Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:P/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-2026-16201 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability. Its CVSS base score is 5.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 24th 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-2026-45412
Vulnerability Data
A vulnerability was found in zevorn rt-claw up to 0.2.0. Affected is the function claw_net_get/claw_net_post of the file claw/services/tools/net.c of the component http_request. The manipulation results in information disclosure. The attack can be executed remotely. The exploit has been made…
more
public and could be used. The project was informed of the problem early through an issue report but has not responded yet.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Remote info disclosure in public-facing HTTP component directly enables exploitation of public-facing app (T1190) to obtain data from local system (T1005).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 15 hardening rules · 10 OS baselines
V10.4.9V11.7.1V14.1.2V14.2.4
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.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Associating and retaining security attributes with data directly supports enforcement of access control decisions across storage, processing, and transmission.
Enforces rules governing access to the system and its data from external systems based on established trust relationships.
This control requires verifying that a sharing partner's access authorizations match the information's restrictions before sharing occurs.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.
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.
PR.AA-05 directly enforces least-privilege authorization that blocks most unauthorized disclosures, yet CWE-200 also arises from logging, error messages, and side-channel paths that access controls alone do not address.
PR.DS-10 mostly prevents CWE-200 by directly eliminating unauthorized access to sensitive data-in-use, yet only partially addresses the weakness because CWE-200 spans many other exposure vectors outside runtime protection.
PR.IR-01's segmentation/zero-trust controls largely eliminate network-level unauthorized access paths that enable exposure, yet CWE-200 spans many additional vectors (API responses, logs, app logic) that network controls alone cannot close.
Hardened baselines and deviation monitoring directly eliminate most configuration-induced access-control defects, yet CWE-284 also encompasses code-level and design flaws outside the scope of configuration management alone.
Secure SDLC practices catch most exposure flaws via design, testing and release controls, yet CWE-200 spans runtime/config issues a single development outcome cannot fully close.
PR.AA-01 supplies proper credential lifecycle controls that reduce unauthorized access paths, yet leaves many other exposure vectors (error messages, logging, side channels, etc.) unaddressed.
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.
Defining and enforcing explicit access rights and restrictions for each entity directly stops the assignment of permissions that exceed what is required, eliminating the root condition that allows improper access control.
Formal authorization, role-based provisioning, and timely revocation of access rights directly stop the creation of accounts or permissions that exceed what the business actually needs.
Restricting anonymous or unknown access and encrypting high-value information limits the exposure of sensitive data that would otherwise be obtainable by unauthorized actors.
Suppressing system details, error specifics, and previous log-on information until successful authentication reduces the information an unauthenticated attacker can gather.
By requiring owners to assign sensitivity labels and corresponding handling rules, the control ensures that information is not left unmarked and therefore reduces the chance that sensitive data will be exposed to unauthorized actors.
Requiring encryption, access controls, and recipient authentication for transfers directly reduces the chance that sensitive data reaches an unauthorized observer.