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10/06/2026 11:47 pm
TL;DR: Gartner’s AI Vendor Race report says AI is helping advanced cyber deception systems anticipate and counter threats at scale by automating deceptive elements and adapting to attacker interaction, while Acalvio is cited for broad coverage across legacy, cloud, identity, and cyber-physical environments. That combination makes deception less about lures and more about identity-aware telemetry and faster attacker attribution.
NHIMG editorial — based on content published by Acalvio: Acalvio recognized as the company to beat in Gartner's AI Vendor Race for cyber deception
Questions worth separating out
Q: How should security teams use cyber deception in identity security programmes?
A: Use it as a signal layer that helps surface misuse of identities, tokens, and access paths.
Q: Why does AI change the value of cyber deception?
A: AI lets deception systems adapt traps and responses more quickly than static bait can.
Q: What is the difference between deception coverage and identity governance?
A: Deception coverage is about observing attacker interaction through false or monitored assets.
Practitioner guidance
- Map deception events to identity telemetry Correlate deceptive asset interactions with account activity, token use, privileged sessions, and cloud access logs so the signal can be consumed by IAM and IR teams.
- Separate IT, OT, and cloud coverage requirements Review whether deceptive assets remain believable and safe across legacy systems, modern cloud services, and cyber-physical environments before assuming one design fits all.
- Define response ownership before deployment Assign clear ownership for triage, containment, and follow-up when a deceptive asset is touched, especially where the same alert may involve IAM, PAM, or SOC workflows.
What's in the full analysis
Acalvio's full post covers the operational detail this post intentionally leaves for the source:
- How the vendor frames AI-driven deception across identity, cloud, on-premises, and cyber-physical environments
- The Gartner excerpts that describe why AI is changing the deception market and how defenders can adapt behavior dynamically
- Details on Acalvio's AI-powered platform capabilities, tool and protocol integrations, and partner ecosystem
- Context on how the vendor positions deception for ITDR and preemptive cybersecurity use cases
👉 Read Acalvio's analysis of Gartner's AI Vendor Race for cyber deception →
AI-powered cyber deception: what it means for identity threat detection?
Explore further
12/06/2026 6:09 am
AI-driven deception is becoming an identity-adjacent control, not a standalone lure layer. The report’s framing matters because attackers do not move through enterprises as abstract threats, they move through identities, tokens, services, and access paths. When deception is tied to those paths, it becomes a way to observe intent and timing rather than merely detect presence. Practitioners should treat deception as a telemetry amplifier for NHI governance, not as a replacement for it.
A few things that frame the scale:
- 43% of security professionals are concerned about AI systems learning and reproducing sensitive information patterns from codebases, according to The State of Secrets in AppSec.
- Organisations maintain an average of 6 distinct secrets manager instances, creating fragmentation that undermines centralised control, according to The State of Secrets in AppSec.
A question worth separating out:
Q: How can teams evaluate whether deception is actually working?
A: Look for evidence that deception improves attribution, reduces investigation time, and exposes real attacker behaviour in identity-heavy paths. If alerts do not correlate to IAM, PAM, or cloud events, the control may be producing noise instead of usable intelligence. A good programme shows measurable impact on triage and containment decisions.
👉 Read our full editorial: AI-powered cyber deception shifts identity threat detection to preemptive defense
