CYFIRMA Research- REVENANT: Executionless, Self-Assembling Threat Hidden in System Entropy

New Threat Model: Executionless Persistence Across Endpoints & AI Layers REVENANT introduces a forward-looking multi-stage attack framework that chains stealthy, executionless techniques to persist not just on systems, but in the operational memory of AI assistants.

Key Highlights:

• Executionless delivery via fonts, clipboard state, and localization strings, no exploits, macros, or dropped binaries.
• AI-layer manipulation (inspired by real-world prompt injection research) to misclassify or suppress SOC alerts.
• Covert exfiltration through whitelisted telemetry channels, such as crash reporting.
• Chainable primitives that evade signature-based detection while surviving endpoint reimaging.
• Includes MITRE ATT&CK mapping, full kill chain simulation, and lab-safe PoC scenarios for blue team training.

REVENANT shows how trusted system features and AI-integrated workflows can be turned into long-lived footholds, bypassing traditional detection entirely. It’s a wake-up call for defenders: securing endpoints is no longer enough; the AI context layer is now part of the attack surface.

Link to the Research Report: https://www.cyfirma.com/research/revenant-executionless-self-assembling-threat-hidden-in-system-entropy/

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