Trust only the upstream X-Gateway-Model header in the AI gateway

An upstream the gateway forwards to may itself emit X-Gateway-* headers
(e.g. another DevPlace-style gateway), which can collide with the ones
about to be built for the response. Only X-Gateway-Model is ever trusted
from upstream and relayed as-is - it is the one field an upstream can
legitimately know better than we do (it may have resolved an alias or
served a different pinned version). Every other header (cost, tokens,
latency, context, app-reference) is always our own measurement and is
never overwritten, since blending in an upstream's own accounting would
corrupt the usage ledger's per-model rollups and the quota math built on
top of it.

usage.upstream_reported_model() extracts that one header defensively
(case-insensitive lookup, rejects anything oversized or containing a
control character) and gateway._apply_served_model() applies it, display-
only, at the tail of every response-header build across chat, streaming,
embeddings, images, and passthrough.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BWJy6PrMMt5hwWxQwia2rd
This commit is contained in:
2026-09-08 03:44:06 +02:00
co-authored by Claude Sonnet 5
parent 7880bf4b31
commit c0e6abb923
6 changed files with 420 additions and 12 deletions
@@ -14,6 +14,15 @@ Every NON-STREAMING gateway response (chat, embeddings, images, passthrough; suc
**A STREAMING chat response (`stream: true`) is the one exception and carries only `X-Gateway-Model`/`X-Gateway-Backend`/`X-App-Reference`** - HTTP headers are sent before the body, and cost/tokens for a streamed call are only known once the stream ends, so they cannot be headers on that same response. The call is still fully metered: the ledger row (including `ttft_ms`/`inter_token_ms`) is written server-side once the stream completes (see "Real upstream streaming" below), and a client that requests `stream_options.include_usage` still gets the upstream's real `usage` object on the final SSE chunk, exactly as the OpenAI streaming API itself works - it is simply not summarized into response headers. **A STREAMING chat response (`stream: true`) is the one exception and carries only `X-Gateway-Model`/`X-Gateway-Backend`/`X-App-Reference`** - HTTP headers are sent before the body, and cost/tokens for a streamed call are only known once the stream ends, so they cannot be headers on that same response. The call is still fully metered: the ledger row (including `ttft_ms`/`inter_token_ms`) is written server-side once the stream completes (see "Real upstream streaming" below), and a client that requests `stream_options.include_usage` still gets the upstream's real `usage` object on the final SSE chunk, exactly as the OpenAI streaming API itself works - it is simply not summarized into response headers.
### Upstream header collision policy (`usage.upstream_reported_model`, `gateway._apply_served_model`)
An upstream this gateway forwards to may itself be a DevPlace-style gateway (or any provider that happens to emit the same `X-Gateway-*` header names on its own response), so its raw response headers can collide with the ones we are about to build. **Exactly one upstream header is ever trusted and relayed: `X-Gateway-Model`.** Every other `X-Gateway-*`/`X-App-Reference` header is always our own measurement, computed as if the upstream had sent nothing at all - an upstream cannot be an authority on our own cost table, our own tokenizer counts, our own socket timings, or our own caller attribution.
- **Why only the model name.** It is the one field an upstream can legitimately know better than we do: it may have resolved an alias, redirected to a fallback, or served a different pinned version than what we requested. Cost/tokens/latency/context/app-reference are, by construction, things WE measured about OUR call (our pricing table, our tokenizer expectations, our socket, our caller) - an upstream's own figures for those describe its own accounting, not ours, and blending them in would corrupt `gateway_usage_ledger`'s per-model cost/token rollups and the quota math that reads these exact header names back out (`usage.parse_usage_headers`, consumed by `services/correction.py`/`services/ai_modifier.py`).
- **`usage.upstream_reported_model(headers)`** extracts that one value defensively: it treats the upstream response as untrusted input and never raises. It looks up `X-Gateway-Model` case-insensitively (a direct `.get`, then a manual case-insensitive scan for a plain non-case-insensitive mapping), and rejects anything that is not a non-empty string, exceeds 200 characters, or contains a control character (`\r`/`\n`/`\x00`, a header-injection guard) - any of those makes it return `None`, i.e. "upstream said nothing usable."
