CVE-2025-49598
Raw vector
CVSS:4.0/AV:L/AC:H/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U/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-2025-49598 is a medium-severity Eval Injection (CWE-95) vulnerability. Its CVSS base score is 4.4 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique JavaScript (T1059.007); ranked at the 5th 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 SI-10 (Information Input Validation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-18308
Vulnerability Data
conda-forge-ci-setup is a package installed by conda-forge each time a build is run on CI. The conda-forge-ci-setup-feedstock setup script is vulnerable due to the unsafe use of the eval function when parsing version information from a custom-formatted meta.yaml file. An…
more
attacker controlling meta.yaml can inject malicious code into the version assignment, which is executed during file processing, leading to arbitrary code execution. Exploitation requires an attacker to modify the recipe file by manipulating the RECIPE_DIR variable and introducing a malicious meta.yaml file. While this is more feasible in CI/CD pipelines, it is uncommon in typical environments, reducing overall risk. This vulnerability is fixed in 4.15.0.
- 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.
Input validation explicitly requires neutralizing untrusted data before it reaches dynamic evaluation constructs such as eval.
Secure-development standards and tools can mandate safe coding patterns that avoid unsafe dynamic evaluation.
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 development life cycle mandates input validation and safe coding practices that directly prevent eval injection.
Application security requirements include rules against dynamic code execution of untrusted input.
Secure architecture principles discourage unsafe dynamic evaluation constructs.
Secure coding explicitly requires neutralization of input before dynamic evaluation, directly mitigating eval injection.
Separation of environments limits the blast radius if eval injection occurs in non-production.