CVE-2026-54549 (GCVE-0-2026-54549)
Vulnerability from cvelistv5 – Published: 2026-09-15 17:18 – Updated: 2026-09-16 14:44
VLAI
EPSS
VEX
Title
Meta Ads MCP: Server-Side Request Forgery (SSRF) in `upload_ad_image` via Unrestricted `image_url` Fetch
Summary
Meta Ads MCP is a Model Context Protocol (MCP) server that lets AI assistants run Meta Ads. Prior to version 1.0.115, the upload_ad_image tool in meta_ads_mcp/core/ads.py passes an attacker-controlled image_url to try_multiple_download_methods() in meta_ads_mcp/core/utils.py, where httpx.AsyncClient uses follow_redirects=True and performs HTTP requests without validating the scheme, host, or resolved IP address. In a streamable-http deployment, a network caller can use any non-empty authorization value because Meta credential validation occurs after the image download, then direct the server to loopback services, private-network addresses, cloud metadata endpoints, or redirect-chained internal targets. The resulting server-side request forgery can expose internal data, invoke state-changing internal services, or disrupt reachable services. This issue is fixed in version 1.0.115.
Severity
8.3 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-16 14:44 UTC
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/pipeboard-co/meta-ads-mcp/secu… | x_refsource_CONFIRM |
| https://github.com/pipeboard-co/meta-ads-mcp/pull/138 | x_refsource_MISC |
| https://github.com/pipeboard-co/meta-ads-mcp/comm… | x_refsource_MISC |
| https://github.com/pipeboard-co/meta-ads-mcp/rele… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| pipeboard-co | meta-ads-mcp |
Affected:
< 1.0.115
|
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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