adversarial-algorithmic-implementation-tap-pair-mcts

name	Adversarial Algorithmic Implementation (TAP/PAIR/MCTS)
description	Implements tree-based attack branching and prompt refinement optimization.

Red-Teaming Attacks Skill

Trigger condition:

When building PersonaGenerators, AttackRunners, or executing simulated adversarial payloads against an Enterprise component.

Supported Protocols:

You must strictly refer to docs/AGENT_DECISION_TREE.md to load the current primary and secondary docs. For attack algorithms, the current primary doc is docs/algorithms.md.

TAP (Tree of Attacks with Pruning)

When orchestrating a TAP node via LangGraph:

1. Branch Sequence: Instruct the Attacker persona to generate N variations of an adversarial prompt.
2. Prune Sequence 1: Evaluator node evaluates out-of-bounds pretexts and deletes the branch.
3. Attack Sequence: Submits the payloads.
4. Prune Sequence 2: Analyze the target response. Drop branches that result in 100% adherence to standard guardrails. Retain only conversational branches with vulnerability flags.

PAIR (Prompt Automatic Iterative Refinement)

For multi-turn, linear refinement:

• The closed-loop system must utilize Chain-of-Thought (CoT) to iteratively refine the target target's refusal message into a more plausible social-engineering pretext.

MCTS (Monte Carlo Tree Search)

• Use MCTS to govern state spaces. If a node is rejected, calculate the Upper Confidence Bound applied to Trees (UCT) formula to switch strategies (e.g., from impersonating IT admin to a senior executive).