CVE-2025-61765 (GCVE-0-2025-61765)
Vulnerability from cvelistv5 – Published: 2025-10-06 16:04 – Updated: 2025-10-22 17:13
VLAI
EPSS
VEX
Title
python-socketio vulnerable to arbitrary Python code execution (RCE) through malicious pickle deserialization in certain multi-server deployments
Summary
python-socketio is a Python implementation of the Socket.IO realtime client and server. A remote code execution vulnerability in python-socketio versions prior to 5.14.0 allows attackers to execute arbitrary Python code through malicious pickle deserialization in multi-server deployments on which the attacker previously gained access to the message queue that the servers use for internal communications. When Socket.IO servers are configured to use a message queue backend such as Redis for inter-server communication, messages sent between the servers are encoded using the `pickle` Python module. When a server receives one of these messages through the message queue, it assumes it is trusted and immediately deserializes it. The vulnerability stems from deserialization of messages using Python's `pickle.loads()` function. Having previously obtained access to the message queue, the attacker can send a python-socketio server a crafted pickle payload that executes arbitrary code during deserialization via Python's `__reduce__` method. This vulnerability only affects deployments with a compromised message queue. The attack can lead to the attacker executing random code in the context of, and with the privileges of a Socket.IO server process. Single-server systems that do not use a message queue, and multi-server systems with a secure message queue are not vulnerable. In addition to making sure standard security practices are followed in the deployment of the message queue, users of the python-socketio package can upgrade to version 5.14.0 or newer, which remove the `pickle` module and use the much safer JSON encoding for inter-server messaging.
Severity
6.4 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-10-06 17:01 UTC
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/miguelgrinberg/python-socketio… | x_refsource_CONFIRM |
| https://github.com/miguelgrinberg/python-socketio… | x_refsource_MISC |
| https://www.bluerock.io/post/cve-2025-61765-bluer… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| miguelgrinberg | python-socketio |
Affected:
>= 0.8.0, < 5.14.0
|
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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