CVE-2022-32148 (GCVE-0-2022-32148)
Vulnerability from cvelistv5 – Published: 2022-08-09 20:18 – Updated: 2026-03-06 19:06
VLAI
EPSS
VEX
Title
Exposure of client IP addresses in net/http
Summary
Improper exposure of client IP addresses in net/http before Go 1.17.12 and Go 1.18.4 can be triggered by calling httputil.ReverseProxy.ServeHTTP with a Request.Header map containing a nil value for the X-Forwarded-For header, which causes ReverseProxy to set the client IP as the value of the X-Forwarded-For header.
Severity
6.5 (Medium)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-02-23 08:15 UTC
CWE
- CWE-200 - Information Exposure
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Go standard library | net/http |
Affected:
0 , < 1.17.12
(semver)
Affected: 1.18.0-0 , < 1.18.4 (semver) |
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.
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.
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