Memory Leak in Fastapi with Hmac Signatures

A Memory Leak in FastAPI when HMAC signatures are involved typically stems from how request bodies and signature verification buffers are handled across asynchronous calls. When a FastAPI endpoint reads the request body for HMAC verification (e.g., using request.body()) and then also forwards or re-reads the body for downstream processing, the body may be retained in memory because it is not streamed or released deterministically. This is common when middleware or dependency functions consume the stream once for signature validation and later code attempts to read it again, causing copies to accumulate in memory under sustained load.

HMAC signature verification in FastAPI often involves computing a digest over the raw payload using a shared secret. If the implementation does not use a streaming approach and instead loads the entire body into memory (e.g., via await request.body()) for each request without cleaning up references, and if the application processes large or numerous payloads, the runtime may hold onto buffers longer than necessary. This pattern becomes risky when combined with long-lived background tasks or when responses are generated slowly, as buffers remain pinned. In extreme cases, an attacker can induce higher memory consumption by sending many requests with sizable bodies, observing behavior changes that may hint at an insecure deployment, which middleBrick flags as a potential Data Exposure or Unsafe Consumption finding during unauthenticated scans.

Additionally, if HMAC verification logic is implemented inside a dependency that is reused across routes, and that dependency retains references to request state (for example, attaching the raw body to the request state for later use), memory can accumulate across requests. This is especially relevant when the application also performs OpenAPI/Swagger spec analysis with full $ref resolution, as tooling may introspect payload shapes and inadvertently encourage retaining structured copies of requests for validation. middleBrick’s 12 security checks run in parallel and can surface such risks by correlating runtime behavior with spec definitions, highlighting patterns where signature verification and body consumption interact poorly, leading to a higher risk score.

To remediate memory concerns while preserving HMAC integrity in FastAPI, use streaming body consumption and avoid retaining the full request payload. Prefer reading the body once, computing the signature, and then processing the payload in a forward-only manner. Below are concrete, working examples that demonstrate a safer pattern.

Example 1: Stream-based HMAC verification without duplicating the body

import hashlib
import hmac
from fastapi import FastAPI, Request, Response, status
from fastapi.responses import JSONResponse

app = FastAPI()

SECRET = b"super-secret-key"

def verify_hmac(body: bytes, signature_header: str) -> bool:
    expected = hmac.new(SECRET, body, hashlib.sha256).hexdigest()
    return hmac.compare_digest(expected, signature_header)

@app.post("/secure")
async def secure_endpoint(request: Request):
    # Read the body as a single chunk (for moderate-sized payloads)
    body = await request.body()
    signature = request.headers.get("X-Signature")
    if not signature or not verify_hmac(body, signature):
        raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid signature")
    # Parse JSON only after successful verification, without keeping extra copies
    payload = JSONResponse.__custom_parse__(body)  # illustrative; use json.loads in practice
    # Process payload
    return {"status": "ok"}

Example 2: Streaming approach for large payloads to limit memory retention

import hashlib
import hmac
from fastapi import FastAPI, Request, Response, status
from fastapi.responses import JSONResponse
import io

app = FastAPI()

SECRET = b"super-secret-key"

def verify_hmac_stream(stream, signature_header: str) -> bool:
    hasher = hashlib.sha256()
    h = hmac.new(SECRET, digestmod=hasher)
    # Read in chunks to avoid holding the entire body in memory at once
    chunk = await stream.read(8192)
    while chunk:
        h.update(chunk)
        chunk = await stream.read(8192)
    expected = h.hexdigest()
    return hmac.compare_digest(expected, signature_header)

@app.post("/secure-stream")
async def secure_stream_endpoint(request: Request):
    signature = request.headers.get("X-Signature")
    if not signature:
        raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Missing signature")
    # Access the body stream directly; do not call request.body() prematurely
    if not verify_hmac_stream(request.stream, signature):
        raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid signature")
    # At this point the stream has been consumed; if you need the payload again,
    # re-initialize or buffer only what’s necessary for business logic
    return {"status": "ok"}

Key practices to reduce memory pressure:

• Read the request body once and avoid multiple calls to await request.body() within the same request lifecycle.
• Use chunked streaming for large payloads and update the HMAC incrementally.
• Do not attach raw body buffers to long-lived objects or cache them inadvertently (e.g., in globals or request state that persists across requests).
• Ensure background tasks or async loops do not hold references to request bodies after the response is sent.
• Validate and parse the payload immediately after signature verification, then release references to the raw bytes as soon as possible.

These patterns help keep memory footprint predictable and align with secure handling of HMAC-signed requests in FastAPI. middleBrick’s CLI can be used to scan endpoints and validate that runtime behavior does not expose excessive memory retention or unsafe consumption patterns.