CVE-2026-40608 (GCVE-0-2026-40608)
Vulnerability from cvelistv5 – Published: 2026-04-21 17:56 – Updated: 2026-04-21 18:36
VLAI
EPSS
VEX
Title
Next AI Draw.io: Unbounded HTTP Body — Denial of Service
Summary
Next AI Draw.io is a next.js web application that integrates AI capabilities with draw.io diagrams. Prior to 0.4.15, the embedded HTTP sidecar contains three POST handlers (/api/state, /api/restore, and /api/history-svg) that process incoming requests by accumulating the entire request body into a JavaScript string without any size limitations. Node.js buffers the entire payload in the V8 heap. Sending a sufficiently large body (e.g., 500 MiB or more) will exhaust the process heap memory, leading to an Out-of-Memory (OOM) error that crashes the MCP server. This vulnerability is fixed in 0.4.15.
Severity
6.2 (Medium)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-21 18:36 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/DayuanJiang/next-ai-draw-io/se… | x_refsource_CONFIRM |
| https://github.com/DayuanJiang/next-ai-draw-io/co… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| DayuanJiang | next-ai-draw-io |
Affected:
< 0.4.15
|
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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