Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-21357 is a high-severity Type Confusion (CWE-843) vulnerability in Microsoft Windows 10 1809. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked in the top 2% of CVEs by exploit likelihood; 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-8 (Security and Privacy Engineering Principles) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
Windows Pragmatic General Multicast (PGM) is affected by a remote code execution vulnerability tracked as CVE-2024-21357. The flaw carries a CVSS 3.1 score of 8.1 and is associated with CWE-843. It was publicly disclosed on 13 February 2024 and impacts the PGM protocol implementation in Windows.
An unauthenticated attacker can exploit the issue over the network without user interaction, although successful exploitation requires high attack complexity. Successful attacks grant the adversary full control over confidentiality, integrity, and availability on the target system.
Microsoft has published an advisory describing the vulnerability and corresponding security updates at https://msrc.microsoft.com/update-guide/vulnerability/CVE-2024-21357. The current EPSS score stands at 0.1727 with an identical recorded peak, indicating no material post-disclosure increase in observed exploitation interest.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-19069
Vulnerability Data
Windows Pragmatic General Multicast (PGM) Remote Code Execution Vulnerability
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation (including fuzzing and type-aware analysis) directly finds type-confusion flaws before deployment.
Engineering principles can require use of type-safe languages, static typing, and runtime type checks that structurally avoid allocating one type and accessing another.
Memory-protection controls limit the blast radius when a type-confusion access occurs but do not stop the flaw itself.
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 prevent type-confusion flaws via safe typing, static analysis, and code review while the control itself addresses many additional weaknesses.
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 type-confusion vulnerabilities through fuzzing and static analysis.
Secure SDLC mandates type-safe design and review that can catch type-confusion flaws.
Application security requirements can specify strong typing and interface contracts that reduce type confusion.
Secure architecture principles promote type-safe languages and memory-safety mechanisms that mitigate type confusion.
Secure coding standards directly forbid unsafe type casts and require static-analysis checks for type confusion.