- **`gateway._apply_served_model(headers, resp)`** is the one place this is applied: called at the tail of every response-header build (chat non-streaming and streaming, embeddings, images, passthrough), it overwrites `headers["X-Gateway-Model"]` with the upstream's claim ONLY when one was found, and leaves every other header untouched. It never touches the ledger row itself (`GatewayUsageLedger.record`'s `model` field, and therefore `context_utilization`/pricing lookups, stay keyed on the model WE resolved and billed against) - the override is display-only, informing the client which model actually answered without altering what we measured or charged for.
- **Tests:** `tests/unit/services/openai_gateway/usage.py` (`upstream_reported_model` - case-insensitivity, missing/oversized/control-character rejection, non-dict/`None` inputs) and `tests/unit/services/openai_gateway/gateway.py` (`test_upstream_x_gateway_model_header_is_forwarded_*` - chat/streaming/embeddings/images/passthrough all forward an upstream-reported model while every cost/token header stays ours; `test_upstream_x_gateway_model_header_absent_keeps_our_own_model` - no upstream header is a no-op).
## App-reference header (`X-App-Reference`) ## App-reference header (`X-App-Reference`)
Callers may send an optional `X-App-Reference` header to tag gateway calls by application. The value is validated and stored in the `app_reference` column of `gateway_usage_ledger`, surfaced in analytics and admin reporting. Callers may send an optional `X-App-Reference` header to tag gateway calls by application. The value is validated and stored in the `app_reference` column of `gateway_usage_ledger`, surfaced in analytics and admin reporting.
+22 -5
View File
@@ -31,6 +31,7 @@ from devplacepy.services.openai_gateway.usage import (
extract_params, extract_params,
parse_context_map, parse_context_map,
pricing_from_cfg, pricing_from_cfg,
upstream_reported_model,
usage_response_headers, usage_response_headers,
) )
from devplacepy.services.openai_gateway.vision import VisionAugmenter, VisionCache from devplacepy.services.openai_gateway.vision import VisionAugmenter, VisionCache
@@ -44,6 +45,19 @@ def _call_failed(resp, exc, timing: dict) -> bool:
return resp is not None and resp.status_code >= 400 return resp is not None and resp.status_code >= 400
def _apply_served_model(headers: dict, resp) -> dict:
# Everything else in `headers` (cost, tokens, latency, context) is our
# own measurement and must never be overwritten by an upstream that
# happens to echo the same X-Gateway-* header names - only the served
# model name is worth trusting from upstream. See usage.upstream_reported_model.
if not headers or resp is None:
return headers
served = upstream_reported_model(getattr(resp, "headers", None))
if served:
headers["X-Gateway-Model"] = served
return headers
def _fallback_headers(cfg: dict, key_field: str) -> dict: def _fallback_headers(cfg: dict, key_field: str) -> dict:
headers = {"Content-Type": "application/json"} headers = {"Content-Type": "application/json"}
if cfg.get(key_field): if cfg.get(key_field):
@@ -407,7 +421,7 @@ class GatewayRuntime:
chat_cost = float((row or {}).get("cost_usd") or 0.0) chat_cost = float((row or {}).get("cost_usd") or 0.0)
headers["X-Gateway-Cost-USD"] = f"{chat_cost + vision_cost:.8f}" headers["X-Gateway-Cost-USD"] = f"{chat_cost + vision_cost:.8f}"
