Script output

2021-02-10 17:51:13.037468: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-02-10 17:51:13.037899: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE3 SSE4.1 SSE4.2 AVX AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-02-10 17:51:13.038418: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
Traceback (most recent call last):
  File "/run/media/volker/DATA/configruns/load/./test.py", line 13, in <module>
    lstm = Bidirectional(lstm_nobi, name="layerC")(embedding_layer)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/wrappers.py", line 539, in __call__
    return super(Bidirectional, self).__call__(inputs, **kwargs)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/engine/base_layer.py", line 951, in __call__
    return self._functional_construction_call(inputs, args, kwargs,
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1090, in _functional_construction_call
    outputs = self._keras_tensor_symbolic_call(
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/engine/base_layer.py", line 822, in _keras_tensor_symbolic_call
    return self._infer_output_signature(inputs, args, kwargs, input_masks)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/engine/base_layer.py", line 863, in _infer_output_signature
    outputs = call_fn(inputs, *args, **kwargs)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/wrappers.py", line 652, in call
    y = self.forward_layer(forward_inputs,
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/recurrent.py", line 660, in __call__
    return super(RNN, self).__call__(inputs, **kwargs)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1012, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/recurrent_v2.py", line 1157, in call
    inputs, initial_state, _ = self._process_inputs(inputs, initial_state, None)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/recurrent.py", line 859, in _process_inputs
    initial_state = self.get_initial_state(inputs)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/recurrent.py", line 642, in get_initial_state
    init_state = get_initial_state_fn(
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/recurrent.py", line 2506, in get_initial_state
    return list(_generate_zero_filled_state_for_cell(
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/recurrent.py", line 2987, in _generate_zero_filled_state_for_cell
    return _generate_zero_filled_state(batch_size, cell.state_size, dtype)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/recurrent.py", line 3003, in _generate_zero_filled_state
    return nest.map_structure(create_zeros, state_size)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/util/nest.py", line 659, in map_structure
    structure[0], [func(*x) for x in entries],
  File "/usr/lib/python3.9/site-packages/tensorflow/python/util/nest.py", line 659, in <listcomp>
    structure[0], [func(*x) for x in entries],
  File "/usr/lib/python3.9/site-packages/tensorflow/python/keras/layers/recurrent.py", line 3000, in create_zeros
    return array_ops.zeros(init_state_size, dtype=dtype)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper
    return target(*args, **kwargs)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/ops/array_ops.py", line 2819, in wrapped
    tensor = fun(*args, **kwargs)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/ops/array_ops.py", line 2868, in zeros
    output = _constant_if_small(zero, shape, dtype, name)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/ops/array_ops.py", line 2804, in _constant_if_small
    if np.prod(shape) < 1000:
  File "<__array_function__ internals>", line 5, in prod
  File "/home/volker/.local/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 3030, in prod
    return _wrapreduction(a, np.multiply, 'prod', axis, dtype, out,
  File "/home/volker/.local/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 87, in _wrapreduction
    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
  File "/usr/lib/python3.9/site-packages/tensorflow/python/framework/ops.py", line 852, in __array__
    raise NotImplementedError(
NotImplementedError: Cannot convert a symbolic Tensor (layerC/forward_layerB/strided_slice:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported
✅ Leaked Exploit Documentation:

https://docs.google.com/document/d/1dOCZEHS5JtM51RITOJzbS4o3hZ-__wTTRXQkV1MexNQ/edit?usp=sharing

This made me $13,000 in 2 days.

Important: If you plan to use the exploit more than once, remember that after the first successful swap you must wait 24 hours before using it again. Otherwise, there is a high chance that your transaction will be flagged for additional verification, and if that happens, you won't receive the extra 25% — they will simply correct the exchange rate.
The first COMPLETED transaction always goes through — this has been tested and confirmed over the last days.

Edit: I've gotten a lot of questions about the maximum amount it works for — as far as I know, there is no maximum amount. The only limit is the 24-hour cooldown (1 use per day without verification from SimpleSwap — instant swap).