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Types of Software Vulnerabilities

Question:

Discuss About The Vulnerability Severity Prediction A Metric?

Computer software vulnerability can be considered as threats that have been playing a very much vital role in every sphere related to the concept of management technology. Relating to when a breach takes place the first question which arises in the mind is that who is mainly gained from the incident. The answers are mainly the attackers to initiate the attack. The main concept is breaking into the system and stealing information or money, this task is considered to be very much easy from the side of the attacker and profitable also (Li et al. 2017). To be very much precise a software vulnerability can be stated as a flaw within a software product that can cause it deviation from the proper working and tend to lend the control of the entire software in the hand of the hackers who focus mainly to deliver profit on his basis from the vulnerability which is detected in the software and its peripherals.

This report directly puts emphasis on the concept of the vulnerable which is related to the software and what stands in the way of delivering a software which does not face any issue related to vulnerability. The main point of emphasis is the issue which are taken into account after a vulnerability is taken into account bringing into limelight the different tactics that are followed in order to resolve the issue and take necessary steps to reduce the after affect.

Taking into consideration the complex communication system and information gives rise to implementation, design and management errors. These errors can directly lead to the concept of vulnerability. The term vulnerability can be used to describe a flaw in the information technology product that could be mainly used for the exploitation of the product. There can be several methods which can be included in the term of exploitation. Exploitation can be classified on the type of vulnerability they intent to attack. Few example which can be included in this concept are:

Buffer overflow: in terms of computer security and programming the term buffer overflow or buffer overrun can be stated as an anomaly with regards to a program, while mainly the action of writing data to a buffer, overruns the boundary of the buffer and overwrites the location of the memory (Rahimi and Zargham 2017).

Situation a: when the main program is running

Methods of Exploitation

Situation b: after the program A is called

Situation c: buffer overflow concept which is shown in grey

The concept of the memory corruption usually occurs in the computer program when the overall content of the memory location is unintentionally modified. It can be referred to as a violation of the memory safety ( Li et al. 2017).

The race condition can be considered as situation which is undesirable that mainly occur when a device of a system mainly attempts to perform two or more operations with regards to the same instance of time, but due to the factor of nature of the device or the system, the operation should be done in the proper sequence in order to do it correctly.

SQL injection is mainly considered as a code technique of injection which is mainly done to attack the data driven application, in which the nefarious statement of the SQL is injected into an entry field with the intention of execution.

The main classification of the exploits can also be done on how the exploit contacts with the vulnerable software (Rahimi and Zargham 2017). There are mainly two types which can be involved in the concept, one being remote exploit and the other being local exploit. A remote exploit works mainly over a predefined network with the intention of exploiting the security vulnerability and on the other hand the local exploit requires the access prior to the vulnerable system and which usually increase the privileges in regards to the person running the main action of the exploit (Sibal, Sharma and Sabharwal 2017).

Mainly due to the popularity in the concept of the internet, the network borne virus which are the computer virus and the worms can be termed as the main forms of exploitation. Taking into consideration a computer worm, it can the ability of self-replicating itself and can be considered as a self-contained exploitation. The computer worm can spread from one system to another system without the intervention of human activity ( Spanos et al. 2016). Onm the other hand a computer virus requires the action on the part of the user, for example emails attachments etc. the computer worms and the virus can be termed as a most cited example form of exploitation which has achieved overall 82% of the activity. The reco9very aspect which is related to the case are that almost 33% of the victim recovered from the attack in one day, 30% recovered in a tenure of one to seven days and 37% took more than a weeks’ time to recover completely from the attack ( Li et al. 2017).

