminating noise and ensuring every alert is a real threat.
Captures malware and payloads not seen by public databases, revealing novel threats before traditional tools can detect them.
Automatically heals compromised decoys while capturing adversaries' behavior and techniques for future analysis.
Modern attackers move laterally in under a second once inside your perimeter.
Traditional security operations tools miss the vast majority of internal host movement.
SOC teams are buried in system noise, missing real threats buried in logs.
Instead of scanning code or monitoring behavioral patterns, active deception alters the battlefield. By deploying indistinguishable fake accounts, files, databases, and network assets, attackers are forced to guess. One wrong step instantly exposes them, turning their speed into their downfall.
No legitimate user has any reason to access decoy assets. Any interaction is an instant high-fidelity incident alert.
Decoys trigger notifications the millisecond an unauthorized entity touches them, bypassing logs and aggregators.
Monitor attackers interacting with fake credentials or decoy directory trees, capturing safe tactical threat intelligence.
Deploy sophisticated fake host footprints and network fabric tricks without slow, heavy agent deployments on end-user machines.
| Feature | EDR / XDR | SIEM | Honeypots | i-Mirage Deception |
|---|---|---|---|---|
| False positive rate | High (noise) | Very high | Very low |
Near zero (alert = breach)
|
| Deployment time | Weeks (agent lag) | Months (rules setup) | Days (per subnet) |
Minutes (cloud automated)
|
| Lateral movement detection | Limited | Log dependent | Siloed |
Comprehensive active fabric
|
| Attacker intelligence | None (blocked) | Post-event | Highly technical |
Detailed threat telemetry
|
| Endpoint agent required | Yes (mandatory) | Often yes | No |
No agent required
|
| OT / IoT asset coverage | Poor/unsupported | Log based | Config heavy |
Native emulated decoys
|
Everything you need to know about i-Mirage active deception technology and how we proactively safeguard your enterprise from lateral cyber threats.
Deception technology plants realistic but fake assets — such as decoy accounts, files, databases, and network services — across your environment. Unlike traditional tools that scan code or monitor behavioral patterns, deception alters the battlefield itself. Attackers are forced to interact with these traps, and any interaction is instant, high-fidelity proof of hostile intent.
No legitimate user or system has any reason to access a decoy asset. Any interaction — whether with a fake credential, directory, or host — is by definition unauthorized. This means every alert is a real incident, eliminating the noise that buries SOC teams under thousands of daily false alerts.
No. i-Mirage deploys sophisticated decoy host footprints and network fabric without heavy agent installations on end-user machines. This enables faster deployment — in minutes for cloud-automated setups — and avoids the lag and complexity of agent-based solutions.
Yes. Modern attackers can move laterally in under a second, and traditional tools miss the vast majority of internal host movement. i-Mirage's active decoy fabric triggers alerts the moment an unauthorized entity touches a decoy, catching lateral movement that log-dependent systems overlook.
When attackers interact with decoy credentials, fake directory trees, or emulated services, i-Mirage safely captures detailed tactical threat intelligence — including attacker techniques, tools, and intent — without exposing real assets. Traditional defences typically block threats with no intelligence gathered.
Request a scoped, risk-free proof of value pilot. Catch unauthorized lateral movement in real-time.
