CVE-2026-108737 (GCVE-0-2026-108737)
Vulnerability from cvelistv5 – Published: 2026-10-11 12:19 – Updated: 2026-10-11 12:19
VLAI
EPSS
VEX
Title
Traccar through 6.16.0 Weak Password Recovery via TokenManager Token Purpose Confusion
Summary
Traccar through 6.16.0 contains a weak password recovery vulnerability that allows attackers to reuse password reset tokens as session credentials because TokenManager does not bind tokens to a purpose. Attackers holding a leaked reset link can obtain a full session via /api/session or change passwords via /api/password/update, retaining access for seven days even after the victim resets their password.
Severity
CWE
- CWE-640 - Weak Password Recovery Mechanism for Forgotten Password
Assigner
References
6 references
| URL | Tags |
|---|---|
| https://hackmd.io/@haind/traccar-token-purpose-co… | third-party-advisory |
| https://github.com/traccar/traccar/blob/cfab560c7… | technical-description |
| https://github.com/traccar/traccar/blob/cfab560c7… | technical-description |
| https://github.com/traccar/traccar/blob/cfab560c7… | technical-description |
| https://github.com/traccar/traccar | product |
| https://www.vulncheck.com/advisories/traccar-thro… | third-party-advisory |
Impacted products
Date Public
2026-10-10 00:00
{
"containers": {
"cna": {
"affected": [
{
"defaultStatus": "unaffected",
"packageURL": "pkg:github/traccar/traccar",
"product": "Traccar",
"repo": "https://github.com/traccar/traccar",
"vendor": "Traccar",
"versions": [
{
"lessThanOrEqual": "6.16.0",
"status": "affected",
"version": "0",
"versionType": "semver"
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}
],
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},
{
"tags": [
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],
"url": "https://github.com/traccar/traccar"
},
{
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"tags": [
"third-party-advisory"
],
"url": "https://www.vulncheck.com/advisories/traccar-through-6.16.0-weak-password-recovery-via-tokenmanager-token-purpose-confusion"
}
],
"title": "Traccar through 6.16.0 Weak Password Recovery via TokenManager Token Purpose Confusion",
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"cveMetadata": {
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"cveId": "CVE-2026-108737",
"datePublished": "2026-10-11T12:19:42.967Z",
"dateReserved": "2026-10-11T01:52:49.949Z",
"dateUpdated": "2026-10-11T12:19:42.967Z",
"state": "PUBLISHED"
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}
],
"id": "CVE-2026-108737",
"lastModified": "2026-10-11T13:17:18.173",
"metrics": {
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"cvssMetricV40": [
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"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
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"published": "2026-10-11T13:17:18.053",
"references": [
{
"source": "disclosure@vulncheck.com",
"url": "https://github.com/traccar/traccar"
},
{
"source": "disclosure@vulncheck.com",
"url": "https://github.com/traccar/traccar/blob/cfab560c79ee9c9eaa41c79c6df351e820d6284b/src/main/java/org/traccar/api/resource/PasswordResource.java#L72-L90"
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}
}
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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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