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xtra

Conversational social engineering detection using a Finite State Machine.

No LLMs. No embeddings. No semantic search. Pure algorithmic detection.

How it works

xtra models conversations as state transitions:

NEUTRAL → RAPPORT_BUILD → TRUST_ESTABLISHED → EXTRACTION_ATTEMPT → FLAGGED

Attacks are detected by their path through state space, not their content.

Signals tracked

  • Flattery density and momentum across turns
  • Asymmetry spike (give/ask ratio collapse)
  • Escalation velocity
  • Reciprocity pressure
  • Decoy turn detection
  • Scope mismatch

Usage

from xtra import Xtra, TurnSignals

result = Xtra().analyze(turns)
if result.is_attack:
    print(result.flag_reason, result.confidence)

Part of Tangible Research

Making AI Tangible — github.com/TangibleResearch

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Extended Threat Reasoning Architecture

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