AUTARCH v1.9 — remote monitoring, SSH manager, daemon, vault, cleanup
- Add Remote Monitoring Station with PIAP device profile system - Add SSH/SSHD manager with fail2ban integration - Add privileged daemon architecture for safe root operations - Add encrypted vault, HAL memory, HAL auto-analyst - Add network security suite, module creator, codex training - Add start.sh launcher script and GTK3 desktop launcher - Remove Output/ build artifacts, installer files, loose docs - Update .gitignore for runtime data and build artifacts - Update README for v1.9 with new launch method, screenshots, and features Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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SsSnake
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core/hal_memory.py
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217
core/hal_memory.py
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"""
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AUTARCH HAL Memory Cache
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Encrypted conversation history for the HAL AI agent.
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Stores all HAL conversations in an AES-encrypted file.
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Only the AI agent system can read them — the decryption key is
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derived from the machine ID + a HAL-specific salt, same pattern
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as the vault but with a separate keyspace.
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Max size: configurable, default 4GB. Trims oldest entries when exceeded.
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Usage:
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from core.hal_memory import get_hal_memory
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mem = get_hal_memory()
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mem.add('user', 'scan my network')
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mem.add('hal', 'Running nmap on 10.0.0.0/24...')
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history = mem.get_history(last_n=50)
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mem.add_context('scan_result', {'tool': 'nmap', 'output': '...'})
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"""
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import hashlib
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import json
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import logging
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import os
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import struct
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import time
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from pathlib import Path
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from typing import Optional
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_log = logging.getLogger('autarch.hal_memory')
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_MEMORY_DIR = Path(__file__).parent.parent / 'data'
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_MEMORY_FILE = _MEMORY_DIR / 'hal_memory.enc'
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_MEMORY_MAGIC = b'HALM'
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_MEMORY_VERSION = 1
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_DEFAULT_MAX_BYTES = 4 * 1024 * 1024 * 1024 # 4GB
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def _derive_key(salt: bytes) -> bytes:
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"""Derive AES key from machine identity + HAL-specific material."""
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machine_id = b''
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for path in ('/etc/machine-id', '/var/lib/dbus/machine-id'):
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try:
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with open(path) as f:
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machine_id = f.read().strip().encode()
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break
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except Exception:
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continue
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if not machine_id:
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import socket
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machine_id = f"hal-{socket.gethostname()}".encode()
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return hashlib.pbkdf2_hmac('sha256', machine_id + b'HAL-MEMORY-KEY', salt, 100_000, dklen=32)
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def _encrypt(plaintext: bytes, key: bytes) -> tuple:
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iv = os.urandom(16)
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try:
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from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
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from cryptography.hazmat.primitives.padding import PKCS7
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padder = PKCS7(128).padder()
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padded = padder.update(plaintext) + padder.finalize()
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enc = Cipher(algorithms.AES(key), modes.CBC(iv)).encryptor()
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return iv, enc.update(padded) + enc.finalize()
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except ImportError:
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pass
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try:
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from Crypto.Cipher import AES
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from Crypto.Util.Padding import pad
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return iv, AES.new(key, AES.MODE_CBC, iv).encrypt(pad(plaintext, 16))
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except ImportError:
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raise RuntimeError('No crypto backend available')
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def _decrypt(iv: bytes, ciphertext: bytes, key: bytes) -> bytes:
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try:
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from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
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from cryptography.hazmat.primitives.padding import PKCS7
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dec = Cipher(algorithms.AES(key), modes.CBC(iv)).decryptor()
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padded = dec.update(ciphertext) + dec.finalize()
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return PKCS7(128).unpadder().update(padded) + PKCS7(128).unpadder().finalize()
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except ImportError:
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pass
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try:
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from Crypto.Cipher import AES
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from Crypto.Util.Padding import unpad
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return unpad(AES.new(key, AES.MODE_CBC, iv).decrypt(ciphertext), 16)
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except ImportError:
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raise RuntimeError('No crypto backend available')
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class HalMemory:
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"""Encrypted conversation memory for HAL."""
