CVE-2026-78497
Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). EPSS scores by FIRST (EPSS SIG), generated by Empirical Security. Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-78497 is a high-severity Eval Injection (CWE-95) vulnerability. Its CVSS base score is 8.4 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked at the 4th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-15 (Development Process, Standards, and Tools) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-103450
Vulnerability Data
JQ::Lite versions before 2.51 for Perl execute Perl code embedded in a query's regular expression by compiling it with string eval. The pattern given to test(), match(), or the match and =~ conditions of select() is placed in a `qr'...'`…
more
literal and compiled as source text, so a `(?{ ... })` code block in it runs without `use re 'eval'`. Single quotes in the pattern are escaped, but a code block runs in place and needs none. An attacker who supplies a query, or text that an application inserts into the pattern of one, can execute arbitrary Perl code in the calling process.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and code analysis can discover eval-injection flaws but does not stop their introduction.
Secure-development standards and tools can mandate safe coding patterns that avoid unsafe dynamic evaluation.
Input validation explicitly requires neutralizing untrusted data before it reaches dynamic evaluation constructs such as eval.
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 SDLC practices directly require input neutralization and avoidance of unsafe dynamic evaluation.
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 can detect eval injection vulnerabilities before deployment.
Secure coding explicitly requires neutralization of input before dynamic evaluation, directly mitigating eval injection.