Cyber Resilience

CVE-2024-45858

Published
18 September 2024
Modified
15 April 2026
CVSS Score v3.1 7.8
Click a component to see what it means
Raw vectorCVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS Score 0.0037 30th percentile
Risk Priority 57 floored blend · peak EPSS

Summary

CVE-2024-45858 is a high-severity Eval Injection (CWE-95) vulnerability in Hiddenlayer (inferred from references). Its CVSS base score is 7.8 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique JavaScript (T1059.007); ranked at the 30th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as LLM Application Platforms; in the Supply Chain and Deployment risk domain.

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

Vulnerability Data

An arbitrary code execution vulnerability exists in versions 0.2.9 up to 0.5.10 of the Guardrails AI Guardrails framework because of the way it validates XML files. If a victim user loads a maliciously crafted XML file containing Python code, the…

more

code will be passed to an eval function, causing it to execute on the user's machine.

CWE(s)

AI Security AnalysisAI

AI Category
LLM Application Platforms
Risk Domain
Supply Chain and Deployment
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Guardrails AI is an open-source framework/platform for validating and adding guardrails to LLM outputs and applications, fitting under Other Platforms as a higher-level AI tool beyond core ML libraries or NLP-specific tools.

Related Threats

MITRE ATT&CK Enterprise Techniques

T1059.007 JavaScript Execution
Adversaries may abuse various implementations of JavaScript for execution.
T1059 Command and Scripting Interpreter Execution
Adversaries may abuse command and script interpreters to execute commands, scripts, or binaries.
T1059.001 PowerShell Execution
Adversaries may abuse PowerShell commands and scripts for execution.
T1059.004 Unix Shell Execution
Adversaries may abuse Unix shell commands and scripts for execution.
T1059.005 Visual Basic Execution
Adversaries may abuse Visual Basic (VB) for execution.
T1059.006 Python Execution
Adversaries may abuse Python commands and scripts for execution.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2026-69253Shared CWE-95
CVE-2026-0769Shared CWE-95
CVE-2026-4001Shared CWE-95
CVE-2025-15551Shared CWE-95
CVE-2026-14380Shared CWE-95
CVE-2023-7245Shared CWE-95
CVE-2026-44643Shared CWE-95
CVE-2025-43466Shared CWE-95
CVE-2026-23885Shared CWE-95
CVE-2026-11422Shared CWE-95

Affected Assets

Hiddenlayer
inferred from references and description; NVD did not file a CPE for this CVE

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)

Validate
Prove the fix (OWASP ASVS)
  • 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.

PR.PS-06 mostly match
prevents

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.

finds

Security testing in development can detect eval injection vulnerabilities before deployment.

prevents

Secure development life cycle mandates input validation and safe coding practices that directly prevent eval injection.

prevents

Application security requirements include rules against dynamic code execution of untrusted input.

prevents

Secure architecture principles discourage unsafe dynamic evaluation constructs.

prevents

Secure coding explicitly requires neutralization of input before dynamic evaluation, directly mitigating eval injection.

none

Separation of environments limits the blast radius if eval injection occurs in non-production.

References