CVE-2026-49433 (GCVE-0-2026-49433)
Vulnerability from cvelistv5 – Published: 2026-06-01 19:59 – Updated: 2026-06-01 20:30 Exclusively Hosted Service
VLAI
EPSS
VEX
Title
DeepAI api.deepai.org/change_user_email CSRF
Summary
The DeepAI endpoint 'https://api.deepai.org/change_user_email' accepts POST requests without any CSRF protection. If an attacker can trick a logged-in user into clicking a malicious link, the attacker can change the user's email address and take over their account. Fixed on 2026-05-20.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · cisa-cg (v2.0.3)
Decision recorded 2026-05-29 21:18 UTC
CWE
- CWE-352 - Cross-Site Request Forgery (CSRF)
References
3 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| DeepAI | api.deepai.org |
Affected:
0 , < 2026-05-20
(custom)
Unaffected: 2026-05-20 |
guessed |
Date Public
2026-06-01 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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