CVE-2026-41206
Arbitrary Code Execution via Plugin Bypass in PySpector
Publication date: 2026-04-23
Last updated on: 2026-04-29
Assigner: GitHub, Inc.
Description
Description
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| parzivalhack | pyspector | to 0.1.8 (exc) |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| CWE-184 | The product implements a protection mechanism that relies on a list of inputs (or properties of inputs) that are not allowed by policy or otherwise require other action to neutralize before additional processing takes place, but the list is incomplete. |
Attack-Flow Graph
AI Powered Q&A
How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:
The vulnerability in PySpector allows an attacker who can supply a plugin file to achieve arbitrary code execution within the PySpector process with its full privileges. This can lead to unauthorized access, modification, or execution of code on systems using PySpector.
Such unauthorized code execution and potential data compromise could negatively impact compliance with common standards and regulations like GDPR and HIPAA, which require strict controls over data confidentiality, integrity, and system security.
Because the vulnerability enables high confidentiality and integrity impact (as indicated by the CVSS score), organizations using affected versions of PySpector might face increased risk of data breaches or unauthorized data manipulation, which are critical compliance concerns under these regulations.
Therefore, until patched (in version 0.1.8), this vulnerability could undermine compliance efforts by exposing systems to risks that these standards aim to mitigate.
Can you explain this vulnerability to me?
CVE-2026-41206 is a moderate severity vulnerability in the PySpector package (versions up to 0.1.7) related to its plugin security validator. This validator uses AST-based static analysis to block dangerous code in plugins by relying on a blocklist of forbidden function names and attribute patterns. However, the blocklist is incomplete and can be bypassed using several Python constructs that are not checked.
- Bypass techniques include dynamic module loading via importlib.import_module, dynamic attribute access through dunder methods, use of the ctypes module, access to the __builtins__ dictionary, construction and execution of raw code objects, and incomplete alias resolution.
Because the validator gates plugin installation with a pass/fail result tied to a trust flag, these bypasses allow an attacker who can supply a plugin file to achieve arbitrary code execution within the PySpector process with its full privileges.
The issue was fixed in PySpector version 0.1.8.
How can this vulnerability impact me? :
If you are using a vulnerable version of PySpector (≤ 0.1.7) and allow plugin installation, an attacker who can supply a malicious plugin can execute arbitrary OS commands with the privileges of the PySpector process.
- This arbitrary code execution can compromise confidentiality and integrity of your system, as the attacker can run commands, access sensitive data, or modify system state.
- The vulnerability has a high impact on confidentiality and integrity, with a moderate overall severity score of 6.9.
Additionally, the static analysis validator provides a false sense of security because it can be trivially bypassed using standard Python libraries and constructs.
How can this vulnerability be detected on my network or system? Can you suggest some commands?
Detection of this vulnerability involves analyzing PySpector plugin files for dangerous code patterns that bypass the plugin security validator. The vulnerability arises because the validator's blocklist is incomplete and can be circumvented using certain Python constructs such as dynamic imports, attribute access, and native calls.
To detect exploitation attempts or vulnerable plugins, you can manually inspect plugin code for usage of unblocked dangerous functions or modules like importlib.import_module, ctypes, __builtins__, or dynamic attribute access patterns (e.g., __class__.__mro__).
While no specific network commands are provided, you can use static code analysis tools or scripts to scan plugin files for suspicious imports or function calls. For example, using grep or similar tools to search for keywords in plugin files:
- grep -rE 'importlib|ctypes|__builtins__|__class__|exec|eval|os\.system|subprocess' /path/to/pyspector/plugins
- Use Python AST parsing scripts to analyze plugin code for dangerous constructs that the validator misses.
Additionally, monitoring for unexpected plugin installations or executions, especially those triggering shell commands or writing files (e.g., id > /tmp/pwned), can help detect exploitation.
What immediate steps should I take to mitigate this vulnerability?
The primary immediate mitigation step is to upgrade PySpector to version 0.1.8 or later, where the plugin validation system has been fixed to comprehensively block all known bypass techniques.
Until the upgrade is applied, restrict the ability to supply or install plugins to trusted users only, as any plugin installation can lead to arbitrary code execution.
Review and audit existing plugins for suspicious code patterns that could exploit the incomplete blocklist.
Consider disabling or limiting plugin functionality if possible, or running PySpector with minimal privileges to reduce impact in case of exploitation.
Implement continuous monitoring and automated scanning of plugins using updated static analysis tools or the fixed PySpector version's validation mechanisms.