CVE-2026-67232 (GCVE-0-2026-67232)
Vulnerability from cvelistv5 – Published: 2026-09-23 20:42 – Updated: 2026-09-24 15:04
VLAI
EPSS
VEX
Title
RabbitMQ: Web-MQTT decompression bomb
Summary
RabbitMQ is a messaging and streaming broker. Prior to versions 3.13.15, 4.0.20, 4.1.11, 4.2.6, and 4.3.0, The cowboy WebSocket options at line 117 set compress => true, enabling RFC 7692 permessage-deflate negotiation. The handler does not set max_frame_size, so cowboy's default of infinity applies. cowlib's cow_ws:parse_payload/9 calls zlib:inflate/2 on the compressed payload with no output-size limit. An attacker can negotiate permessage-deflate during the WebSocket upgrade and send a frame containing a zlib bomb (e.g. 50 KB → 5 GB). Decompression occurs in the connection process before websocket_handle/2 ever sees the MQTT bytes. An unauthenticated attacker can crash a RabbitMQ node running the Web-MQTT plugin by sending a single highly-compressed WebSocket frame (a few KB on the wire) that inflates to gigabytes in memory. The cowboy WebSocket handler decompresses the entire frame before the MQTT CONNECT packet is processed, so no credentials are required. Preconditions include rabbitmq_web_mqtt plugin enabled (not default, but common for browser clients) Network reachability to port 15675/15676 No authentication required. This issue is fixed in versions 3.13.15, 4.0.20, 4.1.11, 4.2.6, and 4.3.0.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-24 13:58 UTC
CWE
- CWE-409 - Improper Handling of Highly Compressed Data (Data Amplification)
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/rabbitmq/rabbitmq-server/secur… | x_refsource_CONFIRM |
| https://github.com/rabbitmq/rabbitmq-server/relea… | x_refsource_MISC |
| https://github.com/rabbitmq/rabbitmq-server/relea… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| rabbitmq | rabbitmq-server |
Affected:
>= 3.13.0, < 3.13.15
Affected: >= 4.0.0, < 4.0.20 Affected: >= 4.1.0, < 4.1.11 Affected: >= 4.2.0, < 4.2.6 |
guessed |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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