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  <updated>2026-10-06T04:25:41.547942+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>csirt@opendfir.org</email>
  </author>
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  <entry>
    <id>https://cve.radiocsirt.org/vuln/euvd-2026-291419</id>
    <title>EUVD-2026-291419</title>
    <updated>2026-10-06T04:25:41.609857+00:00</updated>
    <content>EUVD-2026-291419</content>
    <link href="https://cve.radiocsirt.org/vuln/euvd-2026-291419"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/fkie_cve-2026-40159</id>
    <title>fkie_cve-2026-40159</title>
    <updated>2026-10-06T04:25:41.609895+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml">
        <p>PraisonAI is a multi-agent teams system. Prior to 4.5.128, PraisonAI’s MCP (Model Context Protocol) integration allows spawning background servers via stdio using user-supplied command strings (e.g., MCP("npx -y @smithery/cli ...")). These commands are executed through Python’s subprocess module. By default, the implementation forwards the entire parent process environment to the spawned subprocess. As a result, any MCP command executed in this manner inherits all environment variables from the host process, including sensitive data such as API keys, authentication tokens, and database credentials. This behavior introduces a security risk when untrusted or third-party commands are used. In common scenarios where MCP tools are invoked via package runners such as npx -y, arbitrary code from external or potentially compromised packages may execute with access to these inherited environment variables. This creates a risk of unintended credential exposure and enables potential supply chain attacks through silent exfiltration of secrets. This vulnerability is fixed in 4.5.128.</p>
      </div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/fkie_cve-2026-40159"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-pj2r-f9mw-vrcq</id>
    <title>GHSA-pj2r-f9mw-vrcq — PraisonAI Vulnerable to Sensitive Environment Variable Exposure via Untrusted MCP Subprocess Execution</title>
    <updated>2026-10-06T04:25:41.609938+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> PyPI: PraisonAI</p>
<p>PraisonAI’s MCP (Model Context Protocol) integration allows spawning background servers via stdio using user-supplied command strings (e.g., `MCP("npx -y @smithery/cli ...")`). These commands are executed through Python’s `subprocess` module. By default, the implementation **forwards the entire parent process environment** to the spawned subprocess:</p>
<p>```python
# src/praisonai-agents/praisonaiagents/mcp/mcp.py
env = kwargs.get('env', {})
if not env:
    env = os.environ.copy()
```</p>
<p>As a result, any MCP command executed in this manner inherits all environment variables from the host process, including sensitive data such as API keys, authentication tokens, and database credentials.</p>
<p>This behavior introduces a security risk when untrusted or third-party commands are used. In common scenarios where MCP tools are invoked via package runners such as `npx -y`, arbitrary code from external or potentially compromised packages may execute with access to these inherited environment variables. This creates a risk of unintended credential exposure and enables potential supply chain attacks through silent exfiltration of secrets.</p>
<p>## Reproducing the Attack
1. Export a secret key: `export SUPER_SECRET_KEY=123456_pwned`
2. Start an MCP tool locally that dumps its inherited environment:
```python
from praisonaiagents.mcp import MCP
# The underlying MCP library spawns this command via subprocess and it dumps the variables
mcp = MCP('python -c "import os, json; print(json.dumps(dict(os.enviro…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-pj2r-f9mw-vrcq"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/pysec-2026-2918</id>
    <title>PYSEC-2026-2918 — PraisonAI Vulnerable to Sensitive Environment Variable Exposure via Untrusted MCP Subprocess Execution</title>
    <updated>2026-10-06T04:25:41.609990+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> PyPI: praisonai</p>
<p>PraisonAI’s MCP (Model Context Protocol) integration allows spawning background servers via stdio using user-supplied command strings (e.g., `MCP("npx -y @smithery/cli ...")`). These commands are executed through Python’s `subprocess` module. By default, the implementation **forwards the entire parent process environment** to the spawned subprocess:</p>
<p>```python
# src/praisonai-agents/praisonaiagents/mcp/mcp.py
env = kwargs.get('env', {})
if not env:
    env = os.environ.copy()
```</p>
<p>As a result, any MCP command executed in this manner inherits all environment variables from the host process, including sensitive data such as API keys, authentication tokens, and database credentials.</p>
<p>This behavior introduces a security risk when untrusted or third-party commands are used. In common scenarios where MCP tools are invoked via package runners such as `npx -y`, arbitrary code from external or potentially compromised packages may execute with access to these inherited environment variables. This creates a risk of unintended credential exposure and enables potential supply chain attacks through silent exfiltration of secrets.</p>
<p>## Reproducing the Attack
1. Export a secret key: `export SUPER_SECRET_KEY=123456_pwned`
2. Start an MCP tool locally that dumps its inherited environment:
```python
from praisonaiagents.mcp import MCP
# The underlying MCP library spawns this command via subprocess and it dumps the variables
mcp = MCP('python -c "import os, json; print(json.dumps(dict(os.enviro…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/pysec-2026-2918"/>
  </entry>
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