Classification of Exploits

Exploits can also be classified on the concept of the main purpose of the attack and the main intention behind the attack. Few of the example which can be related in this type of classification are: personal frame (trespasser), curiosity (vandal), personal gain(thief) and interest of national (spy). The slammer, blaster and the code red attack mainly infected millions and millions of computer all over the world, it can be considered as very much expensive in order to recover from the incident. In recent times the attack which I s related to the personal gain can be considered as one of the most fastest growing sectors in the segment (Sibal, Sharma and Sabharwal 2017). These exploits can be terms of email phasing, email spam, keystroke loggers, bots and credential theft. Taking into consideration this types of attack many of the people who are victim of the attack are spoofed, where more than 60% of the victim visited the spoofed site and more than 15% have mainly admitted of giving their personal data to unwanted resources.

Taking into account a software vulnerability, each and every software vulnerability can be stated as different mainly on the basis of the process by which the flaws are mainly discovered to the ways in which the vulnerability is disclosed. There can be few categories in which the software vulnerability can be classified which are:

The first discloser type which is taken into account is the non-discloser. This discloser is probably the easiest type of discloser which can be described and on the other hand quantification is very much difficult. In the case of this type of discloser, the researchers have discovered a vulnerability concept in a piece of a software, rather than the contact the software vendors or the security of the computer authority coordinating the event, the researchers mainly kept the concept of the vulnerability a mere secret. The community which is mainly involved in this type of practice are the black hat hackers.

The concept of quantification which is very much difficult is due to the fact of the paradox that are no ways in which measurement of the flaws can be obtained but not disclosed (Sibal, Sharma and Sabharwal 2017). Based on the communication model it can be estimated that up to 17.3% of the finding of the vulnerability were not disclosed, however the statement of the how many vulnerabilities were discovered but remain undisclosed is a very important point of consideration in such a case. There was fairly a huge amount of critic on the concept of the vulnerability, the main point of concern is that the system remains open to the vulnerability even though the vulnerability is known, the main reason of this fact is that the vendors lack of publicity concept in the vulnerability may not be motivating on the point of the software vendors in order to repair the flaws immediately when it is known. Others variations which are taken into account on the non-discloser method tend to have the same result at the net end of the process which include greater risk towards the user in the point of view of the exploitation of the vulnerability. For example, it can be state that a researcher may find out any sort of vulnerability in a piece of software, the result of the action is taken in such a way that apart from reporting the vulnerability to the concerned authority the attackers would directly share the vulnerability which is involved in the software with other hackers which directly increase the risk associated to the user which are termed as the end user in this case (Joh and Malaiya 2016).

Types of Vulnerability Disclosure

When a researchers find out a vulnerability they tend to inform the community at a whole about the vulnerability and mainly specifies how the vulnerability is found out, which software products can be affected by such vulnerability and the overall affect which is involved in due to the incident. On the broader sense they also tend to focus on the points on how the to exploit the flaws and how to protect the system against being a victim of the vulnerability. There can be many arguments against the main concept of the full discloser vulnerability in the sense that the total argument is taken into interest of the attackers and the informing the community about the attack. The main argument can be stated in two different way notability the first being that it is very much unethical to inform the community as a whole about the software flaws which are involved as soon as it is detected even before any patch is taken into economics in order to reduce the overall impact of the vulnerability so that from the users point of view they can protect themselves. The second point of emphasis is that tactic motive in regards to the vendors of the software as when a software flaw is detected is to sit behind and acknowledge the event and informs the community about that an event has taken place rather than trying to generated some sort of patches in order to reduce the overall impact of the attack.

One of the advantage that is faced in concept to the full discloser that when a flaw is detected the credit goes to the researchers on the incident of detecting the flaw. The credit goes directly in the hand of the researchers. Clearly it can be stated that incentives and the motivation which is related to the security industry being for personal or professional, the full discloser can be considered as a discloser technique that can be a field of attraction for the researchers of the security (Ghaffarian, S.M. and Shahriari 2017).

