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Req vulnerable to unbounded archive/compression extraction triggered by response content-type

High severity GitHub Reviewed Published Jun 8, 2026 in wojtekmach/req • Updated Jul 29, 2026

Package

erlang req (Erlang)

Affected versions

>= 0.1.0, < 0.6.1

Patched versions

0.6.1

Description

Summary

Req's default response pipeline auto-decodes archive and compressed bodies based on the server-supplied content-type (or URL extension) and materialises the full decompressed contents in memory with no size cap. An attacker who controls (or can redirect a victim into) an HTTP endpoint reached by Req.get!/1 can return a tiny "decompression bomb" that expands to many gigabytes on the client and exhausts the BEAM's memory.

Details

1. Archive auto-decoding. Req.Steps.decode_body/1 in lib/req/steps.ex dispatches on the response content-type (or URL extension) and calls Erlang's archive libraries with :memory, returning a [{name, bytes}] list of every entry fully decompressed in RAM: application/zip → :zip.extract(body, [:memory]), application/x-tar → :erl_tar.extract({:binary, body}, [:memory]), application/gzip / .tgz → :erl_tar.extract({:binary, body}, [:memory, :compressed]). No byte cap is enforced before decoding and no per-entry size limit is passed to :zip / :erl_tar.

2. content-encoding chaining. Req.Steps.decompress_body/1 walks the content-encoding header and chains :zlib / :brotli / :ezstd decoders, so a response advertising content-encoding: gzip, gzip, gzip, … inflates through multiple layers without bound.

3. Default-on, attacker-chosen decoder. Both steps are part of Req's default pipeline. The caller does not need to opt in, and the attacker chooses which decoder fires by setting content-type and content-encoding on their own server (or on any host reached via Req's automatic redirect following).

PoC

  1. Run an HTTP server that responds 200 with content-type: application/zip and a body that is a zip archive whose single entry is ~400 MB of zero bytes (compressed wire payload: a few hundred KB).
  2. From the victim process, call Req.get!(url) against that server (no special options, no opt-in to archive decoding).
  3. decode_body/1 dispatches on content-type, invokes :zip.extract(body, [:memory]), and the response body becomes [{~c"bomb.bin", <<400 MB of zero bytes>>}]. A sub-MB request produces hundreds of MB resident memory; layering gzip on the content-encoding path or increasing entry size scales arbitrarily.

Impact

Memory-exhaustion denial of service against any Elixir application that uses Req with its default step pipeline to fetch URLs influenced by an untrusted party, including webhook senders, link previews, OAuth/OIDC discovery clients, package mirrors, image proxies, and any Req.get!/1 call that may follow redirects to attacker-controlled hosts. No authentication is required; a single response can crash the BEAM and take down unrelated workloads on the same VM.

References

@wojtekmach wojtekmach published to wojtekmach/req Jun 8, 2026
Published by the National Vulnerability Database Jun 8, 2026
Published to the GitHub Advisory Database Jul 29, 2026
Reviewed Jul 29, 2026
Last updated Jul 29, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(36th percentile)

Weaknesses

Improper Handling of Highly Compressed Data (Data Amplification)

The product does not handle or incorrectly handles a compressed input with a very high compression ratio that produces a large output. Learn more on MITRE.

CVE ID

CVE-2026-49755

GHSA ID

GHSA-655f-mp8p-96gv

Source code

Credits

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