Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:L/VI:N/VA:N/SC:L/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:XSummary
CVE-2026-49979 is a medium-severity Generation of Error Message Containing Sensitive Information (CWE-209) vulnerability in Appsmith Appsmith. Its CVSS base score is 5.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Software (T1592.002); ranked at the 17th 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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-39129
Vulnerability Data
Appsmith is a platform to build admin panels, internal tools, and dashboards. Prior to 1.99, the POST /api/v1/admin/send-test-email endpoint accepts attacker-controlled smtpHost and smtpPort values and establishes a raw JavaMail TCP connection without any IP validation. This completely bypasses WebClientUtils.IP_CHECK_FILTER,…
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which only applies to Spring WebClient HTTP requests. Additionally, the raw MailException.getMessage() is returned verbatim in the API error response, enabling error-based internal port scanning and service banner enumeration. This vulnerability is fixed in 1.99.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V16.5.1V1.3.6V1.5.3V5.3.2
Mitigating Controls (NIST 800-53 r5) AI
si-11 directly requires error messages to avoid revealing exploitable information about the system or its data.
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 SDLC practices directly require sanitized error handling to prevent sensitive data disclosure.
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.
Secure coding standards explicitly forbid exposing sensitive data in errors.
Security testing can detect error messages that leak sensitive information.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.
Logging policy can require suppression of sensitive data in error messages.
Secure SDLC mandates error-handling rules that avoid leaking sensitive information.
Application security requirements can specify safe error messaging.