CVE-2026-100601 (GCVE-0-2026-100601)
Vulnerability from cvelistv5 – Published: 2026-09-26 13:22 – Updated: 2026-09-30 12:47
VLAI
EPSS
VEX
Title
ClawHub SSRF via Unchecked DNS Resolution in Profile Image
Summary
ClawHub (openclaw/clawhub) application/backend contains a server-side request forgery vulnerability in the public profile preview's image fetching. The preview accepts a user-supplied image URL and checks the textual hostname against private-address patterns, but does not validate or pin the resolved network destination, so a public-looking hostname can resolve to an internal address or change resolution between validation and connection (DNS rebinding). A maintainer-run local harness demonstrated an outbound connection to an owner-controlled loopback listener; access to production internal services, credential disclosure, and code execution were not demonstrated. The issue was confirmed at revision cbfee7343ddc867316dd9b3de6fa8856730f9f41; the complete historical affected range was not established. Fixed by PR #3683, included in revision 8c2de6c506bb4efabe3f0c2ffb8370b9e23d4650, which was deployed to clawhub.ai on 2026-09-11; self-hosted deployments should update to that revision or a later descendant. The npm CLI and OpenClaw runtime are separate products and are not affected.
Severity
5.3 (Medium)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-30 12:47 UTC
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/openclaw/clawhub/security/advi… | vendor-advisory |
| https://github.com/openclaw/clawhub/commit/8c2de6… | patch |
| https://www.vulncheck.com/advisories/clawhub-ssrf… | third-party-advisory |
Impacted products
Date Public
2026-09-11 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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