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CVE-2026-33626 (GCVE-0-2026-33626)

Vulnerability from cvelistv5 – Published: 2026-04-20 20:29 – Updated: 2026-04-21 19:50
VLAI Previdian
Title
LMDeploy Vulnerable to Server-Side Request Forgery (SSRF) via Vision-Language Image Loading
Summary
LMDeploy is a toolkit for compressing, deploying, and serving large language models. Versions prior to 0.12.3 have a Server-Side Request Forgery (SSRF) vulnerability in LMDeploy's vision-language module. The `load_image()` function in `lmdeploy/vl/utils.py` fetches arbitrary URLs without validating internal/private IP addresses, allowing attackers to access cloud metadata services, internal networks, and sensitive resources. Version 0.12.3 patches the issue.
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-21 17:52 UTC
CWE
  • CWE-918 - Server-Side Request Forgery (SSRF)
Impacted products
Vendor Product Version CPE status
InternLM lmdeploy Affected: < 0.12.3
guessed Create a notification for this product.
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant

Vulnerability ID: CVE-2026-33626

Status: Confirmed

Status Updated: 2026-04-24 18:15 UTC

Exploited: Yes


Timestamps
First Seen: 2026-04-24
Asserted: 2026-04-24

Scope
Notes: KEVIntel entry: LMDeploy Vulnerable to Server-Side Request Forgery (SSRF) via Vision-Language Image Loading | Affected: InternLM / lmdeploy | CVSS: 7.5 (HIGH) | Used in malware: unknown | Not yet in CISA KEV: True

Evidence

Type: Public Report

Signal: Successful Exploitation

Confidence: 70%

Source: kevintel


Details
Feed KEVIntel (kevintel.com)
Title LMDeploy Vulnerable to Server-Side Request Forgery (SSRF) via Vision-Language Image Loading
Vendor InternLM
Product lmdeploy
Added Date 2026-04-24T18:15:40.000Z
Cvss Score 7.5
Epss Score None
Cvss Severity HIGH
Epss Percentile None
Used In Malware unknown
Ahead Of Cisa Kev None
Not Yet In Cisa Kev True

References

Created: 2026-06-19 12:42 UTC | Updated: 2026-06-19 12:42 UTC
Show details on NVD website

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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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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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