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Vulnerability Database/CVE-2025-69229

CVE-2025-69229: AIOHTTP Denial of Service Vulnerability

CVE-2025-69229 is a denial of service flaw in AIOHTTP that causes excessive CPU blocking when processing chunked messages. This article covers the technical details, affected versions, impact, and mitigation.

Updated:

CVE-2025-69229 Overview

AIOHTTP, an asynchronous HTTP client/server framework for asyncio and Python, contains a vulnerability in its chunked message handling that can lead to excessive blocking CPU usage. In versions 3.13.2 and below, processing a large number of chunks can cause the server to spend a significant amount of blocking CPU time (approximately 1 second) while handling requests. This resource exhaustion vulnerability (CWE-770) affects applications that utilize the request.read() method in their endpoints.

Critical Impact

Attackers can cause denial of service by sending specially crafted chunked HTTP requests, preventing the server from handling legitimate traffic during processing.

Affected Products

  • AIOHTTP versions 3.13.2 and below
  • Python applications using AIOHTTP's request.read() method
  • Web services and APIs built on the AIOHTTP framework

Discovery Timeline

  • 2026-01-06 - CVE CVE-2025-69229 published to NVD
  • 2026-01-08 - Last updated in NVD database

Technical Details for CVE-2025-69229

Vulnerability Analysis

The vulnerability resides in AIOHTTP's stream handling implementation within aiohttp/streams.py. When processing HTTP chunked transfer encoding, the framework inefficiently manages chunk data structures, leading to CPU exhaustion under specific conditions. The core issue relates to how the framework tracks and processes HTTP chunk splits without implementing proper resource limits or flow control mechanisms.

Applications that expose endpoints using the request.read() method are particularly vulnerable, as this method triggers the problematic code path when processing chunked request bodies. An attacker can exploit this by sending requests with numerous small chunks, causing the server to spend excessive CPU cycles managing the chunk data structures.

Root Cause

The root cause is an allocation of resources without limits (CWE-770). The original implementation used a List[int] for tracking HTTP chunk splits without any bounds on the number of chunks that could be processed before pausing. Additionally, the lack of flow control mechanisms (_low_water_chunks and _high_water_chunks) meant the server would continue processing chunks indefinitely, blocking the event loop and preventing other requests from being serviced.

Attack Vector

This vulnerability is exploitable over the network without authentication. An attacker can send maliciously crafted HTTP requests with chunked transfer encoding containing a large number of small chunks. When the target application processes these requests using request.read(), the server's CPU becomes blocked, effectively creating a denial of service condition for legitimate users.

The attack requires minimal resources from the attacker's perspective but can significantly impact server availability. Each malicious request can block the server for approximately 1 second, and multiple concurrent requests can amplify the impact.

python
         "_protocol",
         "_low_water",
         "_high_water",
+        "_low_water_chunks",
+        "_high_water_chunks",
         "_loop",
         "_size",
         "_cursor",

Source: GitHub Commit - Limit number of chunks

The patch introduces _low_water_chunks and _high_water_chunks attributes to implement flow control based on the number of chunks, not just data size.

python
         self._loop = loop
         self._size = 0
         self._cursor = 0
-        self._http_chunk_splits: Optional[List[int]] = None
+        self._http_chunk_splits: Optional[Deque[int]] = None
         self._buffer: Deque[bytes] = collections.deque()
         self._buffer_offset = 0
         self._eof = False

Source: GitHub Commit - Use collections.deque

This change replaces the List[int] with Deque[int] from collections, providing more efficient append and pop operations for managing chunk splits.

Detection Methods for CVE-2025-69229

Indicators of Compromise

  • Unusual CPU spikes on servers running AIOHTTP-based applications
  • HTTP requests with chunked transfer encoding containing abnormally high numbers of small chunks
  • Server response times degrading significantly during attack periods
  • Event loop blocking warnings in AIOHTTP logs

Detection Strategies

  • Monitor for HTTP requests with Transfer-Encoding: chunked header containing excessive chunk counts
  • Implement application performance monitoring (APM) to detect CPU blocking patterns in asyncio event loops
  • Configure web application firewalls (WAF) to flag requests with unusual chunked encoding patterns
  • Review server logs for repeated requests targeting endpoints that use request.read()

Monitoring Recommendations

  • Set up alerting for CPU utilization anomalies on AIOHTTP application servers
  • Monitor request latency percentiles to detect degradation patterns indicative of DoS attacks
  • Implement rate limiting on endpoints that process chunked request bodies
  • Track connection duration metrics to identify long-running malicious requests

How to Mitigate CVE-2025-69229

Immediate Actions Required

  • Upgrade AIOHTTP to version 3.13.3 or later immediately
  • Audit application code to identify endpoints using request.read() method
  • Implement request timeout configurations to limit processing time for individual requests
  • Consider adding rate limiting at the reverse proxy or load balancer level

Patch Information

The vulnerability is fixed in AIOHTTP version 3.13.3. The fix implements two key improvements: flow control based on chunk count (not just data size) through the introduction of _low_water_chunks and _high_water_chunks attributes, and optimization of the chunk tracking data structure by switching from List[int] to Deque[int] for better performance characteristics.

For detailed patch information, refer to the GitHub Security Advisory.

Workarounds

  • Configure reverse proxy (nginx, HAProxy) to reject requests with excessive chunk counts
  • Implement application-level request size limits before calling request.read()
  • Use request timeouts to prevent long-running request processing
  • Consider temporarily disabling chunked transfer encoding at the load balancer level if not required
bash
# Example nginx configuration to limit request body size
# Add to server or location block
client_max_body_size 10m;
client_body_timeout 30s;

# Limit chunked transfer encoding processing
chunked_transfer_encoding on;
proxy_request_buffering on;

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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