Cyber Resilience

CVE-2017-15715

Redhat Enterprise Linux 6.0 … 7.6

High EPSS
Published
26 March 2018
Modified
21 November 2024
Patch / advisory
CVSS Score v3 8.1
Click a component to see what it means
Raw vectorCVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
EPSS Score 0.86 99.7th percentile
Risk Priority 81 floored blend · peak EPSS

Summary

CVE-2017-15715 is a high-severity Improper Input Validation (CWE-20) vulnerability in Redhat Enterprise Linux. Its CVSS base score is 8.1 (High).

Operationally, ranked in the top 0.3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

In Apache httpd 2.4.0 to 2.4.29, the expression specified in <FilesMatch> could match '$' to a newline character in a malicious filename, rather than matching only the end of the filename. This could be exploited in environments where uploads of…

more

some files are are externally blocked, but only by matching the trailing portion of the filename.

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.

T1036.007 Double File Extension Stealthconfidence: HIGH
Double file extension bypass allows malicious files to evade filename-based upload filters.
T1105 Ingress Tool Transfer Command And Controlconfidence: MEDIUM
Successful bypass enables ingress of malicious files that would otherwise be blocked.
inferred from description + CWE · MITRE ATT&CK Enterprise v19.0

CVEs Like This One

CVE-2024-39573Same product: Apache Http Server
CVE-2017-9788Same product: Apache Http Server
CVE-2025-31672Same product class: NAS / storage appliance
CVE-2018-10933Same product: Canonical Ubuntu Linux
CVE-2016-8735Same product: Canonical Ubuntu Linux
CVE-2023-1380Same product: Canonical Ubuntu Linux
CVE-2017-12617Same product: Canonical Ubuntu Linux
CVE-2023-47855Same product class: NAS / storage appliance
CVE-2023-45745Same product class: NAS / storage appliance
CVE-2025-1736Same product class: NAS / storage appliance

Affected Assets

apache
http server
2.4.0 — 2.4.29
debian
debian linux
8.0, 9.0
canonical
ubuntu linux
14.04, 16.04, 17.10, 18.04
netapp
santricity cloud connector
all versions
netapp
storage automation store
all versions
netapp
storagegrid
all versions
netapp
clustered data ontap
all versions
redhat
enterprise linux
6.0, 7.0, 7.4, 7.5, 7.6

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)
  • 6 hardening rules · 3 OS baselines
Validate
Prove the fix (OWASP ASVS)

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.

addresses: CWE-20

Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.

addresses: CWE-20

Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.

addresses: CWE-20

Directly implements checks on information inputs to reject invalid data before processing.

addresses: CWE-20

Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.

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.PS-06 mostly match
prevents

Secure SDLC practices directly require and enforce input validation during development.

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.

detects

Testing against a defined set of requirements and using code review plus vulnerability scanning forces validation of inputs and handling of unanticipated conditions, reducing the chance that malformed data will be accepted.

prevents

Secure-coding guidelines and mandatory security testing (including code scans) compel developers to validate and sanitize inputs at design and implementation time, lowering the incidence of malformed or malicious data reaching downstream components.

prevents

Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.

prevents

Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.

prevents

Requiring language-specific secure coding standards, peer review, SAST and documented mitigation of common programming errors forces validation of all inputs before they are trusted.

none

Regular automated validation of system software and data content, combined with scanning of all inbound files, enforces input validation at the boundary before untrusted content is processed.

References