CVE-2026-34934
Published: 03 April 2026
Summary
CVE-2026-34934 is a critical-severity SQL Injection (CWE-89) vulnerability in Praison Praisonai. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 6.8th 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 SA-8 (Security and Privacy Engineering Principles) and SI-10 (Information Input Validation).
Threat & Defense at a Glance
Threat & Defense Details
Mitigating Controls (NIST 800-53 r5)AI
Directly prevents SQL injection by requiring validation and sanitization of untrusted thread IDs before incorporation into raw SQL queries constructed with f-strings.
Ensures timely flaw remediation by identifying and patching the SQL injection vulnerability, as demonstrated by the fix in PraisonAI version 4.5.90.
Requires application of security engineering principles, such as secure coding practices for input handling and parameterized queries, to avoid SQL injection flaws during development.
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
SQL injection in public-facing PraisonAI web application allows unauthenticated remote arbitrary SQL execution for data exfiltration/modification/deletion, directly enabling T1190 Exploit Public-Facing Application.
NVD Description
PraisonAI is a multi-agent teams system. Prior to version 4.5.90, the get_all_user_threads function constructs raw SQL queries using f-strings with unescaped thread IDs fetched from the database. An attacker stores a malicious thread ID via update_thread. When the application loads…
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the thread list, the injected payload executes and grants full database access. This issue has been patched in version 4.5.90.
Deeper analysisAI
CVE-2026-34934 is a SQL injection vulnerability (CWE-89) affecting PraisonAI, a multi-agent teams system, in versions prior to 4.5.90. The issue resides in the get_all_user_threads function, which constructs raw SQL queries using f-strings with unescaped thread IDs retrieved directly from the database. This allows injection of malicious payloads into the thread IDs, leading to arbitrary SQL execution. The vulnerability carries a CVSS v3.1 base score of 9.8 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H), indicating critical severity with high impacts on confidentiality, integrity, and availability.
An unauthenticated remote attacker can exploit this vulnerability by first storing a malicious thread ID via the update_thread function. Subsequently, when the application loads the thread list through get_all_user_threads, the injected SQL payload executes, granting the attacker full database access. This enables data exfiltration, modification, or deletion, depending on database permissions.
The vulnerability has been patched in PraisonAI version 4.5.90. Additional details are available in the GitHub security advisory at https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-9cq8-3v94-434g.
Details
- CWE(s)