plasma-umass/ChatDBG

Install ChatDBG into the lldb debugger by running the following command:

Linux

python3 -m pip install ChatDBG
python3 -c 'import chatdbg; print(f"command script import {chatdbg.__path__[0]}/chatdbg_lldb.py")' >> ~/.lldbinit

If you encounter an error, you may be using an older version of LLVM. Update to the latest version as follows:

sudo apt install -y lsb-release wget software-properties-common gnupg
curl -sSf https://apt.llvm.org/llvm.sh | sudo bash -s -- 18 all
# LLDB now available as `lldb-18`.

Mac

xcrun python3 -m pip install ChatDBG
xcrun python3 -c 'import chatdbg; print(f"command script import {chatdbg.__path__[0]}/chatdbg_lldb.py")' >> ~/.lldbinit

This will install ChatDBG as an LLVM extension.

Prerequisites

GDB must be built with Python support. To check if your GDB has Python support and which version it uses, run:

gdb --batch -ex "python import sys; print(f'Python {sys.version}')"

If this prints a Python version (3.9 or higher required), you're good to go. If you get an error like "Python scripting is not supported", you need to install a GDB build with Python support.

Installation

Install ChatDBG and configure GDB to load it:

python3 -m pip install ChatDBG
python3 -c 'import chatdbg; print(f"source {chatdbg.__path__[0]}/chatdbg_gdb.py")' >> ~/.gdbinit

[!NOTE] The second command runs a Python script that outputs a GDB source command, which is then appended to your ~/.gdbinit file. This tells GDB to load ChatDBG on startup. After running this, your ~/.gdbinit should contain a line like:

source /path/to/site-packages/chatdbg/chatdbg_gdb.py

Verifying Installation

To verify ChatDBG is loaded correctly:

gdb --batch -ex "python import chatdbg"

If this runs without errors, ChatDBG is properly installed. When you start GDB, you should see the prompt change to (ChatDBG gdb).

Troubleshooting

"Undefined command: why": This means ChatDBG didn't load. Check that:

1. Your ~/.gdbinit contains the source line (not Python code)
2. The path in the source line points to an existing file
3. GDB's Python can import chatdbg: gdb --batch -ex "python import chatdbg"

Python version mismatch: If GDB uses a different Python than your system default, install ChatDBG using GDB's Python:

gdb --batch -ex "python import subprocess, sys; subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'ChatDBG'])"

Then regenerate the gdbinit line using the same Python.

To use ChatDBG with Rust, you need to do two steps: modify your Cargo.toml file and add one line to your source program.

1. Add this to your Cargo.toml file:

[dependencies]
chatdbg = "0.6.2"

[profile.dev]
panic = "abort"

[profile.release]
panic = "abort"

2. In your program, apply the #[chatdbg::main] attribute to your main function:

#[chatdbg::main]
fn main() {

Now you can debug your Rust code with gdb or lldb.

(ChatDBG lldb) run
Process 85494 launched: '/Users/emery/git/ChatDBG/test/a.out' (arm64)
TEST 1
TEST -422761288
TEST 0
TEST 0
TEST 0
TEST 0
TEST 0
TEST 0
Process 85494 stopped
* thread #1, queue = 'com.apple.main-thread', stop reason = EXC_BAD_ACCESS (code=1, address=0x100056200)
    frame #0: 0x0000000100002f64 a.out`foo(n=8, b=1) at test.cpp:7:22
   4     int x[] = { 1, 2, 3, 4, 5 };
   5
   6     void foo(int n, float b) {
-> 7       cout << "TEST " << x[n * 10000] << endl;
   8     }
   9
   10    int main()
Target 0: (a.out) stopped.

Ask why to have ChatDBG provide a helpful explanation why this program failed, and suggest a fix:

(ChatDBG lldb) why
The root cause of this error is accessing an index of the array `x`
that is out of bounds. In `foo()`, the index is calculated as `n *
10000`, which can be much larger than the size of the array `x` (which
is only 5 elements). In the given trace, the program is trying to
access the memory address `0x100056200`, which is outside of the range
of allocated memory for the array `x`.

To fix this error, we need to ensure that the index is within the
bounds of the array. One way to do this is to check the value of `n`
before calculating the index, and ensure that it is less than the size
of the array divided by the size of the element. For example, we can
modify `foo()` as follows:

    ```
    void foo(int n, float b) {
      if (n < 0 || n >= sizeof(x)/sizeof(x[0])) {
        cout << "ERROR: Invalid index" << endl;
        return;
      }
      cout << "TEST " << x[n] << endl;
    }
    ```

This code checks if `n` is within the valid range, and prints an error
message if it is not. If `n` is within the range, the function prints
the value of the element at index `n` of `x`. With this modification,
the program will avoid accessing memory outside the bounds of the
array, and will print the expected output for valid indices.

Traceback (most recent call last):
  File "yourscript.py", line 9, in <module>
    print(tryme(100))
  File "yourscript.py", line 4, in tryme
    if x / i > 2:
ZeroDivisionError: division by zero
Uncaught exception. Entering post mortem debugging
Running 'cont' or 'step' will restart the program
> yourscript.py(4)tryme()
-> if x / i > 2:

Ask why to have ChatDBG provide a helpful explanation why this program failed, and suggest a fix:

(ChatDBG Pdb) why
The root cause of the error is that the code is attempting to
divide by zero in the line "if x / i > 2". As i ranges from 0 to 99,
it will eventually reach the value of 0, causing a ZeroDivisionError.

A possible fix for this would be to add a check for i being equal to
zero before performing the division. This could be done by adding an
additional conditional statement, such as "if i == 0: continue", to
skip over the iteration when i is zero. The updated code would look
like this:

def tryme(x):
    count = 0
    for i in range(100):
        if i == 0:
            continue
        if x / i > 2:
            count += 1
    return count

if __name__ == '__main__':
    print(tryme(100))