CVE-2025-62493
Memory Safety in Quickjs Project Quickjs ≤ 2025-09-13
Raw vector
CVSS:4.0/AV:A/AC:H/AT:P/PR:L/UI:P/VC:H/VI:L/VA:L/SC:H/SI:L/SA:L/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-62493 is a medium-severity Out-of-bounds Read (CWE-125) vulnerability in Quickjs Project Quickjs. Its CVSS base score is 5.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 29th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-8 (Security and Privacy Engineering Principles) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-34781
Vulnerability Data
A vulnerability exists in the QuickJS engine's BigInt string conversion logic (js_bigint_to_string1) due to an incorrect calculation of the required number of digits, which in turn leads to reading memory past the allocated BigInt structure. * The function determines the…
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number of characters (n_digits) needed for the string representation by calculating: $$ \\ \text{n\_digits} = (\text{n\_bits} + \text{log2\_radix} - 1) / \text{log2\_radix}$$ $$$$This formula is off-by-one in certain edge cases when calculating the necessary memory limbs. For instance, a 127-bit BigInt using radix 32 (where $\text{log2\_radix}=5$) is calculated to need $\text{n\_digits}=26$. * The maximum number of bits actually stored is $\text{n\_bits}=127$, which requires only two 64-bit limbs ($\text{JS\_LIMB\_BITS}=64$). * The conversion loop iterates $\text{n\_digits}=26$ times, attempting to read 5 bits in each iteration, totaling $26 \times 5 = 130$ bits. * In the final iterations of the loop, the code attempts to read data that spans two limbs: C c = (r->tab[pos] >> shift) | (r->tab[pos + 1] << (JS_LIMB_BITS - shift)); * Since the BigInt was only allocated two limbs, the read operation for r->tab[pos + 1] becomes an Out-of-Bounds Read when pos points to the last valid limb (e.g., $pos=1$). This vulnerability allows an attacker to cause the engine to read and process data from the memory immediately following the BigInt buffer. This can lead to Information Disclosure of sensitive data stored on the heap adjacent to the BigInt object.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation directly finds out-of-bounds read flaws through static analysis, fuzzing, and dynamic bounds checks.
Secure engineering principles require bounds checking and memory-safe constructs that stop out-of-bounds reads from being introduced.
Process isolation confines the effects of an out-of-bounds read to the compromised process.
Input validation rejects malformed indices or lengths that would otherwise cause reads outside buffer bounds.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure-development practices such as bounds checking and memory-safe languages directly prevent out-of-bounds reads.
Vulnerability scanning and recording can discover instances of out-of-bounds reads after code is deployed.
Routine patching replaces vulnerable code containing out-of-bounds read flaws.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development and acceptance includes fuzzing and static analysis that detect out-of-bounds read defects before release.
Logging can record evidence of an out-of-bounds read but does not prevent the weakness itself.
Secure development life cycle mandates input validation and bounds checking that directly prevent out-of-bounds reads.
Application security requirements include explicit bounds and memory-safety specifications that mitigate buffer over-reads.
Secure system architecture and engineering principles require memory-safe design patterns and runtime protections against out-of-bounds access.
Secure coding standards explicitly forbid unsafe pointer arithmetic and mandate bounds-checked reads, eliminating CWE-125.