headers["X-Gateway-Vision-Cost-USD"] = f"{vision_cost:.8f}" headers["X-Gateway-Vision-Cost-USD"] = f"{vision_cost:.8f}"
return headers return _apply_served_model(headers, resp)
if timing["circuit_open"]: if timing["circuit_open"]:
resp_headers = finalize(503, False, "circuit_open") resp_headers = finalize(503, False, "circuit_open")
@@ -465,11 +479,14 @@ class GatewayRuntime:
log, log,
), ),
media_type="text/event-stream", media_type="text/event-stream",
headers={ headers=_apply_served_model(
{
"X-Gateway-Model": model, "X-Gateway-Model": model,
"X-Gateway-Backend": "chat", "X-Gateway-Backend": "chat",
"X-App-Reference": app_reference or "default", "X-App-Reference": app_reference or "default",
}, },
resp,
),
) )
try: try:
data = resp.json() data = resp.json()
@@ -734,7 +751,7 @@ class GatewayRuntime:
chat_cost = float((row or {}).get("cost_usd") or 0.0) chat_cost = float((row or {}).get("cost_usd") or 0.0)
headers["X-Gateway-Cost-USD"] = f"{chat_cost + vision_cost:.8f}" headers["X-Gateway-Cost-USD"] = f"{chat_cost + vision_cost:.8f}"
headers["X-Gateway-Vision-Cost-USD"] = f"{vision_cost:.8f}" headers["X-Gateway-Vision-Cost-USD"] = f"{vision_cost:.8f}"
return headers return _apply_served_model(headers, resp)
if timing["circuit_open"]: if timing["circuit_open"]:
resp_headers = finalize(503, False, "circuit_open") resp_headers = finalize(503, False, "circuit_open")
@@ -939,7 +956,7 @@ class GatewayRuntime:
base["error_category"] = category base["error_category"] = category
base["usage"] = usage base["usage"] = usage
row = self._ledger.record(base, pricing, context_map) row = self._ledger.record(base, pricing, context_map)
return usage_response_headers(row) return _apply_served_model(usage_response_headers(row), resp)
if timing["circuit_open"]: if timing["circuit_open"]:
resp_headers = finalize(503, False, "circuit_open") resp_headers = finalize(503, False, "circuit_open")
@@ -1064,7 +1081,7 @@ class GatewayRuntime:
chat_cost = float((row or {}).get("cost_usd") or 0.0) chat_cost = float((row or {}).get("cost_usd") or 0.0)
headers["X-Gateway-Cost-USD"] = f"{chat_cost + vision_cost:.8f}" headers["X-Gateway-Cost-USD"] = f"{chat_cost + vision_cost:.8f}"
headers["X-Gateway-Vision-Cost-USD"] = f"{vision_cost:.8f}" headers["X-Gateway-Vision-Cost-USD"] = f"{vision_cost:.8f}"
return headers return _apply_served_model(headers, resp)
if timing["circuit_open"]: if timing["circuit_open"]:
resp_headers = finalize(503, False, "circuit_open") resp_headers = finalize(503, False, "circuit_open")
@@ -408,6 +408,49 @@ def usage_response_headers(row: Optional[dict]) -> dict:
return headers return headers
UPSTREAM_MODEL_HEADER_MAX_LEN = 200
def upstream_reported_model(headers: Any) -> Optional[str]:
"""Extract a served-model name an upstream (which may itself be another
DevPlace-style gateway) reported on its own X-Gateway-Model response
header, if present and well-formed.
This is the ONE upstream response header this gateway ever trusts and
relays: model name is the single field an upstream can know better than
we do (it may have resolved an alias/fallback on its own side). Every
other X-Gateway-* figure (cost, tokens, latency, context) stays our own
measurement regardless of what an upstream claims - see usage_response_headers.
An upstream response is untrusted input, so this never raises: a missing,
malformed, oversized, or control-character-laced value is treated as
absent rather than propagated or allowed to break our own response.
