CVE-2024-20327
Cisco Ios Xr ≤ 7.9.21
Raw vector
CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:C/C:N/I:N/A:HSummary
CVE-2024-20327 is a high-severity Improper Input Validation (CWE-20) vulnerability in Cisco Ios Xr. Its CVSS base score is 7.4 (High).
Operationally, ranked at the 26th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-18042
Vulnerability Data
A vulnerability in the PPP over Ethernet (PPPoE) termination feature of Cisco IOS XR Software for Cisco ASR 9000 Series Aggregation Services Routers could allow an unauthenticated, adjacent attacker to crash the ppp_ma process, resulting in a denial of service…
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(DoS) condition. This vulnerability is due to the improper handling of malformed PPPoE packets that are received on a router that is running Broadband Network Gateway (BNG) functionality with PPPoE termination on a Lightspeed-based or Lightspeed-Plus-based line card. An attacker could exploit this vulnerability by sending a crafted PPPoE packet to an affected line card interface that does not terminate PPPoE. A successful exploit could allow the attacker to crash the ppp_ma process, resulting in a DoS condition for PPPoE traffic across the router.
- CWE(s)
Related Threats
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Affected Assets
Mitigating Controls
Control response
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- 6 hardening rules · 3 OS baselines
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Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.
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 and enforce input validation during development.
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.
Testing against a defined set of requirements and using code review plus vulnerability scanning forces validation of inputs and handling of unanticipated conditions, reducing the chance that malformed data will be accepted.
Secure-coding guidelines and mandatory security testing (including code scans) compel developers to validate and sanitize inputs at design and implementation time, lowering the incidence of malformed or malicious data reaching downstream components.
Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.
Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.
Requiring language-specific secure coding standards, peer review, SAST and documented mitigation of common programming errors forces validation of all inputs before they are trusted.
Regular automated validation of system software and data content, combined with scanning of all inbound files, enforces input validation at the boundary before untrusted content is processed.