CAPEC

Common Attack Pattern Enumeration and Classification
Common Attack Pattern Enumeration and Classification

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Individual CAPEC Dictionary Definition (Release 1.1)
Individual CAPEC Dictionary Definition (Release 1.1)

Exploitation of Session Variables, Resource IDs and other Trusted Credentials
Attack Pattern ID
Pattern Abstraction: Standard

21

Typical Severity

High

Description

Summary

Attacks on session IDs and resource IDs take advantage of the fact that some software accepts user input without verifying its authenticity. For example, a message queueing system that allows service requesters to post messages to its queue through an open channel (such as anonymous FTP), authorization is done through checking group or role membership contained in the posted message. However, there is no proof that the message itself, the information in the message (such group or role membership), or indeed the process that wrote the message to the queue are authentic and authorized to do so.

Many server side processes are vulnerable to these attacks because the server to server communications have not been analyzed from a security perspective or the processes "trust" other systems because they are behind a firewall. In a similar way servers that use easy to guess or spoofable schemes for representing digital identity can also be vulnerable. Such systems frequently use schemes without cryptography and digital signatures (or with broken cryptography). Session IDs may be guessed due to insufficient randomness, poor protection (passed in the clear), lack of integrity (unsigned), or improperly correlation with access control policy enforcement points.

Exposed configuration and properties files that contain system passwords, database connection strings, and such may also give an attacker an edge to identify these identifiers.

The net result is that spoofing and impersonation is possible leading to an attacker's ability to break authentication, authorization, and audit controls on the system.

Attack Execution Flow

Explore
  1. Survey the application for Indicators of Susceptibility: Using a variety of methods, until one is found that applies to the target system. the attacker probes for credentials, session tokens, or entry points that bypass credentials altogether.

    Attack Step Techniques
    DescriptionEnvironments
    Spider all available pagesenv-Web
    Attack known bad interfacesenv-Web env-CommProtocol env-ClientServer env-Local
    Indicators of Susceptibility
    IDTypeDescriptionEnvironments
    c21s1i1PositiveSession IDs are usedenv-Web env-Peer2Peer env-ClientServer env-CommProtocol
    c21s1i2PositiveOpen access points exist that use no user IDs or passwords, but determine authorization based on message contentenv-Web env-Peer2Peer env-CommProtocol env-ClientServer env-Local
    Outcomes
    IDTypeDescription
    c21s1o1SuccessSession IDs are identifiable
    c21s1o2SuccessOpen channels are available
    Security Controls
    IDTypeDescription
    c211s2s1DetectiveMonitor velocity of page fetching in web logs. Humans who view a page and select a link from it will click far slower and far less regularly than tools. Tools make requests very quickly and the requests are typically spaced apart regularly (e.g. 0.8 seconds between them).
    c211s2s2DetectiveCreate links on some pages that are visually hidden from web browsers. Using IFRAMES, images, or other HTML techniques, the links can be hidden from web browsing humans, but visible to spiders and programs. A request for the page, then, becomes a good predictor of an automated tool probing the application.
    c211s2s3PreventativeActively monitor the application and either deny or redirect requests from origins that appear to be automated.
    c211s2s4DetectiveMonitor velocity of feature activations (non-web software). Humans who activate features (click buttons, request actions, invoke APIs, etc.) will do so far slower and far less regularly than tools. Tools make requests very quickly and the requests are typically spaced apart regularly (e.g. 0.8 seconds between them).
Experiment
  1. Fetch samples: An attacker fetches many samples of a session ID. This may be through legitimate access (logging in, legitimate connections, etc) or just systematic probing.

    Attack Step Techniques
    DescriptionEnvironments
    An attacker makes many anonymous connections and records the session IDs assigned.env-Web env-Peer2Peer env-CommProtocol env-ClientServer
    An attacker makes authorized connections and records the session tokens or credentials issued.env-Web env-Peer2Peer env-CommProtocol env-ClientServer
    An attacker gains access to (legitimately or illegitimately) a nearby system (e.g., in the same operations network, DMZ, or local network) and makes a connections from it, attempting to gain the same privileges as a trusted system.env-Peer2Peer env-CommProtocol env-ClientServer
    Indicators of Susceptibility
    IDTypeDescriptionEnvironments
    c21s3i1PositiveTrust in the system is based on IP address, MAC address, network locality, or other general network characteristic.env-CommProtocol env-ClientServer env-Peer2Peer
    c21s3i2PositiveWeb applications use session IDsenv-Web
    c21s3i3PositiveNetwork systems issue session IDs or connection IDsenv-CommProtocol env-ClientServer env-Peer2Peer
    Outcomes
    IDTypeDescription
    c21s3o1SuccessSystems or applications grant trust based on logical or physical network locality.
    c21s3o2SuccessSession identifiers successfully spoofed
    C21s3o3FailureNo session IDs can be found or exploited
    Security Controls
    IDTypeDescription
    c21s3s1DetectiveMonitor logs for unusual amounts of invalid sessions.
    c21s3s2DetectiveMonitor logs for unusual amounts of invalid connections or invalid requests from unauthorized hosts.
Exploit
  1. Impersonate: An attacker can use successful experiments to impersonate an authorized user or system

    Security Controls
    IDTypeDescription
    c21s4s1DetectiveAnalyze logs for users or systems that are connecting from unexpected sources.
    c21s4s2DetectiveAnalyze logs for users or systems successfully requesting or performing unexpected actions.
    c21s4s3CorrectiveIf heuristics are sufficiently reliable, disconnect hosts or users that appear to be unauthorized impersonations.
  2. Spoofing: Bad data can be injected into the system by an attacker.