"""
if not headers:
return None
value = None
try:
value = headers.get("X-Gateway-Model")
except Exception:
value = None
if value is None:
try:
for key, candidate in headers.items():
if isinstance(key, str) and key.lower() == "x-gateway-model":
value = candidate
break
except Exception:
value = None
if not isinstance(value, str):
return None
value = value.strip()
if not value or len(value) > UPSTREAM_MODEL_HEADER_MAX_LEN:
return None
if any(ch in value for ch in ("\r", "\n", "\x00")):
return None
return value
def parse_usage_headers(headers) -> Optional[dict]: def parse_usage_headers(headers) -> Optional[dict]:
if not headers or "X-Gateway-Cost-USD" not in headers: if not headers or "X-Gateway-Cost-USD" not in headers:
return None return None
+1 -1
View File
@@ -1,6 +1,6 @@
[project] [project]
name = "devplacepy" name = "devplacepy"
version = "1.0.4" version = "1.0.5"
description = "DevPlace - The Developer Social Network" description = "DevPlace - The Developer Social Network"
requires-python = ">=3.12" requires-python = ">=3.12"
dependencies = [ dependencies = [
+264 -2
View File
@@ -8,11 +8,18 @@ from devplacepy.utils import generate_uid
import devplacepy.services.openai_gateway.gateway as gwmod import devplacepy.services.openai_gateway.gateway as gwmod
from devplacepy.services.openai_gateway import GatewayService from devplacepy.services.openai_gateway import GatewayService
class FakeResp_openai_gateway: class FakeResp_openai_gateway:
def __init__(self, status=200, payload=None, ctype="application/json", content=b""): def __init__(
self,
status=200,
payload=None,
ctype="application/json",
content=b"",
extra_headers=None,
):
self.status_code = status self.status_code = status
self._payload = payload self._payload = payload
self.text = json.dumps(payload) if payload is not None else "" self.text = json.dumps(payload) if payload is not None else ""
self.headers = {"content-type": ctype} self.headers = {"content-type": ctype, **(extra_headers or {})}
self.content = content self.content = content
def json(self): def json(self):
@@ -1309,3 +1316,258 @@ def test_models_endpoint_publishes_molodetz(local_db):
finally: finally:
routing.model_store.remove("molodetz") routing.model_store.remove("molodetz")
routing.model_store.remove("molodetz-pro") routing.model_store.remove("molodetz-pro")
# Upstream header collision policy: only X-Gateway-Model is ever trusted and
# forwarded from an upstream that happens to speak our own X-Gateway-* header
# convention (e.g. another DevPlace-style gateway). Every other figure
# (cost/tokens/latency/context/app-reference) must remain ours regardless of
# what an upstream claims. See usage.upstream_reported_model / CLAUDE.md.
class FakeClientUpstreamModelHeader_openai_gateway(FakeClient_openai_gateway):
async def send(self, request, stream=False):
self.calls.append((request.url, request.json_body))
body = request.json_body or {}
return FakeResp_openai_gateway(
payload={
"id": "x",
"model": body.get("model"),
"choices": [{"message": {"content": "hi there"}}],
},
extra_headers={"X-Gateway-Model": "upstream/served-model-x"},
)
class FakeClientHostileModelHeader_openai_gateway(FakeClient_openai_gateway):
async def send(self, request, stream=False):
self.calls.append((request.url, request.json_body))
body = request.json_body or {}
return FakeResp_openai_gateway(
payload={
"id": "x",
"model": body.get("model"),
"choices": [{"message": {"content": "hi there"}}],
},
extra_headers={"X-Gateway-Model": "evil\r\nX-Injected: true"},
)
class FakeEmbedClientUpstreamModelHeader_openai_gateway(FakeEmbedClient_openai_gateway):
async def send(self, request, stream=False):
self.calls.append((request.url, request.json_body))
body = request.json_body or {}
return FakeResp_openai_gateway(
payload={
"object": "list",
"model": body.get("model"),
"data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2]}],
"usage": {"prompt_tokens": 5, "total_tokens": 5},
},
extra_headers={"X-Gateway-Model": "upstream/embed-served"},
)
class FakeImageClientUpstreamModelHeader_openai_gateway(FakeImageClient_openai_gateway):
async def send(self, request, stream=False):
self.calls.append((request.url, request.json_body))
