Deception technology solutions: an enterprise buyer’s framework for 2026

In the disclosed GTG-1002 espionage campaign, attackers directed Claude Code to execute an estimated 80 to 90 percent of the operation autonomously, showing the machine speed you now defend against. That figure comes from Anthropic’s own disclosure of the campaign: GTG-1002 was an attacker-directed AI system used against outside targets, not a case of a victim organization’s own enterprise agent being hijacked, but it is still a clear signal of how fast unsupervised operations can now move. The identity, cloud, and network controls you run remain essential, but authenticated and authorized activity can still be working toward the wrong objective, a gap a preemptive deception layer closes. If you are evaluating deception technology solutions in 2026, start with the criteria that separate platforms that scale in production from those that stay a proof of concept: deployment model, environment coverage, and independent validation.

At a glance

• Acalvio is named a leader and outperformer in the GigaOm Radar for Deception Technology for the fourth consecutive year in 2026.
• Weigh deployment model, environment coverage, and independent validation alongside vendor track record and production experience, not against them.
• Full coverage spans identity, cloud, network, and OT and ICS environments, not a single layer of the stack.
• Deception is additive to your identity, endpoint, and network controls; it does not replace them.
• In the U.S. Navy ANTX FY25 exercise, Acalvio delivered 100 percent true positive alerts and denied 80 percent of attacker objectives against automated, credential-driven techniques.

A cyber deception shortlist should be built around four criteria, weighted alongside vendor track record and production experience rather than in place of them: deployment model, coverage across environments, deception depth beyond static honeypots, and independent, third-party validation.

Deployment model matters because an agentless platform can start generating alerts within days, without rolling out software agents before decoys go live; a deployment that stalls in a proof-of-concept phase never delivers the coverage you are paying for. Coverage across environments matters because attackers do not confine themselves to one layer of the stack, so a shortlist candidate needs to cover identity, cloud, network, and OT and ICS environments from a single platform rather than stitching together separate point products. Deception depth matters because a single static decoy is easy for a patient attacker to map and avoid, and a hand-maintained one cannot keep pace with automated reconnaissance; a shortlist candidate needs dynamic decoys, honeytokens, and deceptive paths that refresh automatically, since automation is the baseline requirement at machine speed, not an upgrade. Independent validation matters because a vendor’s own performance claims carry less weight than an outside evaluation, an analyst report, or a controlled exercise run by a third party.

Acalvio applies all four in practice, largely through ShadowPlex’s agentless deployment and 360 Deception coverage, detailed in the sections below.

Acalvio is named a leader and outperformer in the GigaOm Radar for Deception Technology for the fourth consecutive year in 2026, a recognition based on GigaOm’s independent evaluation of deception platforms. The GigaOm Radar evaluates enterprise deception vendors across concentric rings, placing solutions with the highest balance of maturity, innovation, and execution closest to the center; for the fourth consecutive year, Acalvio secured its position closest to the center of the Leader ring, with GigaOm citing its development cadence, including advancements in autonomous decoy orchestration, predictive attack path analysis, OT deception, and generative deception features.

This standing rests on the ShadowPlex Preemptive Cybersecurity Platform and its 360 Deception approach, built on three deception vectors Acalvio calls Fake Looks Real, Real Looks Fake, and Intentionally Suspicious Artifacts, applied across identity, cloud, network, and OT and ICS environments from a single management fabric. Rather than forcing security operations teams to manage fragmented point products across separate environments, this architecture delivers dynamic, cross-environment visibility, and it is why Acalvio is often named among the top deception technology providers in the category: a platform tested by someone other than the vendor itself, one that covers more than one layer of the environment, and one with a track record of translating detections into denied attacker objectives rather than noisy alerts.

Your requirements as an enterprise buyer go beyond what a smaller deployment needs. A platform has to scale across a large, often hybrid or multi-cloud footprint without requiring a separate infrastructure build, and it has to integrate with tools already in your security operations center, including SIEM and SOAR, so deception-generated alerts flow into the same triage and response workflows your analysts already use instead of adding a separate console to their workload. ShadowPlex’s agentless deployment model and its existing integrations with common SIEM and SOAR platforms address these requirements, letting a large environment adopt deception without replacing or duplicating existing infrastructure.

Deception in this model is additive. ShadowPlex runs alongside SIEM, EDR, IAM, PAM, MFA, and XDR rather than replacing any of them; it adds an intent-based signal for activity that has already cleared those controls.

The strongest proof point for a deception technology vendor is a controlled, third-party exercise rather than a vendor’s own marketing claim. In the U.S. Navy ANTX FY25 exercise, run by the Naval Information Warfare Center Pacific, Acalvio was evaluated against a live red team: every alert it generated reflected a high-confidence indicator of malicious activity, and it denied 80 percent of the attacker’s objectives across the automated, credential-driven techniques in scope for the exercise, spanning initial enumeration through credential access and lateral movement, techniques also documented in MITRE ATT&CK. This exercise was not a production AI-agent deployment; it is supporting evidence for the underlying detection mechanism, scoped to the conditions of the exercise itself.

That kind of result is difficult to manufacture in a vendor demo. It requires a live red team exercise, an independent government evaluator, and clear objectives for what the attacker is trying to achieve, which is exactly what separates a controlled exercise from a marketing claim. Why did anything touch an asset no legitimate process should need? That is the question a high-confidence deception alert answers, and it is why evaluations like ANTX FY25 carry more weight than an internal benchmark.