high CVSS 7.5

CVE-2025-67726·Python vulnerability

Tornado is a Python web framework and asynchronous networking library. Versions 6.5.2 and below use an inefficient algorithm when parsing parameters for HTTP header values, potentially causing a DoS. The _parseparam function in httputil.py is used to parse specific HTTP header values, such as those in multipart/form-data and repeatedly calls string.count() within a nested loop while processing quoted semicolons. If an attacker sends a request with a large number of maliciously crafted parameters in a Content-Disposition header, the server's CPU usage increases quadratically (O(n²)) during parsing. Due to Tornado's single event loop architecture, a single malicious request can cause the entire server to become unresponsive for an extended period. This issue is fixed in version 6.5.3.

Severity
high
Software
Python
Fixed in
6.5.3
Published
2025-12-12

Affected versions

Until: 6.5.3

Fixed in: 6.5.3

How to fix this CVE

Update Python's Tornado web framework to version 6.5.3 or later to patch a quadratic-time parsing vulnerability in HTTP header processing. This vulnerability allows attackers to trigger CPU exhaustion through maliciously crafted Content-Disposition headers, causing denial of service. Upgrading will replace the inefficient _parseparam function with an optimized implementation that prevents exponential CPU consumption.

sudo dnf update python3-tornado

Defensia detects this vulnerability

What an exploitation attempt looks like

Sample log line indicative of exploitation attempts:

POST|PUT|PATCH request with Content-Disposition header containing multiple semicolon-delimited parameters with quoted values (e.g., Content-Disposition: form-data; name="field1"; filename="file;file;file...") paired with elevated CPU usage and request timeout errors

WAF mitigation (if patching is not yet possible)

Add this rule to your WAF to block exploitation attempts while you schedule the patch. 

Block or rate-limit requests with Content-Disposition headers containing more than 10 semicolon-delimited parameters or headers exceeding 4KB in length; implement request size limits on multipart/form-data payloads

How to check if you are affected

  1. Run `python3 -c "import tornado; print(tornado.version)"` to check the installed Tornado version; versions 6.5.2 and below are vulnerable
  2. Execute `pip show tornado | grep Version` if Tornado is installed via pip to confirm the exact version in use
  3. Search application logs for unusual spikes in CPU usage correlated with requests containing malformed Content-Disposition headers with repeated semicolons
  4. After patching, verify the fix with `python3 -c "import tornado; print(tornado.version)"` and confirm the version is 6.5.3 or higher

FAQ

What is CVE-2025-67726?

CVE-2025-67726 is a denial-of-service vulnerability in Tornado's HTTP header parsing that uses an inefficient algorithm with nested loops and repeated string operations. Attackers can exploit this by sending a single request with a specially crafted Content-Disposition header containing many malicious parameters, causing quadratic CPU consumption and server unresponsiveness.

Is CVE-2025-67726 being actively exploited?

No, CVE-2025-67726 is not listed in CISA's Known Exploited Vulnerabilities (KEV) catalog and has no publicly available exploits at this time.

What versions of Python are affected by CVE-2025-67726?

Tornado versions up to and including 6.5.2 are affected; the vulnerability is patched in Tornado 6.5.3 and later. Note that this affects the Tornado framework installed on Python, not Python itself.

How do I check if my server is vulnerable to CVE-2025-67726?

Run `pip show tornado | grep Version` or `python3 -c "import tornado; print(tornado.version)"` to check the Tornado version; if it is 6.5.2 or lower, your server is vulnerable.

Does Defensia detect CVE-2025-67726?

Yes — Defensia's CVE advisory scanner compares installed package versions against the NVD database. If Tornado is installed on a monitored server, CVE-2025-67726 will appear in your dashboard with remediation steps.

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References

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