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GHSA-v569-hp3g-36wr CVE-2026-34230

Rack has quadratic complexity in Rack::Utils.select_best_encoding via wildcard Accept-Encoding header

High RubyGems
Severity
7.5 / 10
High · CVSS 3.1
Exploit chance (EPSS)
0.45%
Chance of exploitation in the next 30 days. Higher than 38.87% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-400 Uncontrolled Resource Consumption
CWE-407 Inefficient Algorithmic Complexity
Fix
2.2.23
Upgrade rack to this version or later

Description

Summary

Rack::Utils.select_best_encoding processes Accept-Encoding values with quadratic time complexity when the header contains many wildcard (*) entries. Because this method is used by Rack::Deflater to choose a response encoding, an unauthenticated attacker can send a single request with a crafted Accept-Encoding header and cause disproportionate CPU consumption on the compression middleware path.

This results in a denial of service condition for applications using Rack::Deflater.

Details

Rack::Utils.select_best_encoding expands parsed Accept-Encoding values into a list of candidate encodings. When an entry is *, the method computes the set of concrete encodings by subtracting the encodings already present in the request:

if m == "*"
  (available_encodings - accept_encoding.map(&:first)).each do |m2|
    expanded_accept_encoding << [m2, q, preference]
  end
else
  expanded_accept_encoding << [m, q, preference]
end

Because accept_encoding.map(&:first) is evaluated inside the loop, it is recomputed for each wildcard entry. If the request contains N wildcard entries, this produces repeated scans over the full parsed header and causes quadratic behavior.

After expansion, the method also performs additional work over expanded_accept_encoding, including per-entry deletion, which further increases the cost for large inputs.

Rack::Deflater invokes this method for each request when the middleware is enabled:

Utils.select_best_encoding(ENCODINGS, Utils.parse_encodings(accept_encoding))

As a result, a client can trigger this expensive code path simply by sending a large Accept-Encoding header containing many repeated wildcard values.

For example, a request with an approximately 8 KB Accept-Encoding header containing about 1,000 *;q=0.5 entries can cause roughly 170 ms of CPU time in a single request on the Rack::Deflater path, compared to a negligible baseline for a normal header.

This issue is distinct from CVE-2024-26146. That issue concerned regular expression denial of service during Accept header parsing, whereas this issue arises later during encoding selection after the header has already been parsed.

Impact

Any Rack application using Rack::Deflater may be affected.

An unauthenticated attacker can send requests with crafted Accept-Encoding headers to trigger excessive CPU usage in the encoding selection logic. Repeated requests can consume worker time disproportionately and reduce application availability.

The attack does not require invalid HTTP syntax or large payload bodies. A single header-sized request is sufficient to reach the vulnerable code path.

Mitigation

  • Update to a patched version of Rack in which encoding selection does not repeatedly rescan the parsed header for wildcard entries.
  • Avoid enabling Rack::Deflater on untrusted traffic.
  • Apply request filtering or header size / format restrictions at the reverse proxy or application boundary to limit abusive Accept-Encoding values.

Affected versions

RubyGems

PackageVulnerableFixed in
rack
< 2.2.23
2.2.23
rack
>= 3.0.0.beta1, < 3.1.21
3.1.21
rack
>= 3.2.0, < 3.2.6
3.2.6

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

rack RubyGems → 2.2.23

bundler
bundle update rack # Gemfile: gem "rack", ">= 2.2.23"

Severity breakdown

CVSS 3.1 7.5

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Weakness

CWE-400: Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource.

How to prevent it
  • Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
  • Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, or uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution is simply difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.
  • Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
  • Implementation: Ensure that all failures in resource allocation place the system into a safe posture.

CWE-407: Inefficient Algorithmic Complexity

An algorithm in a product has an inefficient worst-case computational complexity that may be detrimental to system performance and can be triggered by an attacker, typically using crafted manipulations that ensure that the worst case is being reached.

References

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
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