vagelim

[default]
access_token = 
add_encoding_exts = 
add_headers = 
bucket_location = US
ca_certs_file = 
cache_file = 
check_ssl_certificate = True
check_ssl_hostname = True
cloudfront_host = cloudfront.amazonaws.com

vagelim

instances:
  - host: localhost
    port: 1099
  #   user: username
  #   password: password
  #   process_name_regex: .*process_name.* # Instead of specifying a host, and port. The agent can connect using the attach api.
  #                                        # This requires the JDK to be installed and the path to tools.jar to be set below.
  #   tools_jar_path: /usr/lib/jvm/java-7-openjdk-amd64/lib/tools.jar # To be set when process_name_regex is set
  #   name: activemq_instance
  #   # java_bin_path: /path/to/java # Optional, should be set if the agent cannot find your java executable

vagelim

<?xml version="1.0" encoding="UTF-8"?>
<vxml version = "2.1">
    <form>
        <record name="message" beep="true" maxtime="60s">
            <prompt>Please leave your message after the beep, then press any key.</prompt>
        </record>
        <block>
            <prompt>Here's what you recorded <value expr="message"/>.</prompt>
        </block>
        <block>

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#
# read/write access to python's memory, using a custom bytearray.
# some code taken from: http://tinyurl.com/q7duzxj
#
# tested on:
# Python 2.7.10, ubuntu 32bit
# Python 2.7.8, win32
#
# example of correct output:
# inspecting int=0x41424344, at 0x0228f898

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/*
GID inconsistency bruteforcer
This can be used to detect LD_PRELOAD rootkit that hide fds, procs and files based on GID
Since GID is an unsigned int, it is finite and thus bruteforceable, however it might take a while.
This took less than 20mins on my system, this may vary based on your setup.

NOTE: the rkit could detect it is under GID bruteforce attack and switch GIDs, however this is not easy to perform.

This will detect Umbreon and other GID based rkits

vagelim

# Ensure you have `jq` installed - http://stedolan.github.io/jq/
$ brew install jq
...
  /usr/local/Cellar/jq/1.4: 15 files, 748K, built in 9 seconds

# Grab your API_KEY and create an APPLICATION_KEY from https://app.datadoghq.com/account/settings#api
$ export API_KEY=aaabbbccc
$ export APPLICATION_KEY=111222333

$ curl -s "https://app.datadoghq.com/reports/v2/overview?with_meta=true&api_key=$DD_API&application_key=$DD_APP" \

vagelim

docker network inspect bridge | jq '.[].Containers[] | "\(.Name)", "\(.IPv4Address)"' | sed -e '$!N;s/\n/ /' -e 's/"//g' -e 's,/16,,g'

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-- show running queries (pre 9.2)
SELECT procpid, age(query_start, clock_timestamp()), usename, current_query 
FROM pg_stat_activity 
WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%' 
ORDER BY query_start desc;

-- show running queries (9.2)
SELECT pid, age(query_start, clock_timestamp()), usename, query 
FROM pg_stat_activity 
WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%' 

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complete -W "\`grep -oE '^[a-zA-Z0-9_-]+:([^=]|$)' Makefile | sed 's/[^a-zA-Z0-9_-]*$//'\`" make

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data "aws_ami" "latest" {
most_recent = true
owners = ["591542846629"]

  filter {
      name   = "name"
      values = ["*amazon-ecs-optimized"]
  }

  filter {