blu3r4y

Write-Up: Web - Log4j & Log4j2 from Google CTF 2022

This blog post explains three ways to exploit Log4j 2.17.2 from Google CTF 2022:

• Level 1: Trigger an exception in Log4j that contains the flag
• Level 2: Guessing the flag with the help of RegEx conversion patterns
• Bonus: Guessing the flag with a time-based side channel using ReDoS

The bonus was not necessary to solve the challenge but fun to code ;)

blu3r4y

name: setup-poetry
on:
  push:

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
        uses: actions/checkout@v4

blu3r4y

# Copyright 2021
#    Dynatrace Research
#    SAL Silicon Austria Labs
#    LIT Artificial Intelligence Lab
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0

blu3r4y

# Copyright 2021
#    Dynatrace Research
#    SAL Silicon Austria Labs
#    LIT Artificial Intelligence Lab
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0

blu3r4y

# Copyright 2021
#    Dynatrace Research
#    SAL Silicon Austria Labs
#    LIT Artificial Intelligence Lab
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0

blu3r4y

import re, sys

REGEX_ATTACHMENT = {"de": r"\u200E(.*?) \(Datei angehängt\)"}
SUB_ATTACHMENT = r"<attached: \g<1>>"


def convert(file: str, locale="de"):
    """
    Convert the locale of attachments to the english one.
    The output is written to a file in the same location.

blu3r4y

import numpy as np


def majority_vote(*arrays: np.array, n_classes: int = None) -> np.array:
    """
    Given an arbitrary number of integer-based, one-dimensional input vectors
    that represent class labels, compute a new vector that will take the majority
    label of the input vectors. Ties are broken randomly for each observation.

    If you omit the `n_classes` argument, it will be inferred by counting

blu3r4y

from circus import get_arbiter

alice = dict(
    name="alice",
    cmd="python -m flask run --port=81",
    env={"FLASK_APP": "flask_alice.py"},
    copy_env=True,
    copy_path=True,
)

blu3r4y

Keybase proof

I hereby claim:

• I am blu3r4y on github.
• I am blu3r4y (https://keybase.io/blu3r4y) on keybase.
• I have a public key ASAaCd4yddilhaf1QEv9GI40ZdcfMICJMpPkklewor035Ao

To claim this, I am signing this object:

blu3r4y

from functools import lru_cache
from typing import Sequence


class LazySequence(Sequence):
    """
    A sequence object that is backed by a function for retrieving elements
    """

    @lru_cache(maxsize=None)