| Attack Pattern ID | Pattern Abstraction: Detailed 59 |
| Typical Severity | High |
| Description | Summary This attack targets predictable session ID in order to gain privileges. The attacker can predict the session ID used during a transaction to perform spoofing and session hijacking. Attack Execution Flow Explore Find Session IDs: The attacker interacts with the target host and finds that session IDs are used to authenticate users. |
Attack Step Techniques |
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| Description | Environments |
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| 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 |
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Indicators of Susceptibility
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| ID | Type | Description | Environments |
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| c59s1i1 | Positive | Web applications use session IDs | env-Web | | c59s1i2 | Positive | Network systems issue session IDs or connection IDs | env-CommProtocol env-ClientServer env-Peer2Peer |
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Security Controls |
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| ID | Type | Description |
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| c59s1s1 | Detective | Monitor logs for unusual amounts of invalid sessions. | | c59s1s2 | Detective | Monitor logs for unusual amounts of invalid connections or invalid requests from unauthorized hosts. |
Characterize IDs: The attacker studies the characteristics of the session ID (size, format, etc.). As a results the attacker finds that legitimate session IDs are predictable. |
Attack Step Techniques |
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| Description | Environments |
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| Cryptanalysis. The attacker uses cryptanalysis to determine if the session IDs contain any cryptographic protections. | env-Web env-ClientServer env-Peer2Peer env-CommProtocol | | Pattern tests. The attacker looks for patterns (odd/even, repetition, multiples, or other arithmetic relationships) between IDs | env-Web env-ClientServer env-Peer2Peer env-CommProtocol | | Comparison against time. The attacker plots or compares the issued IDs to the time they were issued to check for correlation. | env-Web env-ClientServer env-Peer2Peer env-CommProtocol |
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Outcomes |
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| ID | Type | Description |
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| c59s2o1 | Success | Patterns are detectable in session IDs | | c59s2o2 | Failure | Session IDs pass NIST FIPS 140 statistical tests for cryptographic randomness. | | c59s2o3 | Success | Session IDs are repeated. |
Experiment Match issued IDs: The attacker brute forces different values of session ID and manages to predict a valid session ID. |
Attack Step Technique |
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| Description | Environments |
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| The attacker models the session ID algorithm enough to produce a compatible series os IDs, or just one match. | env-Web env-ClientServer env-Peer2Peer env-CommProtocol |
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Outcomes |
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| ID | Type | Description |
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| c59s3o2 | Success | Session identifiers successfully spoofed | | c59s3o3 | Failure | No session IDs can be found or exploited |
Exploit Use matched Session ID: The attacker uses the falsified session ID to access the target system. |
Attack Step Techniques |
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| Description | Environments |
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| The attacker loads the session ID into his web browser and browses to restricted data or functionality. | env-Web | | The attacker loads the session ID into his network communications and impersonates a legitimate user to gain access to data or functionality. | env-CommProtocol env-Peer2Peer env-ClientServer |
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Security Controls |
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| ID | Type | Description |
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| c59s4s1 | Detective | Monitor the correlation between session IDs and other station designations (MAC address, IP address, VLAN, etc.). Alert on session ID reuse from multiple sources. | | c59s4s2 | Preventative | Terminate both sessions if an ID is used from multiple origins. |
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| Attack Prerequisites | The target host uses session IDs to keep track of the users. Session IDs are used to control access to resources. The session IDs used by the target host are predictable.For example, the session IDs are generated using predictable information (e.g., time). |
| Typical Likelihood of Exploit |
High
|
| Methods of Attack | - Spoofing
- Brute Force
- Analysis
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| Examples-Instances | Description Jetty before 4.2.27, 5.1 before 5.1.12, 6.0 before 6.0.2, and 6.1 before 6.1.0pre3 generates predictable session identifiers using java.util.random, which makes it easier for remote attackers to guess a session identifier through brute force attacks, bypass authentication requirements, and possibly conduct cross-site request forgery attacks. Related Vulnerability Description mod_usertrack in Apache 1.3.11 through 1.3.20 generates session ID's using predictable information including host IP address, system time and server process ID, which allows local users to obtain session ID's and bypass authentication when these session ID's are used for authentication. Related Vulnerability |
| Attacker Skill or Knowledge Required | Low: There are tools to brute force sesion ID. Those tools require a low level of knowledge.
Medium/High: Predicting Session ID may require more computation work which uses advanced analysis such as statistic analysis. |
| Probing Techniques | The attacker can perform analysis of the randomness of the session generation algortihm. The attacker may need to steal a few valid session IDs using a different type of attack. And then use those session ID to predict the following ones. The attacker can use brute force tools to find a valid session ID. |
| Solutions and Mitigations | Use a strong source of randomness to generate a session ID. Use adequate length session IDs Do not use information available to the user in order to generate session ID (e.g., time). Ideas for creating random numbers are offered by Eastlake [RFC1750] Encrypt the session ID if you expose it to the user. For instance session ID can be stored in a cookie in encrypted format. |
| Attack Motivation-Consequences | |
| Context Description | |
| Related Weaknesses | | CWE-ID | Weakness Name | Weakness Relationship Type |
|---|
| 290 | Authentication Bypass by Spoofing | Targeted | | 330 | Use of Insufficiently Random Values | Targeted | | 331 | Insufficient Entropy | Targeted | | 346 | Origin Validation Error | Targeted | | 488 | Data Leak Between Sessions | Secondary | | 539 | Information Leak Through Persistent Cookies | Secondary | | 200 | Information Leak (Information Disclosure) | Secondary | | 6 | J2EE Misconfiguration: Insufficient Session-ID Length | Targeted | | 285 | Missing or Inconsistent Access Control | Secondary | | 384 | Session Fixation | Secondary |
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| Related Security Principles | - Securing the Weakest Link
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| Purpose | Penetration |
| CIA Impact | | Confidentiality Impact | Integrity Impact | Availability Impact |
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| High | High | Low |
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| Technical Context | | Architectural Paradigm | Framework | Platform | Language |
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| Client-Server | J2EE | All | All |
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| References | G. Hoglund and G. McGraw. Exploiting Software: How to Break Code. Addison-Wesley, February 2004. |
| Source | | Submission(s) |
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| Submitter | Organization | Date | Comment |
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| Eric Dalci | Cigital, Inc | 2007-01-25 | |
| Modification(s) |
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| Modifier | Organization | Date | Comment |
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| Sean Barnum | Cigital, Inc | 2007-03-07 | Review and revise |
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