Session Hacking

Technical security testing of Session Management implementation covers two key areas:

• Integrity of Session ID creation
• Secure management of active sessions and Session IDs

The Session ID should be sufficiently unpredictable and abstracted from any private information, and the Session management should be logically secured to prevent any manipulation or circumvention of application security. These two key areas are interdependent, but should be considered separately for a number of reasons. Firstly, the choice of underlying technology to provide the sessions is bewildering and can already include a large number of OTS products and an almost unlimited number of bespoke or proprietary implementations. Whilst the same technical analysis must be performed on each, established vendor solutions may require a slightly different testing approach, and existing security research may exist on the implementation. Secondly, even an unpredictable and abstract Session ID may be rendered completely ineffectual should the Session management be flawed. Similarly, a strong and secure session management implementation may be undermined by a poor Session ID implementation. Furthermore, the analyst should closely examine how (and if) the application uses the available Session management. It is not uncommon to see Microsoft ISS server ASP Session IDs passed religiously back and forth during interaction with an application, only to discover that these are not used by the application logic at all. It is therefore not correct to say that because an application is built on a ‘proven secure’ platform its Session Management is automatically secure.

Session Analysis

The Session Tokens (Cookie, SessionID or Hidden Field) themselves should be examined to ensure their quality from a security perspective. They should be tested against criteria such as their randomness, uniqueness, resistance to statistical and cryptographic analysis and information leakage.

• Token Structure & Information Leakage

The first stage is to examine the structure and content of a Session ID provided by the application. A common mistake is to include specific data in the Token instead of issuing a generic value and referencing real data at the server side. If the Session ID is clear-text, the structure and pertinent data may be immediately obvious as the following:

192.168.100.100:user:password:25:51If part or the entire Token appears to be
encoded or hashed, it should be compared to various techniques to check for
obvious obfuscation. For example the string 192.168.100.100:user:password:25:51
is represented in Hex, Base64 and as an MD5 hash: 

Hex 3139322E3136382E3130302E313A6F77617370757365723A70617373776F72643A31353A3538Base64 MTkyLjE2OC4xMDAuMTpvd2FzcHVzZXI6cGFzc3dvcmQ6MTU6NTg=MD5 01c2fc4f0a817afd8366689bd29dd40aHaving identified the type of obfuscation, it may be possible to decode back to the original data. In most cases, however, this is unlikely. Even so, it may be useful to enumerate the encoding in place from the format of the message. Furthermore, if both the format and obfuscation technique can be deduced, automated brute-force attacks could be devised. Hybrid tokens may include information such as IP address or User ID together with an encoded portion,

Analysis of the variable areas (if any) of the Session ID should be undertaken to establish the existence of any recognizable or predictable patterns. These analysis may be performed manually and with bespoke or OTS statistical or cryptanalytic tools in order to deduce any patterns in Session ID content. Manual checks should include comparisons of Session IDs issued for the same login conditions – e.g. the same username, password and IP address. Time is an important factor which must also be controlled. High numbers of simultaneous connections should be made in order to gather samples in the same time window and keep that variable constant. Even a quantization of 50ms or less may be too coarse and a sample taken in this way may reveal time-based components that would otherwise be missed. Variable elements should be analysed over time to determine whether they are incremental in nature. Where they are incremental, patterns relating to absolute or elapsed time should be investigated. Many systems use time as a seed for their pseudo random elements. Where the patterns are seemingly random, one-way hashes of time or other environmental variations should be considered as a possibility. Typically, the result of a cryptographic hash is a decimal or hexadecimal number so should be identifiable. In analysing Session IDs sequences, patterns or cycles, static elements and client dependencies should all be considered as possible contributing elements to the structure and function of the application.

• Are the Session IDs provably random in nature? e.g. Can the result be reproduced?
• Do the same input conditions produce the same ID on a subsequent run?
• Are the Session IDs provably resistant to statistical or cryptanalysis?
• What elements of the Session IDs are time-linked?
• What portions of the Session IDs are predictable?
• Can the next ID be deduced even given full knowledge of the generation algorithm and previous IDs?

Brute Force Attacks
Brute force attacks inevitably lead on from questions relating to predictability and randomness. The variance within the Session IDs must be considered together with application session durations and timeouts. If the variation within the Session IDs is relatively small, and Session ID validity is long, the likelihood of a successful brute-force attack is much higher. A long session ID (or rather one with a great deal of variance) and a shorter validity period would make it far harder to succeed in a brute force attack.

• How long would a brute-force attack on all possible Session IDs take?
• Is the Session ID space large enough to prevent brute forcing? e.g. is the length of the key sufficient when compared to the valid life-span
• Do delays between connection attempts with different Session IDs mitigate the risk of this attack?