CVE-2026-25532 (GCVE-0-2026-25532)
Vulnerability from cvelistv5 – Published: 2026-02-04 17:58 – Updated: 2026-02-04 19:24
VLAI
EPSS
VEX
Title
ESF-IDF is Vulnerable to WPS Enrollee Fragment Integer Underflow
Summary
ESF-IDF is the Espressif Internet of Things (IOT) Development Framework. In versions 5.5.2, 5.4.3, 5.3.4, 5.2.6, and 5.1.6, a vulnerability exists in the WPS (Wi-Fi Protected Setup) Enrollee implementation where malformed EAP-WSC packets with truncated payloads can cause integer underflow during fragment length calculation. When processing EAP-Expanded (WSC) messages, the code computes frag_len by subtracting header sizes from the total packet length. If an attacker sends a packet where the EAP Length field covers only the header and flags but omits the expected payload (such as the 2-byte Message Length field when WPS_MSG_FLAG_LEN is set), frag_len becomes negative. This negative value is then implicitly cast to size_t when passed to wpabuf_put_data(), resulting in a very large unsigned value. This issue has been patched in versions 5.5.3, 5.4.4, 5.3.5, 5.2.7, and 5.1.7.
Severity
6.3 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-02-04 19:24 UTC
CWE
- CWE-191 - Integer Underflow (Wrap or Wraparound)
Assigner
References
8 references
| URL | Tags |
|---|---|
| https://github.com/espressif/esp-idf/security/adv… | x_refsource_CONFIRM |
| https://github.com/espressif/esp-idf/commit/60f99… | x_refsource_MISC |
| https://github.com/espressif/esp-idf/commit/6f676… | x_refsource_MISC |
| https://github.com/espressif/esp-idf/commit/73a58… | x_refsource_MISC |
| https://github.com/espressif/esp-idf/commit/b209f… | x_refsource_MISC |
| https://github.com/espressif/esp-idf/commit/b88be… | x_refsource_MISC |
| https://github.com/espressif/esp-idf/commit/cad36… | x_refsource_MISC |
| https://github.com/espressif/esp-idf/commit/de288… | x_refsource_MISC |
Impacted products
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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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