CVE-2022-30631 (GCVE-0-2022-30631)
Vulnerability from cvelistv5 – Published: 2022-08-09 20:16 – Updated: 2025-10-20 17:51
VLAI
EPSS
VEX
Title
Stack exhaustion when reading certain archives in compress/gzip
Summary
Uncontrolled recursion in Reader.Read in compress/gzip before Go 1.17.12 and Go 1.18.4 allows an attacker to cause a panic due to stack exhaustion via an archive containing a large number of concatenated 0-length compressed files.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-674 - Uncontrolled Recursion
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Go standard library | compress/gzip |
Affected:
0 , < 1.17.12
(semver)
Affected: 1.18.0-0 , < 1.18.4 (semver) |
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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.
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