CVE-2026-48998 (GCVE-0-2026-48998)
Vulnerability from cvelistv5 – Published: 2026-06-11 12:34 – Updated: 2026-06-11 16:05
VLAI
EPSS
VEX
Title
guzzlehttp/psr7 has Host Confusion via Authority Reinterpretation
Summary
guzzlehttp/psr7 is a PSR-7 HTTP message library implementation in PHP. Versions prior to 2.10.2 contain improper Host header validation when parsing raw HTTP request messages and when deriving a server request URI from server variables. An attacker can provide a malformed Host header containing URI authority delimiters, such as `trusted.example@evil.example`. When the Host value is used to construct a URI, the malformed value can be reinterpreted as URI userinfo and host. This can cause the PSR-7 request URI host to differ from the original Host header value. Applications are affected if they parse attacker-controlled raw HTTP requests with `GuzzleHttp\Psr7\Message::parseRequest()` or the legacy 1.x `GuzzleHttp\Psr7\parse_request()` function, or if they build server requests from attacker-controlled server variables, then rely on the resulting URI host for routing, allow-list checks, or forwarding decisions. In affected forwarding or gateway scenarios, this may cause requests or credentials to be sent to an unintended host. The issue is patched in `2.10.2`. `1.x` is end-of-life and will not receive a patch. Some workarounds are available. Validate the `Host` header as `uri-host [ ":" port ]` before calling `Message::parseRequest()` or legacy `parse_request()` on untrusted HTTP request data, or before deriving routing and forwarding decisions from a parsed request URI. Reject Host values containing userinfo, path, query, or fragment delimiters.
Severity
5.3 (Medium)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-11 16:05 UTC
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/guzzle/psr7/security/advisorie… | x_refsource_CONFIRM |
Impacted products
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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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