CVE-2024-49768 in Waitress
Summary
by MITRE • 10/29/2024
Waitress is a Web Server Gateway Interface server for Python 2 and 3. A remote client may send a request that is exactly recv_bytes (defaults to 8192) long, followed by a secondary request using HTTP pipelining. When request lookahead is disabled (default) we won't read any more requests, and when the first request fails due to a parsing error, we simply close the connection. However when request lookahead is enabled, it is possible to process and receive the first request, start sending the error message back to the client while we read the next request and queue it. This will allow the secondary request to be serviced by the worker thread while the connection should be closed. Waitress 3.0.1 fixes the race condition. As a workaround, disable channel_request_lookahead, this is set to 0 by default disabling this feature.
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Analysis
by VulDB Data Team • 11/02/2024
The vulnerability CVE-2024-49768 affects Waitress, a Python-based Web Server Gateway Interface server that serves as an HTTP server for applications built on Python 2 and 3. This issue manifests as a race condition within the request processing mechanism that can lead to improper handling of HTTP pipelining scenarios. The vulnerability specifically targets the interaction between request lookahead functionality and connection management within the Waitress server implementation. When a remote client sends a carefully crafted request of exactly recv_bytes length (defaulting to 8192 bytes) followed by a secondary request through HTTP pipelining, the server's behavior becomes unpredictable and potentially exploitable.
The technical flaw stems from how Waitress handles concurrent request processing when request lookahead is enabled. Under normal circumstances, the server processes requests sequentially, but when lookahead is activated, it attempts to read and queue subsequent requests while still processing the current one. This creates a race condition where the server may begin sending an error response for the first malformed request while simultaneously reading and queuing the second request. The worker thread continues processing the queued secondary request even though the connection should have been terminated due to the parsing error in the first request. This behavior violates the expected HTTP protocol semantics and can lead to unexpected service behavior or potential information disclosure.
The operational impact of this vulnerability extends beyond simple service disruption to potentially enable more sophisticated attacks. When request lookahead is enabled, an attacker can exploit this race condition to inject additional requests that will be processed by the same worker thread, effectively bypassing normal connection closure logic. This creates a window where malicious requests can be executed within the context of an existing connection, potentially leading to unauthorized access or resource exhaustion. The vulnerability affects all versions of Waitress prior to 3.0.1, making it a critical concern for systems running older versions. According to CWE standards, this represents a race condition vulnerability classified under CWE-362, which deals with concurrent execution using shared resources.
The mitigation strategy involves disabling the channel_request_lookahead feature, which is set to zero by default, effectively disabling this functionality. This approach aligns with ATT&CK framework techniques related to privilege escalation and defense evasion by removing the attack surface that enables the race condition. Organizations should upgrade to Waitress version 3.0.1 or later, which includes fixes for this race condition. Additionally, network administrators should monitor for unusual HTTP pipelining patterns and implement proper connection timeout configurations. The vulnerability highlights the importance of proper synchronization mechanisms in multi-threaded web server implementations and demonstrates how seemingly minor configuration options can introduce significant security risks. Systems administrators should also consider implementing rate limiting and connection monitoring to detect and prevent exploitation attempts that rely on HTTP pipelining and request queuing behaviors.