Deception

2026-05-224 minZscaler ThreatLabzinfo

Frontier AI models such as Anthropic Mythos and OpenAI GPT 5.5 Cyber represent a paradigm shift in security testing by leveraging multi-step reasoning to chain vulnerabilities and misconfigurations into viable attack paths. Zscaler's evaluation demonstrates that these models significantly outperform legacy tools in speed and accuracy when embedded in structured testing harnesses, though they require careful contextual grounding to avoid severity inflation or pattern anchoring. Organizations are advised to implement Zero Trust architectures and deception technologies to mitigate the accelerated threat posed by AI-enabled adversaries.

2026-05-194 minZscaler ThreatLabzinfo

The emergence of advanced AI models capable of rapid vulnerability discovery and exploit prototyping has rendered traditional reactive patching cycles obsolete. Organizations must transition to a Modern Defensible Architecture (MDA) utilizing Zero Trust, active deception, and automated containment to defend against machine-speed threats.

Some honeypots don't exist to catch attackers. They exist to make the environment around them convincing enough that sophisticated actors commit real tooling to the traps that do.

2026-05-134 minCisco Talosinfo

Generative AI enables defenders to rapidly deploy highly adaptive honeypots that simulate complex environments like Linux shells or IoT devices. By leveraging LLMs to generate plausible responses to attacker inputs, organizations can deceive automated AI-driven attacks, shifting the defensive strategy from passive detection to active manipulation and intelligence gathering.