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def __init__(self, max_bytes: int = _DEFAULT_MAX_BYTES):
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self._max_bytes = max_bytes
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self._salt = b''
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self._entries = []
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self._load()
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def _load(self):
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if not _MEMORY_FILE.exists():
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self._salt = os.urandom(32)
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self._entries = []
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return
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try:
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with open(_MEMORY_FILE, 'rb') as f:
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magic = f.read(4)
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if magic != _MEMORY_MAGIC:
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self._salt = os.urandom(32)
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self._entries = []
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return
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f.read(1) # version
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self._salt = f.read(32)
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iv = f.read(16)
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ciphertext = f.read()
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key = _derive_key(self._salt)
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plaintext = _decrypt(iv, ciphertext, key)
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self._entries = json.loads(plaintext.decode('utf-8'))
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_log.info(f'[HAL Memory] Loaded {len(self._entries)} entries')
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except Exception as e:
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_log.error(f'[HAL Memory] Load failed: {e}')
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self._salt = os.urandom(32)
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self._entries = []
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def _save(self):
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try:
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_MEMORY_DIR.mkdir(parents=True, exist_ok=True)
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key = _derive_key(self._salt)
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plaintext = json.dumps(self._entries).encode('utf-8')
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# Trim if over max size
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while len(plaintext) > self._max_bytes and len(self._entries) > 10:
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self._entries = self._entries[len(self._entries) // 4:] # Drop oldest 25%
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plaintext = json.dumps(self._entries).encode('utf-8')
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_log.info(f'[HAL Memory] Trimmed to {len(self._entries)} entries ({len(plaintext)} bytes)')
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iv, ciphertext = _encrypt(plaintext, key)
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with open(_MEMORY_FILE, 'wb') as f:
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f.write(_MEMORY_MAGIC)
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f.write(struct.pack('B', _MEMORY_VERSION))
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f.write(self._salt)
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f.write(iv)
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f.write(ciphertext)
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os.chmod(_MEMORY_FILE, 0o600)
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except Exception as e:
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_log.error(f'[HAL Memory] Save failed: {e}')
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def add(self, role: str, content: str, metadata: dict = None):
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"""Add a conversation entry."""
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entry = {
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'role': role,
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'content': content,
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'timestamp': time.time(),
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}
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if metadata:
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entry['metadata'] = metadata
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self._entries.append(entry)
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# Auto-save every 20 entries
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if len(self._entries) % 20 == 0:
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self._save()
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def add_context(self, context_type: str, data: dict):
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"""Add a context entry (scan result, fix result, IR, etc.)."""
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self.add('context', json.dumps(data), metadata={'type': context_type})
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def get_history(self, last_n: int = 50) -> list:
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"""Get recent conversation history."""
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return self._entries[-last_n:] if self._entries else []
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def get_full_history(self) -> list:
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"""Get all entries."""
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return self._entries
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def search(self, query: str, max_results: int = 20) -> list:
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"""Search memory for entries containing query string."""
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query_lower = query.lower()
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results = []
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for entry in reversed(self._entries):
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if query_lower in entry.get('content', '').lower():
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results.append(entry)
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if len(results) >= max_results:
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break
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return results
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def clear(self):
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"""Clear all memory."""
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self._entries = []
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self._save()
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def save(self):
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"""Force save to disk."""
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self._save()
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def stats(self) -> dict:
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"""Get memory stats."""
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total_bytes = len(json.dumps(self._entries).encode())
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return {
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'entries': len(self._entries),
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'bytes': total_bytes,
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'max_bytes': self._max_bytes,
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'percent_used': round(total_bytes / self._max_bytes * 100, 2) if self._max_bytes else 0,
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}
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# Singleton
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_instance: Optional[HalMemory] = None
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def get_hal_memory(max_bytes: int = None) -> HalMemory:
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global _instance
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if _instance is None:
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from core.config import get_config
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config = get_config()
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if max_bytes is None:
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max_bytes = config.get_int('hal_memory', 'max_bytes', _DEFAULT_MAX_BYTES)
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_instance = HalMemory(max_bytes=max_bytes)
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return _instance
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