CVE-2026-18040 (GCVE-0-2026-18040)
Vulnerability from cvelistv5 – Published: 2026-10-03 08:55 – Updated: 2026-10-03 08:55
VLAI
EPSS
VEX
Title
HQC leaks private key information through secret-indexed GF(2^8) tables and a secret-dependent fixed-weight sampler
Summary
In Bouncy Castle for Java before 1.86, HQC leaked secret-derived data through two side channels: its GF(2^8) arithmetic used lookup tables indexed by field elements, making the cache line touched a function of the operand, and its fixed-weight support sampler left its duplicate scan as soon as a collision was found and stored accepted positions at a secret index. Both run on secret inputs during encapsulation and decapsulation, and the sampler re-expands the secret key from its seed on every decapsulation, so an attacker able to observe cache behaviour or decapsulation timing can recover information about the HQC private key. The field arithmetic is now table-free and the sampler branch-free within a batch of candidates, with output and randomness consumption unchanged.
Severity
CWE
- CWE-208 - Observable Timing Discrepancy
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/bcgit/bc-java/wiki/CVE%E2%80%9… | vendor-advisory |
| https://github.com/bcgit/bc-java/commit/283acd810… | patch |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Legion of the Bouncy Castle Inc. | BC-JAVA |
Affected:
1.73 , < 1.86
(maven)
|
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"packageName": "bcprov",
"packageURL": "pkg:maven/org.bouncycastle/bcprov-jdk18on",
"platforms": [
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"product": "BC-JAVA",
"programFiles": [
"GF",
"HQCEngine",
"ReedSolomon",
"FastFourierTransform"
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"repo": "https://github.com/bcgit/bc-java",
"vendor": "Legion of the Bouncy Castle Inc.",
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"version": "1.73",
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}
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"type": "reporter",
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}
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"subConfidentialityImpact": "NONE",
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"valueDensity": "NOT_DEFINED",
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"source": {
"discovery": "EXTERNAL"
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"title": "HQC leaks private key information through secret-indexed GF(2^8) tables and a secret-dependent fixed-weight sampler",
"x_generator": {
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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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