CWE-614 Details

CWE-614

Sensitive Cookie in HTTPS Session Without 'Secure' Attribute
Draft
2007-05-07
00h00 +00:00
2025-12-11
00h00 +00:00
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Name: Sensitive Cookie in HTTPS Session Without 'Secure' Attribute

The Secure attribute for sensitive cookies in HTTPS sessions is not set.

Allgemeine Informationen

Einführungsmodi

Implementation

Anwendbare Plattformen

Technologien

Class: Web Based (Undetermined)

Häufige Konsequenzen

Bereich Auswirkung Wahrscheinlichkeit
ConfidentialityRead Application Data

Note: Omitting the secure flag makes it possible for the user agent to send the cookies in plaintext over an HTTP session.

Beobachtete Beispiele

Referenzen Beschreibung

CVE-2024-47833

python library for ML and data science does not use the Secure flag for session cookies

CVE-2004-0462

A product does not set the Secure attribute for sensitive cookies in HTTPS sessions, which could cause the user agent to send those cookies in plaintext over an HTTP session with the product.

CVE-2008-3663

A product does not set the secure flag for the session cookie in an https session, which can cause the cookie to be sent in http requests and make it easier for remote attackers to capture this cookie.

CVE-2008-3662

A product does not set the secure flag for the session cookie in an https session, which can cause the cookie to be sent in http requests and make it easier for remote attackers to capture this cookie.

CVE-2008-0128

A product does not set the secure flag for a cookie in an https session, which can cause the cookie to be sent in http requests and make it easier for remote attackers to capture this cookie.

Mögliche Gegenmaßnahmen

Phases : Implementation
Always set the secure attribute when the cookie should be sent via HTTPS only.

Erkennungsmethoden

Automated Static Analysis

Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)
Wirksamkeit : High

Hinweise zur Schwachstellen-Zuordnung

Begründung : This CWE entry is at the Variant level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.
Kommentar : Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.

Verwandte Angriffsmuster

CAPEC-ID Name des Angriffsmusters
CAPEC-102 Session Sidejacking
Session sidejacking takes advantage of an unencrypted communication channel between a victim and target system. The attacker sniffs traffic on a network looking for session tokens in unencrypted traffic. Once a session token is captured, the attacker performs malicious actions by using the stolen token with the targeted application to impersonate the victim. This attack is a specific method of session hijacking, which is exploiting a valid session token to gain unauthorized access to a target system or information. Other methods to perform a session hijacking are session fixation, cross-site scripting, or compromising a user or server machine and stealing the session token.

Einreichung

Name Organisation Datum Veröffentlichungsdatum Version
Anonymous Tool Vendor (under NDA) 2007-05-07 +00:00 2007-05-07 +00:00 Draft 6

Änderungen

Name Organisation Datum Kommentar
Sean Eidemiller Cigital 2008-07-01 +00:00 added/updated demonstrative examples
Eric Dalci Cigital 2008-07-01 +00:00 updated Potential_Mitigations, Time_of_Introduction
CWE Content Team MITRE 2008-09-08 +00:00 updated Relationships, Taxonomy_Mappings
CWE Content Team MITRE 2008-10-14 +00:00 updated Observed_Examples
CWE Content Team MITRE 2009-03-10 +00:00 updated Name
CWE Content Team MITRE 2009-05-27 +00:00 updated Related_Attack_Patterns
CWE Content Team MITRE 2011-06-01 +00:00 updated Common_Consequences
CWE Content Team MITRE 2012-05-11 +00:00 updated Relationships
CWE Content Team MITRE 2012-10-30 +00:00 updated Potential_Mitigations
CWE Content Team MITRE 2014-07-30 +00:00 updated Relationships
CWE Content Team MITRE 2017-01-19 +00:00 updated Relationships
CWE Content Team MITRE 2017-11-08 +00:00 updated Taxonomy_Mappings
CWE Content Team MITRE 2020-02-24 +00:00 updated Applicable_Platforms, Relationships
CWE Content Team MITRE 2021-10-28 +00:00 updated Relationships
CWE Content Team MITRE 2022-06-28 +00:00 updated Relationships
CWE Content Team MITRE 2023-04-27 +00:00 updated Detection_Factors, Relationships
CWE Content Team MITRE 2023-06-29 +00:00 updated Mapping_Notes
CWE Content Team MITRE 2025-09-09 +00:00 updated Common_Consequences, Description, Diagram, Potential_Mitigations
CWE Content Team MITRE 2025-12-11 +00:00 updated Observed_Examples, Relationships, Weakness_Ordinalities
Die auf CVE Find präsentierten Informationen stammen aus mehreren sorgfältig ausgewählten Referenzquellen. CVE-Daten werden von der MITRE Corporation und der National Vulnerability Database (NVD) bereitgestellt. Der Katalog bekannter ausgenutzter Schwachstellen (KEV) stammt von der Cybersecurity and Infrastructure Security Agency (CISA), während EPSS-Scores von FIRST.org kommen. Darüber hinaus werden Daten zu Software-Schwachstellen (CWE) und häufigen Angriffsmustern (CAPEC) von der MITRE Corporation gepflegt, und Informationen zu Hardware- und Software-Konfigurationen (CPE) werden von der NVD bereitgestellt.