[Security] Memory Exhaustion (OOM) and Resource Leak via crafted PAX Headers in tarfile
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Evaluación
- Dificultad
- 3/5
- Tiempo estimado
- 1-2 días
- Aptitud para principiantes
- 30/100
Línea de trabajo
The parsing loop is in TarInfo._proc_pax in Lib/tarfile.py, which builds the raw_headers list and then the pax_headers dict without any record limit. Read that loop, then reproduce the report with the attached PoC to confirm the memory growth. Done would mean a record or size cap that raises InvalidHeaderError, plus a test in Lib/test/test_tarfile.py. Because this is a security report, check with maintainers before opening a public PR.
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Descripción
Bug report
Description:
I have identified a critical Denial of Service (DoS) vulnerability in the tarfile module of Python 3.15.0. A crafted tar archive containing a malicious PAX extended header (XHDTYPE) can force the Python process to consume an extreme amount of memory instantly, leading to an Out Of Memory (OOM) crash. Furthermore, the memory is not released by the garbage collector after the extraction operation completes.
Vulnerability Details:
Location: tarfile.TarInfo._proc_pax
Root Cause: The _proc_pax function parses the PAX header data block in a while loop without enforcing any limit on the number of records. An attacker can craft a valid PAX header data block (e.g., 100MB) filled entirely with minimal-length valid records (e.g., b"5 a=\n" which is 5 bytes per record).
Impact: The parser will create over 20 million key-value pairs in the raw_headers list and subsequently in the pax_headers dictionary. This rapidly exhausts system memory. In real-world web applications (e.g., Django, Flask, CI/CD runners) that process user-uploaded tar files, this instantly kills the worker thread and can cause the entire host OS to trigger the OOM killer.
Resource Leak: After the extraction completes (returning HTTP 200), the huge memory allocation is not immediately reclaimed by Python's garbage collector due to the massive number of objects created, leaving the server in a zombie state consuming multi-gigabyte RSS memory indefinitely.
Proof of Concept (PoC):
This PoC simulates a backend service receiving a file upload and extracting it.
Attacker Script (Generates and sends the payload):
python
import tarfile
import io
import urllib.request
def create_pax_bomb():
# Minimal valid PAX record: "5 a=\n" (5 bytes)
record = b"5 a=\n"
target_size = 100 * 1024 * 1024 # 100 MB
num_records = target_size // len(record)
payload_data = record * num_records
tar_buffer = io.BytesIO()
with tarfile.open(fileobj=tar_buffer, mode="w") as tar:
info = tarfile.TarInfo("././@PaxHeader")
info.type = tarfile.XHDTYPE
info.size = len(payload_data)
tar.addfile(info, io.BytesIO(payload_data))
normal_info = tarfile.TarInfo("test.txt")
normal_info.size = 0
tar.addfile(normal_info)
return tar_buffer.getvalue()
Send via HTTP POST...
Server/Extraction Script:
python
import tarfile
When the server calls this:
try:
with tarfile.open(filepath, "r:") as tar:
tar.extractall(path=EXTRACT_DIR)
print("Extraction complete.")
except Exception as e:
print(e)
Execution Result:
The server script prints Extraction complete (or HTTP 200 success).
However, observing the process memory (Task Manager / psutil) shows memory usage instantly spiking to multiple GBs.
After the extraction finishes, the memory is not released, leaving the process hanging and unresponsive.
Suggested Fix:
Add a hard limit to the number of records or the maximum size of the PAX header that tarfile is willing to process.
For example, in _proc_pax, enforce a maximum record count (e.g., MAX_PAX_RECORDS = 10000) or a maximum total size for the raw_headers list, and raise InvalidHeaderError if exceeded.
CPython versions tested on:
3.15
Operating systems tested on:
Windows
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- Python
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