CVE-2026-90938 (GCVE-0-2026-90938)
Vulnerability from cvelistv5 – Published: 2026-09-14 12:48 – Updated: 2026-09-14 13:29
VLAI
EPSS
VEX
Title
LangBot through 0.4.17 Unauthenticated Plugin Registration via WebSocket
Summary
LangBot's plugin runtime (pip package langbot_plugin) through 0.4.17 starts a debug WebSocket server on 0.0.0.0:5401 (/plugin/ws) whose authentication is gated on plugin_debug_key, which defaults to an empty string and is never set by the upstream repository, Docker image, or docker-compose (which additionally publishes port 5401 to the host); the key check is therefore skipped entirely. Any remote attacker able to reach the port can register an arbitrary "debug plugin" without credentials. Because events are broadcast to all initialized plugins without filtering, the attacker's plugin receives the full context of every IM message event (including private chats, message chains, and user/sender IDs in plaintext) and can inject forged replies, send messages as any configured bot, enumerate bot UUIDs, invoke configured LLM models, read knowledge-base contents, and register malicious tools that feed every user's LLM pipeline. Registering with "prod_mode": true causes later legitimate installations of a plugin with the same author/name to be rejected, resulting in persistent denial of service. No patched version was available at the time of publication.
Severity
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-14 13:29 UTC
CWE
- CWE-306 - Missing Authentication for Critical Function
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/langbot-app/LangBot/security/a… | vendor-advisory |
| https://www.vulncheck.com/advisories/langbot-thro… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| langbot-app | LangBot |
Affected:
0 , ≤ 0.4.17
(semver)
cpe:2.3:a:langbot:langbot:*:*:*:*:*:*:*:* |
Date Public
2026-07-31 00:00
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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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