Security layer for AI agents: blocks prompt injection, detects fake packages, scans vulnerabilities.
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io.github.sinewaveai/agent-security-scanner-mcp is an MCP server that security layer for AI agents: blocks prompt injection, detects fake packages, scans vulnerabilities. Its tool list has not been published yet over stdio and sse, requires no API key, and scores 88/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"io-github-sinewaveai-agent-security-scanner-mcp": {
"args": [
"-y",
"agent-security-scanner-mcp"
],
"command": "npx"
}
}
}Are you the author?
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Security layer for AI agents: blocks prompt injection, detects fake packages, scans vulnerabilities.
Run this in your terminal to verify the server starts. Then let us know if it worked - your result helps other developers.
npx -y 'agent-security-scanner-mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories - click any category to see the underlying evidence.
PYSEC-2021-142
A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
PYSEC-2020-96
A vulnerability was discovered in the PyYAML library in versions before 5.3.1, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. An attacker could use this flaw to execute arbitrary code on the system by abusing the python/object/new constructor.
PYSEC-2020-176
PyYAML 5.1 through 5.1.2 has insufficient restrictions on the load and load_all functions because of a class deserialization issue, e.g., Popen is a class in the subprocess module. NOTE: this issue exists because of an incomplete fix for CVE-2017-18342.
PYSEC-2018-49
In PyYAML before 5.1, the yaml.load() API could execute arbitrary code if used with untrusted data. The load() function has been deprecated in version 5.1 and the 'UnsafeLoader' has been introduced for backward compatibility with the function.
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