CVE-2025-62496 (GCVE-0-2025-62496)
Vulnerability from cvelistv5 – Published: 2025-10-16 15:52 – Updated: 2025-10-16 17:26
VLAI
EPSS
VEX
Title
Integer overflow in js_bigint_from_string in QuickJS
Summary
A vulnerability exists in the QuickJS engine's BigInt string parsing logic (js_bigint_from_string) when attempting to create a BigInt from a string with an excessively large number of digits.
The function calculates the necessary number of bits (n_bits) required to store the BigInt using the formula:
$$\text{n\_bits} = (\text{n\_digits} \times 27 + 7) / 8 \quad (\text{for radix 10})$$
* For large input strings (e.g., $79,536,432$ digits or more for base 10), the intermediate calculation $(\text{n\_digits} \times 27 + 7)$ exceeds the maximum value of a standard signed 32-bit integer, resulting in an Integer Overflow.
* The resulting n_bits value becomes unexpectedly small or even negative due to this wrap-around.
* This flawed n_bits is then used to compute n_limbs, the number of memory "limbs" needed for the BigInt object. Since n_bits is too small, the calculated n_limbs is also significantly underestimated.
* The function proceeds to allocate a JSBigInt object using this underestimated n_limbs.
* When the function later attempts to write the actual BigInt data into the allocated object, the small buffer size is quickly exceeded, leading to a Heap Out-of-Bounds Write as data is written past the end of the allocated r->tab array.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-10-16 17:26 UTC
CWE
- CWE-190 - Integer Overflow or Wraparound
Assigner
References
2 references
Impacted products
Date Public
2025-07-24 22:00
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"cveId": "CVE-2025-62496",
"datePublished": "2025-10-16T15:52:05.654Z",
"dateReserved": "2025-10-15T08:47:41.878Z",
"dateUpdated": "2025-10-16T17:26:25.654Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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