CVE-2026-93957 (GCVE-0-2026-93957)
Vulnerability from cvelistv5 – Published: 2026-09-20 01:00 – Updated: 2026-09-22 16:03 X_Open Source
VLAI
EPSS
VEX
Title
olivier-ls PHP-FTS Filter Matching SearchEngine.php matchesSingleFilter comparison
Summary
A vulnerability has been found in olivier-ls PHP-FTS up to 1.1.3. This affects the function SearchEngine::matchesSingleFilter of the file src/SearchEngine.php of the component Filter Matching. The manipulation leads to incorrect comparison. Remote exploitation of the attack is possible. The exploit has been disclosed to the public and may be used. Upgrading to version 1.1.4 is able to mitigate this issue. The identifier of the patch is 0b2fae333d6b022da7ed4c43e2d41aa03f91dff3. It is suggested to upgrade the affected component. The vendor was contacted early, responded in a very professional manner and quickly released a fixed version of the affected product.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-22 16:03 UTC
CWE
- CWE-697 - Incorrect Comparison
Assigner
References
9 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/407916 | vdb-entrytechnical-description |
| https://vuldb.com/vuln/407916/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-93957 | third-party-advisory |
| https://vuldb.com/submit/943923 | third-party-advisory |
| https://github.com/olivier-ls/php-fts/issues/2 | issue-tracking |
| https://github.com/sumo166/CVE-apply/blob/main/ol… | broken-linkexploit |
| https://github.com/olivier-ls/php-fts/commit/0b2f… | patch |
| https://github.com/olivier-ls/php-fts/releases/ta… | patch |
| https://github.com/olivier-ls/php-fts/ | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| olivier-ls | PHP-FTS |
Affected:
1.1.0
Affected: 1.1.1 Affected: 1.1.2 Affected: 1.1.3 Unaffected: 1.1.4 cpe:2.3:a:olivier-ls:php-fts:*:*:*:*:*:*:*:* |
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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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