CVE-2026-24904 (GCVE-0-2026-24904)
Vulnerability from cvelistv5 – Published: 2026-01-29 21:19 – Updated: 2026-01-29 21:34
VLAI
EPSS
VEX
Title
TrustTunnel has `client_random_prefix` rule bypass via fragmented or partial TLS ClientHello
Summary
TrustTunnel is an open-source VPN protocol with a rule bypass issue in versions prior to 0.9.115. In `tls_listener.rs`, `TlsListener::listen()` peeks 1024 bytes and calls `extract_client_random(...)`. If `parse_tls_plaintext` fails (for example, a fragmented/partial ClientHello split across TCP writes), `extract_client_random` returns `None`. In `rules.rs`, `RulesEngine::evaluate` only evaluates `client_random_prefix` when `client_random` is `Some(...)`. As a result, when extraction fails (`client_random == None`), any rule that relies on `client_random_prefix` matching is skipped and evaluation falls through to later rules. As an important semantics note: `client_random_prefix` is a match condition only. It does not mean "block non-matching prefixes" by itself. A rule with `client_random_prefix = ...` triggers its `action` only when the prefix matches (and the field is available to evaluate). Non-matches (or `None`) simply do not match that rule and continue to fall through. The vulnerability is fixed in version 0.9.115.
Severity
5.3 (Medium)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-01-29 21:34 UTC
CWE
- CWE-284 - Improper Access Control
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/TrustTunnel/TrustTunnel/securi… | x_refsource_CONFIRM |
| https://github.com/TrustTunnel/TrustTunnel/commit… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| TrustTunnel | TrustTunnel |
Affected:
< 0.9.115
|
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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