    Outcome
    IDTypeDescription
    c21s5o1SuccessUnauthorized data is injected into an application.
    Security Controls
    IDTypeDescription
    c21s5s1DetectiveApply heuristic evaluation to input data. This can include validating source addresses, user names, ACLs or other data that indicates authorization. This need not be done inline at the time the data is processed, but can be done after the processing has occurred to detect attack.
    c21s5s2CorrectiveApply transaction-based logic to systems whose initial authorization cannot be better controlled. Roll back transactions that are subsequently determined to be fraudulent or illegitimate.
Attack Prerequisites

Server software must rely on weak session IDs proof and/or verification schemes

Typical Likelihood of Exploit

High

Methods of Attack
  • Spoofing
  • API Abuse
  • Injection
Examples-Instances

Description


Thin client applications like web applications are particularly vulnerable to session ID attacks. Since the server has very little control over the client, but still must track sessions, data, and objects on the server side, cookies and other mechanisms have been used to pass the key to the session data between the client and server. When these session keys are compromised it is trivial for an attacker to impersonate a user's session in effect, have the same capabilities as the authorized user. There are two main ways for an attacker to exploit session IDs.
A brute force attack involves an attacker repeatedly attempting to query the system with a spoofed session header in the HTTP request. A web server that uses a short session ID can be easily spoofed by trying many possible combinations so the parameters session-ID= 1234 has few possible combinations, and an attacker can retry several hundred or thousand request  with little to no issue on their side.
The second method is interception, where a tool such as wireshark is used to sniff the wire and pull off any unprotected session identifiers. The attacker can then use these variables and access the application.

Attacker Skill or Knowledge Required

Low → To achieve a direct connection with the weak or non-existent server session access control, and pose as an authorized user

Resources Required

Ability to deploy software on network. Ability to communicate synchronously or asynchronously with server

Solutions and Mitigations

Design: utilize strong federated identity such as SAML to encrypt and sign identity tokens in transit.

Implementation: Use industry standards session key generation mechanisms that utilize high amount of entropy to generate the session key. Many standard web and application servers will perform this task on your behalf.

Implementation: If the session identifier is used for authentication, such as in the so-called single sign on use cases, then ensure that it is protected at the same level of assurance as authentication tokens.

Implementation: If the web or application server supports it, then encrypting and/or signing the session ID (such as cookie) can protect the ID if intercepted.

Design: Use strong session identifiers that are protected in transit and at rest.

Implementation: Utilize a session timeout for all sessions, for example 20 minutes. If the user does not explicitly logout, the server terminates their session after this period of inactivity. If the user logs back in then a new session key is generated.

Implementation: Verify of authenticity of all session IDs at runtime.

Attack Motivation-Consequences
  • Privilege Escalation
  • Information Leakage
  • Data Modification
Context Description


“Attack Pattern: Session ID, Resource ID, and Blind Trust
When session and resource IDs are simple and available, attackers can use them to their advantage. Many schemes are so simple that pasting in another known ID in a message stream works.
[Hoglund and McGraw 04]

Injection Vector

Malicious input delivered through standard service calls, e.g. FTP or posting a message to a message queue.

Payload

Varies with instantiation of attack pattern. The main goal is so spoof or impersonate a legitimate user.

Activation Zone

Client machine and client network (e.g. Intranet)

Payload Activation Impact

Enables attacker to impersonate another user and access commands and data (and log behavior to audit logs) on their behalf.

Related Weaknesses
CWE-IDWeakness NameWeakness Relationship Type
290Authentication Bypass by SpoofingTargeted
302Authentication Bypass by Assumed-Immutable DataTargeted
346Origin Validation ErrorTargeted
539Information Leak Through Persistent CookiesSecondary
6J2EE Misconfiguration: Insufficient Session-ID LengthTargeted
384Session FixationSecondary
Purpose

Penetration

CIA Impact
Confidentiality ImpactIntegrity ImpactAvailability Impact
HighHighLow
Technical Context
Architectural ParadigmFrameworkPlatformLanguage
Client-ServerAllAllAll
References

G. Hoglund and G. McGraw. Exploiting Software: How to Break Code. Addison-Wesley, February 2004.

Source
Submission(s)
SubmitterOrganizationDateComment
G. Hoglund and G. McGraw. Exploiting Software: How to Break Code. Addison-Wesley, February 2004.Cigital, Inc2007-01-01
Modification(s)
ModifierOrganizationDateComment
Gunnar PetersonCigital, Inc2007-02-28Fleshed out content to CAPEC schema from the original descriptions in "Exploiting Software"
Sean BarnumCigital, Inc2007-03-10Review and revise
Richard StruseVOXEM, Inc2007-03-26Review and feedback leading to changes in Description
Sean BarnumCigital, Inc2007-04-13Modified pattern content according to review and feedback
Paco HopeCigital, Inc.2007-10-20Added extended Attack Execution Flow
 
Page Last Updated: April 18, 2008