Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:NSummary
CVE-2026-40114 is a high-severity SSRF (CWE-918) vulnerability in Praison Praisonai. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 20th 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 map to AC-4 (Information Flow Enforcement) and SI-10 (Information Input Validation) — 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.
CVE-2026-40114 is a server-side request forgery (SSRF) vulnerability in PraisonAI, a multi-agent teams system. In versions prior to 4.5.128, the /api/v1/runs endpoint accepts an arbitrary webhook_url in the request body without any URL validation. Upon completion of a submitted job, whether successful or failed, the server uses httpx.AsyncClient to make an HTTP POST request to the specified URL, allowing requests to unintended destinations.
An unauthenticated attacker can exploit this vulnerability over the network with low complexity and no user interaction required. By submitting a job via the endpoint with a malicious webhook_url, the attacker causes the server to send POST requests to arbitrary internal or external targets when the job finishes. This enables SSRF attacks against cloud metadata services, internal APIs, and other network-adjacent services, with a CVSS v3.1 base score of 7.2 (AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:N) reflecting low confidentiality and integrity impacts in a changed scope.
The vulnerability, associated with CWE-918 (Server-Side Request Forgery), is fixed in PraisonAI version 4.5.128. Security practitioners should upgrade to this version or later. Additional details are available in the GitHub Security Advisory at https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-8frj-8q3m-xhgm.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-21158
Vulnerability Data
PraisonAI is a multi-agent teams system. Prior to 4.5.128, the /api/v1/runs endpoint accepts an arbitrary webhook_url in the request body with no URL validation. When a submitted job completes (success or failure), the server makes an HTTP POST request to…
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this URL using httpx.AsyncClient. An unauthenticated attacker can use this to make the server send POST requests to arbitrary internal or external destinations, enabling SSRF against cloud metadata services, internal APIs, and other network-adjacent services. This vulnerability is fixed in 4.5.128.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.6V1.5.3V5.3.2V10.4.7
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
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 development practices directly include input validation and destination allow-listing that prevent SSRF.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
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.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.