The Cookie Monster's Tantrum: Inside CVE-2025-69230

In the world of asynchronous Python, aiohttp is the heavyweight champion. It powers everything from microservices to massive scraping bots, relying on the asyncio event loop to handle thousands of connections concurrently without breaking a sweat. The golden rule of async programming is simple: never block the event loop.

But what if I told you that you could force a purely asynchronous server to stutter, cough, and eventually choke, just by asking it to hold a few cookies? This isn't a memory corruption bug, and we aren't overflowing a buffer on the heap. This is a logic flaw in how the server complains about bad data.

CVE-2025-69230 is what I like to call a "Tantrum DoS." It relies on the fact that developers—bless their hearts—often want to know exactly what went wrong. When aiohttp encounters a cookie it doesn't like, it logs a warning. That sounds responsible, right? But when you combine eager logging with an attacker who controls the input, you get a recipe for a "Log Storm"—a scenario where a single HTTP request generates gigabytes of text and consumes enough I/O to bring a logging stack to its knees.

The vulnerability lives in aiohttp/_cookie_helpers.py, specifically within the parse_cookie_header function. This function is responsible for taking the raw Cookie header string (e.g., session=123; tracking=456) and turning it into a nice Python dictionary.

Here is the logic flaw: The parser iterates over the cookie string, splitting it by semicolons. For every segment, it checks if the cookie name matches a valid regex pattern (_COOKIE_NAME_RE). If the name is invalid (say, it contains a comma or a space where it shouldn't), the code immediately triggers a warning log.

[!NOTE] The Root Cause: The logging operation happens inside the parsing loop. The complexity of parsing is $O(n)$, but the complexity of logging is also $O(n)$.

In a normal scenario, a user might send one or two malformed cookies due to a browser bug. But an attacker isn't bound by browser standards. An attacker can craft a header that complies with the HTTP size limit (usually 8KB) but is packed densely with thousands of tiny, invalid cookie definitions.

Because aiohttp processes this lazily when request.cookies is accessed, the application code unwittingly pulls the trigger. The moment the app asks for the cookies, the parser runs, sees 3,000 bad entries, and screams into the log file 3,000 times—synchronously, in many logging configurations.

Let's look at the actual code change. It perfectly illustrates the difference between "technically correct" code and "defensive" code. In the vulnerable version, the developer prioritized immediate feedback.

Vulnerable Code (Pre-Patch):

# Inside the parsing loop...
if not _COOKIE_NAME_RE.match(key):
    # DIRECT CALL TO LOGGER INSIDE THE LOOP
    internal_logger.warning("Can not load cookie: Illegal cookie name %r", key)

Every time the regex fails, we hit internal_logger.warning. Python's logging module is robust, but it involves string formatting, lock acquisition (to ensure thread safety), and I/O operations. Doing this 5,000 times in a tight loop is a performance disaster.

Fixed Code (Commit 64629a08...):

# Before the loop
invalid_names = []
 
# Inside the loop...
if not _COOKIE_NAME_RE.match(key):
    # DEFER THE LOGGING
    invalid_names.append(key)
 
# After the loop
if invalid_names:
    # LOG ONCE, AND DOWNGRADE TO DEBUG
    internal_logger.debug(
        "Cannot load cookie. Illegal cookie names: %r", invalid_names
    )

The fix applies two critical mitigations:

1. Aggregation: Instead of logging $N$ times, we append to a list (a very cheap operation) and log exactly once at the end.
2. Severity Downgrade: They shifted the level from WARNING to DEBUG. In 99% of production environments, DEBUG logs are disabled, meaning the attack now consumes effectively zero resources.

Exploiting this requires no special tools—just curl or a simple Python script. We need to maximize the number of invalid cookie names within the server's header size limit (typically 8192 bytes).

A valid cookie looks like name=value. An invalid one (for aiohttp) might contain a forbidden character in the name. The regression test in the patch uses bad + chr(1) + name.

The Attack Chain:

1. Target Selection: Find an endpoint that reads cookies (e.g., /dashboard, /login, or any middleware that checks session tokens).
2. Payload Generation: We want short names to fit as many as possible. Let's use a,b=1. The comma is often invalid in older RFC implementations or specific regex configurations.

# Exploit Generator Concept
payload = "; ".join([f"bad,cookie{i}=x" for i in range(2000)])
headers = {"Cookie": payload}
requests.get("https://target-server.com/", headers=headers)

When the server receives this 6KB header, it accepts it (valid HTTP length). But when the application logic touches request.cookies, the parser iterates.

• Cookie 1: bad,cookie0 -> Invalid Regex -> LOG WARNING
• Cookie 2: bad,cookie1 -> Invalid Regex -> LOG WARNING
• ...
• Cookie 2000: bad,cookie1999 -> Invalid Regex -> LOG WARNING

Multiply this by 100 concurrent requests, and you are forcing the server to write 200,000 log lines per second. This trashes the disk I/O, spikes the CPU due to string formatting, and if you are paying for Splunk or Datadog by the gigabyte, it effectively burns a hole in your wallet.

You might look at the CVSS score of 2.7 and laugh. "It's just a warning log," you say. "I have 64 cores," you say.

This is a classic "Death by a Thousand Cuts."

1. Log Blindness: If I flood your logs with millions of cookie warnings, good luck finding the actual SQL injection attempts happening simultaneously. It's a smoke bomb.
2. Disk Exhaustion: If your server logs to a local file without aggressive rotation, I can fill your partition. When /var/log hits 100%, services often crash or enter read-only modes.
3. Cost Denial of Service (cDoS): Modern cloud logging is expensive. A sustained attack could generate terabytes of log data, resulting in a surprise bill that costs more than the downtime would have.
4. Performance Degradation: String formatting and I/O are synchronous blocking operations in many logging handlers. While aiohttp is async, the standard logging module is not necessarily non-blocking (depending on the handler). A massive burst of logging can stutter the event loop, increasing latency for legitimate users.

The mitigation is straightforward: Update aiohttp.

The patch effectively neutralizes the threat by batching the errors. Even if I send 5,000 invalid cookies, the server now performs one single list creation and (if debug is on) one single log write.

Remediation Steps:

1. Patch: pip install aiohttp>=3.13.3.
2. Config check: Ensure your production log level is set to INFO or WARNING. If you run DEBUG in production, you are inviting trouble regardless of this specific bug.
3. WAF Rules: Configure your Web Application Firewall to inspect Cookie headers. If a header contains an excessive number of semicolons (e.g., > 100), block the request at the edge. No legitimate user has 500 cookies.

This vulnerability serves as a reminder: Never perform unbound operations inside a loop based on user input, even if that operation seems as harmless as logger.warning().