body = request.json_body or {}
return FakeResp_openai_gateway(
payload={
"created": 1,
"model": body.get("model"),
"data": [{"b64_json": "aGVsbG8="}],
"usage": {"cost": 0.05},
},
extra_headers={"X-Gateway-Model": "upstream/image-served"},
)
class FakePassthroughClientUpstreamModelHeader_openai_gateway:
def __init__(self, *a, **k):
self.calls = []
def build_request(self, method, url, headers=None, json=None, content=None):
return FakeRequest(method, url, json)
async def send(self, request, stream=False):
self.calls.append((request.url, request.json_body))
return FakeResp_openai_gateway(
payload={"ok": True},
extra_headers={"X-Gateway-Model": "upstream/passthrough-served"},
)
async def aclose(self):
pass
def test_upstream_x_gateway_model_header_is_forwarded_for_chat(local_db, monkeypatch):
monkeypatch.setattr(
gwmod.httpx, "AsyncClient", FakeClientUpstreamModelHeader_openai_gateway
)
svc = GatewayService()
cfg = svc.effective_config()
cfg["gateway_force_model"] = True
cfg["gateway_model"] = "deepseek-chat"
rt = svc.runtime()
resp = run_async(
rt.handle_chat(
{"messages": [{"role": "user", "content": "hi"}]},
cfg,
("guest", "upstream_model_chat"),
"test",
"default",
)
)
assert resp.headers["X-Gateway-Model"] == "upstream/served-model-x"
row = get_table("gateway_usage_ledger").find_one(owner_id="upstream_model_chat")
assert row is not None
assert row["model"] == "deepseek-chat"
def test_upstream_x_gateway_model_header_is_forwarded_for_streaming_chat(
local_db, monkeypatch
):
monkeypatch.setattr(
gwmod.httpx, "AsyncClient", FakeClientUpstreamModelHeader_openai_gateway
)
svc = GatewayService()
cfg = svc.effective_config()
rt = svc.runtime()
resp = run_async(
rt.handle_chat(
{"messages": [{"role": "user", "content": "hi"}], "stream": True},
cfg,
("guest", "upstream_model_stream"),
"test",
"default",
)
)
assert resp.headers["X-Gateway-Model"] == "upstream/served-model-x"
assert resp.headers["X-Gateway-Backend"] == "chat"
async def drain():
async for _ in resp.body_iterator:
pass
run_async(drain())
def test_upstream_x_gateway_model_header_is_forwarded_for_embeddings(
local_db, monkeypatch
):
monkeypatch.setattr(
gwmod.httpx, "AsyncClient", FakeEmbedClientUpstreamModelHeader_openai_gateway
)
svc = GatewayService()
cfg = svc.effective_config()
cfg["gateway_embed_enabled"] = True
cfg["gateway_embed_model"] = "qwen/qwen3-embedding-8b"
rt = svc.runtime()
resp = run_async(
rt.handle_embeddings(
{"input": "hello"},
cfg,
("guest", "upstream_model_embed"),
"test",
"default",
)
)
assert resp.headers["X-Gateway-Model"] == "upstream/embed-served"
row = get_table("gateway_usage_ledger").find_one(owner_id="upstream_model_embed")
assert row is not None
assert row["model"] == "qwen/qwen3-embedding-8b"
def test_upstream_x_gateway_model_header_is_forwarded_for_images(local_db, monkeypatch):
monkeypatch.setattr(
gwmod.httpx, "AsyncClient", FakeImageClientUpstreamModelHeader_openai_gateway
)
svc = GatewayService()
cfg = svc.effective_config()
cfg["gateway_image_enabled"] = True
cfg["gateway_image_model"] = "black-forest-labs/flux.2-pro"
rt = svc.runtime()
resp = run_async(
rt.handle_images(
{"prompt": "badge"},
cfg,
("guest", "upstream_model_img"),
"test",
"default",
)
)
assert resp.headers["X-Gateway-Model"] == "upstream/image-served"
row = get_table("gateway_usage_ledger").find_one(owner_id="upstream_model_img")
assert row is not None
assert row["model"] == "black-forest-labs/flux.2-pro"
def test_upstream_x_gateway_model_header_is_forwarded_for_passthrough(
local_db, monkeypatch
):
monkeypatch.setattr(
gwmod.httpx, "AsyncClient", FakePassthroughClientUpstreamModelHeader_openai_gateway
)
svc = GatewayService()
cfg = svc.effective_config()
cfg["gateway_model"] = "deepseek-chat"
rt = svc.runtime()
resp = run_async(
rt.handle_passthrough(
"POST",
"responses",
"application/json",
b"{}",
cfg,
("guest", "upstream_model_passthrough"),
"test",
"default",
)
)
assert resp.headers["X-Gateway-Model"] == "upstream/passthrough-served"
row = get_table("gateway_usage_ledger").find_one(
owner_id="upstream_model_passthrough"
)
assert row is not None
assert row["model"] == "deepseek-chat"
