Cyber Resilience

CVE-2020-36947

HighPublic PoC

Published: 27 January 2026

Published
27 January 2026
Modified
02 February 2026
KEV Added
Patch
CVSS Score v4 7.1 CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/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:X
EPSS Score 0.0001 3.0th percentile
Risk Priority 14 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2020-36947 is a high-severity SQL Injection (CWE-89) vulnerability in Librenms Librenms. Its CVSS base score is 7.1 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 3.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

The strongest mitigations our analysis identified are NIST 800-53 SI-10 (Information Input Validation) and AC-6 (Least Privilege).

Deeper analysis

CVE-2020-36947 is an authenticated SQL injection vulnerability in LibreNMS version 1.46, specifically within the MAC accounting graph endpoint. The issue, classified under CWE-89, allows attackers to manipulate the 'sort' parameter using crafted SQL injection techniques to perform time-based blind SQL injection and extract sensitive database information.

Remote attackers with low privileges (PR:L) can exploit this vulnerability over the network (AV:N) with low attack complexity (AC:L) and no user interaction (UI:N). Successful exploitation enables high confidentiality impact (C:H) with low integrity impact (I:L) and no availability impact (A:N), as reflected in the CVSS v3.1 base score of 7.1, allowing them to retrieve database contents.

Advisories and additional details are available from the LibreNMS community at https://community.librenms.org/, the project's GitHub repository at https://github.com/librenms/librenms, the official site at https://www.librenms.org, VulnCheck at https://www.vulncheck.com/advisories/librenms-mac-accounting-graph-authenticated-sql-injection, and a proof-of-concept exploit at https://www.exploit-db.com/exploits/49246. The vulnerability was published on 2026-01-27T16:16:12.040.

EU & UK References

Vulnerability details

LibreNMS 1.46 contains an authenticated SQL injection vulnerability in the MAC accounting graph endpoint that allows remote attackers to extract database information. Attackers can exploit the vulnerability by manipulating the 'sort' parameter with crafted SQL injection techniques to retrieve sensitive…

more

database contents through time-based blind SQL injection.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise TechniquesAI

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
T1213.006 Databases Collection
Adversaries may leverage databases to mine valuable information.
Why these techniques?

Authenticated SQL injection in a network-accessible application (LibreNMS) directly enables T1190 for initial exploitation and T1213.006 for extracting database contents via blind SQLi.

Confidence: HIGH · MITRE ATT&CK Enterprise v18.1

CVEs Like This One

CVE-2026-26990Same product: Librenms Librenms
CVE-2026-26988Same product: Librenms Librenms
CVE-2026-6204Same product: Librenms Librenms
CVE-2024-51092Same product: Librenms Librenms
CVE-2025-9428Same product class: network monitoring / SIEM
CVE-2012-10063Same product class: network monitoring / SIEM
CVE-2025-67255Same product class: network monitoring / SIEM
CVE-2020-36859Same product class: network monitoring / SIEM
CVE-2016-15050Same product class: network monitoring / SIEM
CVE-2021-47693Same product class: network monitoring / SIEM

Affected Assets

librenms
librenms
1.46

Mitigating Controls

Mitigating Controls (NIST 800-53 r5) AI

prevent

Requires validation and sanitization of the 'sort' parameter in the MAC accounting graph endpoint to block crafted time-based blind SQL injection payloads.

prevent

Restricts the database privileges granted to the low-privilege authenticated account used to reach the vulnerable endpoint, limiting data extraction even if injection succeeds.

detect

Enables monitoring of application and database query patterns to identify anomalous time-based blind SQL injection attempts against the MAC accounting endpoint.

References