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PySpector has a Plugin Sandbox Bypass leads to Arbitrary Code Execution

High severity GitHub Reviewed Published Mar 17, 2026 in ParzivalHack/PySpector • Updated Mar 18, 2026

Package

pip pyspector (pip)

Affected versions

<= 0.1.6

Patched versions

0.1.7

Description

Summary

PySpector versions <= 0.1.6 are affected by a security validation bypass in the plugin system. The validate_plugin_code() function in plugin_system.py, performs static AST analysis to block dangerous API calls before a plugin is trusted and executed. However, the internal resolve_name() helper only handles ast.Name and ast.Attribute node types, returning None for all others. When a plugin uses indirect function calls via getattr() (such as getattr(os, 'system')) the outer call's func node is of type ast.Call, causing resolve_name() to return None, and the security check to be silently skipped. The plugin incorrectly passes the trust workflow, and executes arbitrary system commands on the user's machine when loaded.

Impact

An attacker who can deliver a malicious plugin file to a PySpector user and convince them to install it, can achieve arbitrary code execution on the user's local machine. Exploitation requires the victim to explicitly run pyspector plugin install --trust on the malicious file (a deliberate multi-step action that meaningfully limits the attack surface compared to passive vulnerabilities). However, the bypass directly undermines the security guarantee that validate_plugin_code() is designed to provide. Once the plugin is trusted and executed, the following is achievable:

  • Full read/write access to the local filesystem
  • Exfiltration of sensitive data and environment variables (i.e. API keys, credentials, etc...)
  • Establishment of persistence mechanisms
  • Lateral movement in CI/CD environments where PySpector runs with elevated permissions (pre-commit hooks and scheduled scans)

Any user of PySpector who installs third-party plugins outside the official repository is potentially affected.

PoC

The following steps reproduce the vulnerability on PySpector <= 0.1.6:

  1. Create a malicious plugin file that uses getattr-based indirect calls to bypass AST validation, and confirm the validator incorrectly marks it as safe:

image

2. Run PySpector Plugin Validator module (this confirms the validator incorrectly marks the plugin as safe):

image

3. Install and trust the plugin through the normal PySpector workflow:

pyspector plugin install /tmp/evil_plugin.py --trust
4. Execute the plugin, during a scan:
pyspector scan /any/target --plugin evil

References

@ParzivalHack ParzivalHack published to ParzivalHack/PySpector Mar 17, 2026
Published to the GitHub Advisory Database Mar 18, 2026
Reviewed Mar 18, 2026
Last updated Mar 18, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Local
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction Active
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability Low
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Incomplete List of Disallowed Inputs

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. Learn more on MITRE.

CVE ID

CVE-2026-33139

GHSA ID

GHSA-v3xv-8vc3-h2m6

Source code

Credits

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