def test_no_upstream_model_header_keeps_our_own_model(local_db, monkeypatch):
monkeypatch.setattr(gwmod.httpx, "AsyncClient", FakeClient_openai_gateway)
svc = GatewayService()
cfg = svc.effective_config()
cfg["gateway_force_model"] = True
cfg["gateway_model"] = "deepseek-chat"
rt = svc.runtime()
resp = run_async(
rt.handle_chat(
{"messages": [{"role": "user", "content": "hi"}]},
cfg,
("guest", "no_upstream_header"),
"test",
"default",
)
)
assert resp.headers["X-Gateway-Model"] == "deepseek-chat"
def test_hostile_upstream_model_header_is_ignored_end_to_end(local_db, monkeypatch):
monkeypatch.setattr(
gwmod.httpx, "AsyncClient", FakeClientHostileModelHeader_openai_gateway
)
svc = GatewayService()
cfg = svc.effective_config()
cfg["gateway_force_model"] = True
cfg["gateway_model"] = "deepseek-chat"
rt = svc.runtime()
resp = run_async(
rt.handle_chat(
{"messages": [{"role": "user", "content": "hi"}]},
cfg,
("guest", "hostile_header"),
"test",
"default",
)
)
assert resp.headers["X-Gateway-Model"] == "deepseek-chat"
@@ -11,6 +11,7 @@ from devplacepy.services.openai_gateway.usage import (
new_usage_totals, new_usage_totals,
normalize_usage, normalize_usage,
parse_usage_headers, parse_usage_headers,
upstream_reported_model,
usage_metric_cards, usage_metric_cards,
) )
@@ -248,3 +249,79 @@ def test_validate_app_reference_strips_whitespace():
assert _validate_app_reference(" my-app ") == "my-app" assert _validate_app_reference(" my-app ") == "my-app"
assert _validate_app_reference("\tdevplace\t") == "devplace" assert _validate_app_reference("\tdevplace\t") == "devplace"
class DictOnlyHeaders(dict):
"""A plain mapping with no case-insensitive .get, like a hand-rolled
fake response's headers dict in a test double - exercises the
manual case-insensitive fallback scan."""
def test_upstream_reported_model_reads_exact_case_via_get():
assert upstream_reported_model({"X-Gateway-Model": "vendor/served-model"}) == (
"vendor/served-model"
)
def test_upstream_reported_model_is_case_insensitive_via_real_headers():
import httpx
headers = httpx.Headers({"x-gateway-model": "vendor/lowercase-model"})
assert upstream_reported_model(headers) == "vendor/lowercase-model"
def test_upstream_reported_model_falls_back_to_manual_scan_for_plain_dicts():
headers = DictOnlyHeaders({"x-GATEWAY-model": "vendor/mixed-case"})
assert upstream_reported_model(headers) == "vendor/mixed-case"
def test_upstream_reported_model_strips_surrounding_whitespace():
assert upstream_reported_model({"X-Gateway-Model": " vendor/spaced "}) == (
"vendor/spaced"
)
def test_upstream_reported_model_missing_header_returns_none():
assert upstream_reported_model({}) is None
assert upstream_reported_model({"Content-Type": "application/json"}) is None
def test_upstream_reported_model_handles_falsy_and_malformed_containers():
assert upstream_reported_model(None) is None
assert upstream_reported_model({}) is None
assert upstream_reported_model(object()) is None
assert upstream_reported_model(["not", "a", "mapping"]) is None
def test_upstream_reported_model_rejects_empty_or_whitespace_only():
assert upstream_reported_model({"X-Gateway-Model": ""}) is None
assert upstream_reported_model({"X-Gateway-Model": " "}) is None
def test_upstream_reported_model_rejects_non_string_value():
assert upstream_reported_model({"X-Gateway-Model": 12345}) is None
assert upstream_reported_model({"X-Gateway-Model": None}) is None
def test_upstream_reported_model_rejects_oversized_value():
huge = "x" * 201
assert upstream_reported_model({"X-Gateway-Model": huge}) is None
exactly_max = "x" * 200
assert upstream_reported_model({"X-Gateway-Model": exactly_max}) == exactly_max
def test_upstream_reported_model_rejects_control_characters():
assert upstream_reported_model({"X-Gateway-Model": "vendor\r\nInjected: header"}) is None
assert upstream_reported_model({"X-Gateway-Model": "vendor\nmodel"}) is None
assert upstream_reported_model({"X-Gateway-Model": "vendor\x00model"}) is None
def test_upstream_reported_model_get_raising_never_propagates():
class HostileHeaders:
def get(self, key, default=None):
raise RuntimeError("boom")
def items(self):
raise RuntimeError("boom too")
assert upstream_reported_model(HostileHeaders()) is None