Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2021-27850 is a critical-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Apache Tapestry. Its CVSS base score is 9.8 (Critical).
Operationally, ranked in the top 0.2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2021-1359
Vulnerability Data
A critical unauthenticated remote code execution vulnerability was found all recent versions of Apache Tapestry. The affected versions include 5.4.5, 5.5.0, 5.6.2 and 5.7.0. The vulnerability I have found is a bypass of the fix for CVE-2019-0195. Recap: Before the…
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fix of CVE-2019-0195 it was possible to download arbitrary class files from the classpath by providing a crafted asset file URL. An attacker was able to download the file `AppModule.class` by requesting the URL `http://localhost:8080/assets/something/services/AppModule.class` which contains a HMAC secret key. The fix for that bug was a blacklist filter that checks if the URL ends with `.class`, `.properties` or `.xml`. Bypass: Unfortunately, the blacklist solution can simply be bypassed by appending a `/` at the end of the URL: `http://localhost:8080/assets/something/services/AppModule.class/` The slash is stripped after the blacklist check and the file `AppModule.class` is loaded into the response. This class usually contains the HMAC secret key which is used to sign serialized Java objects. With the knowledge of that key an attacker can sign a Java gadget chain that leads to RCE (e.g. CommonsBeanUtils1 from ysoserial). Solution for this vulnerability: * For Apache Tapestry 5.4.0 to 5.6.1, upgrade to 5.6.2 or later. * For Apache Tapestry 5.7.0, upgrade to 5.7.1 or later.
- CWE(s)
Related Threats
Likely ATT&CK TechniquesAI
Techniques this vulnerability likely enables, inferred from its description, weakness type, and attributed-actor tradecraft. Confidence is per-technique.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 7 hardening rules · 6 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.
Penetration testing attempts to access or extract sensitive data, revealing exposure of sensitive information to unauthorized actors.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
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.
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.
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.
Authentication verifies actor identity and is a prerequisite for access decisions, yet addresses only one facet of the broad set of exposure vectors in CWE-200.
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.
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.
Secure delivery, protected storage, and confidentiality of allocation records limit exposure of authentication material to unauthorized observers.
Requiring defined procedures, assigned roles, and technical/organizational measures for handling PII reduces the chance that sensitive personal data will be exposed to unauthorized actors through inadequate handling or missing safeguards.