CVE-2014-1858

__init__.py in f2py in NumPy before 1.8.1 allows local users to write to arbitrary files via a symlink attack on a temporary file.

Published: 2018-01-08 Last update: 2026-06-16 Assigner: [email protected] Source: [email protected]
NVD Status：Modified，CVE State: published
View at NVD, CVE.org, EUVD

CVE-2014-1858 is rated Low Risk (34.4/100): CVSS Medium severity, with low exploitation likelihood (EPSS 0.45%). Monitor for updates and reassess as exploit intelligence or EPSS changes.

Risk is dynamic; we continuously reassess and refresh what is shown on this page as upstream context changes.

Exploit prediction scoring system (EPSS) score for CVE-2014-1858

EPSS lead: Daily EPSS estimates relative likelihood of exploitation; percentile ranks this CVE among scored vulnerabilities (higher = more severe relative rank).

# Date Old EPSS score New EPSS score Delta (New - Old)
1 2026-06-19 0.46% 0.45% -0.01%
2 2026-06-15 0.04% 0.46% +0.41%
3 2025-11-30 — 0.04% —

Full EPSS history (8 records total)

Common vulnerability scoring system (CVSS) metrics for CVE-2014-1858

CVSS metrics for this CVE.

Base score Version Severity Vector Exploitability Impact Score source
5.5 3.0 MEDIUM
CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:N Click to expand
Attack vector (AV:L)
They already need access on the box, or another person has to do something wrong; it’s not a remote drive-by.
Attack complexity (AC:L)
Once they can reach the bug, pulling it off is straightforward—no weird race conditions or rare setup.
Privileges required (PR:L)
A normal user session is enough; they don’t have to be admin.
User interaction (UI:N)
Nobody has to click “OK” or open a trap file; it can work without a victim helping.
Scope (S:U)
Damage stays in the same “trust bubble” as the broken component—no big spill into unrelated systems.
Confidentiality (C:N)
Doesn’t really leak secrets in a meaningful way.
Integrity (I:H)
They could widely tamper with or forge data—trust in the data is badly hurt.
Availability (A:N)
Service keeps running; no real outage angle.
 1.8 3.6 [email protected]
2.1 2.0 LOW
AV:L/AC:L/Au:N/C:N/I:P/A:N Click to expand
Access vector (AV:L)
Requires local access to the target system.
Access complexity (AC:L)
Exploitation conditions are straightforward and predictable.
Authentication (AU:N)
No authentication is required.
Confidentiality impact (C:N)
No confidentiality impact.
Integrity impact (I:P)
Partial integrity impact.
Availability impact (A:N)
No availability impact.
 3.9 2.9 [email protected]

Weakness enumeration for CVE-2014-1858

GitHub Security Advisory for CVE-2014-1858

OS Trackers for CVE-2014-1858

vendor priority summary link
redhat low — https://access.redhat.com/security/cve/CVE-2014-1858
ubuntu low CVE-2014-1858 low priority: Ubuntu including 1 source packages (python-numpy), 15 status rows across 15 suites (artful, bionic, cosmic, lucid, precise, quantal, saucy, trusty, upstream, utopic, vivid, wily, xenial, yakkety, zesty): ignored 10, not-affected 3, DNE 1, released 1. https://ubuntu.com/security/CVE-2014-1858

Affected software / configurations for CVE-2014-1858

Vendor Product Version Raw CPE
numpy numpy < 1.8.1 cpe:2.3:a:numpy:numpy:*:*:*:*:*:*:*:*

References for CVE-2014-1858

URL Tags
http://lists.fedoraproject.org/pipermail/package-announce/2014-February/128358.html Third Party Advisory
http://lists.fedoraproject.org/pipermail/package-announce/2014-February/128781.html Third Party Advisory
http://www.openwall.com/lists/oss-security/2014/02/08/3 Mailing List Third Party Advisory
http://www.securityfocus.com/bid/65441 Third Party Advisory VDB Entry
https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737778 Mailing List Third Party Advisory
https://bugzilla.redhat.com/show_bug.cgi?id=1062009 Issue Tracking Third Party Advisory
https://exchange.xforce.ibmcloud.com/vulnerabilities/91318 Third Party Advisory VDB Entry
https://github.com/numpy/numpy/blob/maintenance/1.8.x/doc/release/1.8.1-notes.rst Third Party Advisory
https://github.com/numpy/numpy/commit/0bb46c1448b0d3f5453d5182a17ea7ac5854ee15 Third Party Advisory
https://github.com/numpy/numpy/pull/4262 Third Party Advisory
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