Heap Overflow in Fastapi with Basic Auth

A heap overflow in a FastAPI service that uses HTTP Basic Authentication can occur when user-controlled data from the Authorization header is copied into fixed-size buffers on the heap without proper length checks. Although FastAPI is a Python framework and Python manages memory automatically, a heap overflow becomes relevant when the request handling path passes credentials to an underlying native component (e.g., a C extension, a compiled library, or bindings) that performs unsafe memory operations. For example, if your FastAPI app decodes the Base64 credentials and forwards them to a native library that stores the username or password in a fixed-size C buffer, an oversized payload can corrupt heap metadata and lead to arbitrary code execution or crashes.

Basic Auth sends credentials as Base64-encoded, not encrypted, strings in the Authorization header. If the server decodes these values and uses unsafe string operations in any native dependency, an attacker can send a very long username or password, causing a heap overflow. The unauthenticated attack surface of FastAPI often includes the authentication endpoint before tokens or sessions are established, making Basic Auth a common vector for initial access testing. A middleBrick scan can detect whether your FastAPI endpoints expose authentication flows that accept large credentials and whether any native components are invoked during authentication, surfacing related security findings such as Input Validation and Unsafe Consumption.

In practice, this risk materializes when a FastAPI route parses the Authorization header and passes the decoded payload directly to an extension written in C/C++ or via ctypes. The route might look correct in Python, but the native layer may lack bounds checking. This combination exposes the heap overflow if the attacker can control the length of the decoded string and the native code trusts that input. Because the scan is unauthenticated, middleBrick can probe the authentication path with long credentials and flag anomalies in how credentials are handled, linking findings to relevant checks such as Input Validation and Data Exposure.

To mitigate heap overflow risks when using Basic Auth in FastAPI, ensure that credentials are validated in Python before any interaction with native code, and avoid passing raw user input to unsafe layers. Use well-maintained libraries for parsing Authorization headers and enforce length and format constraints. Below are concrete, working examples that demonstrate secure handling of Basic Auth in FastAPI.

Secure Basic Auth parsing with length validation

from fastapi import FastAPI, Request, HTTPException, Depends
from base64 import b64decode
import re

app = FastAPI()

def get_credentials(request: Request):
    auth = request.headers.get("Authorization")
    if not auth or not auth.startswith("Basic "):
        raise HTTPException(status_code=401, detail="Missing or invalid Authorization header")
    encoded = auth.split(" ", 1)[1]
    # Basic length guard to prevent oversized payloads
    if len(encoded) > 2048:
        raise HTTPException(status_code=400, detail="Authorization header too long")
    try:
        decoded = b64decode(encoded)
    except Exception:
        raise HTTPException(status_code=400, detail="Invalid Base64")
    parts = decoded.split(b":", 1)
    if len(parts) != 2:
        raise HTTPException(status_code=400, detail="Invalid credentials format")
    username, password = parts
    # Enforce safe length limits per policy
    if len(username) > 128 or len(password) > 128:
        raise HTTPException(status_code=400, detail="Credentials exceed length limits")
    # Optionally restrict characters to avoid injection in downstream systems
    if not re.match(r"^[\w\-\.]+$", username.decode("utf-8", errors="ignore")):
        raise HTTPException(status_code=400, detail="Invalid username characters")
    return username.decode("utf-8"), password.decode("utf-8")

@app.get("/items")
def read_items(credentials: tuple[str, str] = Depends(get_credentials)):
    username, password = credentials
    # At this point, username and password are safe to use in Python logic
    # Do not forward raw credentials to native extensions without further validation
    return {"msg": f"Hello, {username}"}

Avoid unsafe native calls with validated credentials

If you must pass credentials to a native extension, ensure the extension validates lengths and uses bounded copy operations. From Python, prefer high-level interfaces and avoid ctypes or CFFI with raw user input. If you use an external library, keep it updated and review its memory-safety practices. For example, if a hypothetical native module expects strings, pass only sanitized, length-limited values:

# Assume safe_native is a vetted extension that validates input lengths internally
def call_safe_native(username: str, password: str):
    # Validate before passing to native code
    if len(username) > 256 or len(password) > 256:
        raise ValueError("Credentials too long for native layer")
    # This is a simplified illustration; ensure the native API itself is memory-safe
    safe_native.authenticate(username, password)

In summary, mitigate heap overflow risks by validating and bounding credential lengths in Python, avoiding direct use of raw Authorization input in unsafe native code, and using vetted libraries. middleBrick can help identify whether your endpoints accept large credentials and whether authentication flows interact with native components, providing findings tied to Input Validation and Unsafe Consumption checks.