hashcat/Python/hcmp.py

import hcshared
import multiprocessing

def init(ctx: dict, user_fn, extract_esalts):
    # Extract and merge salts and esalts
    salts = hcshared.extract_salts(ctx["salts_buf"])
    esalts = extract_esalts(ctx["esalts_buf"])
    for salt, esalt in zip(salts, esalts):
        salt["esalt"] = esalt

    st_salts = hcshared.extract_salts(ctx["st_salts_buf"])
    st_esalts = extract_esalts(ctx["st_esalts_buf"])
    for salt, esalt in zip(st_salts, st_esalts):
        salt["esalt"] = esalt

    # Save state in ctx
    ctx["salts"] = salts
    ctx["st_salts"] = st_salts
    ctx["user_fn"] = user_fn
    ctx["pool"] = multiprocessing.Pool(processes=ctx["parallelism"])
    return

def handle_queue(ctx: dict, passwords: list, salt_id: int, is_selftest: bool) -> list:
    user_fn = ctx["user_fn"]
    salts = ctx["salts"]
    st_salts = ctx["st_salts"]
    pool = ctx["pool"]
    parallelism = ctx["parallelism"]

    chunk_size = (len(passwords) + parallelism - 1) // parallelism
    chunks = [passwords[i:i + chunk_size] for i in range(0, len(passwords), chunk_size)]

    jobs = []
    for chunk in chunks:
        if chunk:
            jobs.append(pool.apply_async(
                hcshared._worker_batch,
                args=(chunk, salt_id, is_selftest, user_fn, salts, st_salts)
            ))

    hashes = []
    for job in jobs:
        hashes.extend(job.get())
    return hashes

def term(ctx: dict):
    if "pool" in ctx:
        ctx["pool"].close()
        ctx["pool"].join()
        del ctx["pool"]
    return