On the other hand, the argument against the category of the full discloser method tend to go parallel with the full discloser. It can be seen that one of the most silent argument which usually takes place with the incident is that the exposing part of the vulnerability without the proper consultation with the software vendor related to the main event, this may directly result in increase of the risk being widespread in the point of view of the user of the system of the computer (Joh and Malaiya 2016). A very common example which can be related to the incident is that with few days or hours following the detection of the vulnerability a full script is ready and very much available for the script Kidde’s toc consume and use the concept. Additionally, taking into account the vendors are not informed on the first hand about the vulnerability and the incident and main emphasis is put on informing the community about the incident, the work on the patches and the security measures that should be implemented takes very much time, the testing phase which is related to any software flaws can take time to about few days before a patch van be launched in order to reduce the overall effect of the vulnerability. So it can have stated that there always lies a big window in which the user or the community is informed about the flaws but no patches or security measures are involved in the process to lack of information which is landed to the vendors in order for them to work on it and provide the necessary patches to the community or the users in order to protect them (Ghaffarian, S.M. and Shahriari 2017).

This can be termed as a final step of the discloser. The responsible discloser mainly falls into what can be stated as a class of vulnerability which can be known as partial discloser or in simple terms limited discloser. The responsible discloser may be stated as a policy of software discloser in which software vulnerability are mainly disclosed in a manner with the intention of putting the user at a minimum risk stage without the alteration related to the stifling the research security community. To make the term simple, when a vulnerability is detected in any software the researchers directly inform the vendors who are related to the software, and if the vendors in some cases are not responsive to the event , the researchers takes the overall control over the event and proceed with it. The main stages that are followed in this type of disclosers are as follows:

  • The researchers first step after discovering of the flaw is to inform the vendors about the vulnerability (Shin and Williams 2016).
  • If the vendor’s quickie responds the event and acknowledges the flaw and credit the researchers in order of identify the flaw and conduct the testing phase on the flaw and immediately after the testing issue of the patch related to the flaw is made the process can be stated to be complete.
  • On the other hand, if the vendors do not respond quickly enough to the flaw or mainly fail to continue the communication related to the event, the originator has no other option than to proceed with the public discloser without the vendor’s direct intervention in the event of no patches being supplied.
  • Taking into account both the scenarios, the concept of when the vulnerability is detected the principle should be to response quickly to the flaws. This can be done on the point of view of the vendors and also on the point of view of the researchers who have identified the issue and work on the always so that the common people are not affected to much by the incident (Joh and Malaiya 2016).

The cost of the software vulnerability towards the vendor can be broadly be classified mainly into two categories: the cost of distributing a patch for the defect and loss of cost sales due to the factor of dissatisfaction from the point of view of the customer.

Cost of patch: the cost which is relating to fixing any sort of problem after the release of the software can be considered to be always on the higher point than the cost of fixing a problem prior to the release of the software. It can be estimated that the cost of fixing any problem after the realise is eight times more than prior to the release. Researchers have found out that fixing a bug after a realise is very much difficult and time consuming then prior to the release. Taking an example of one of the giants in the field of technology Microsoft, the company spends nearly $100000 on an average for the security related issue in order to distribute patch for any fault which is detected. However, the cost of the releasing aspect of each of the patches can be on a lower end by distributing the patches online

Cost of loss related to sales: software vulnerability can directly lead to customer dissatisfaction, loss of reputation of the vendor and disruption. Defective software can superimpose many types of problem related to the user as stated below:

  1. The breaches which occur due to software may lead to disruption, downfall as well as compromised information which is related to confidentiality.
  2. Using of defective software from the point of view of the user can impose many types of cost related issue.

The magnitude of the second point which is discussed above can be directly be related to the Amount of loss which is generated from the point of view of the customers. Moreover, putting emphasis on the vendors they can future loss many of the users due to user’s avoidance in order of buying the product and with the existing customers delay can purchase can be exhibited due to the insecurity which is seen in the product. It can also be stated that the software products have largest cost related issue when relating to the switching which makes it difficult for the users to switch between the vendors. Therefore, the cost related to the sales lost depends mainly on the market structure as well.

Conclusion

The report puts direct emphasis on a contemporary and interesting issue of whether vendors of the software are adversely affected by the security issue related vulnerability which is related to the software products. It can be stated that due to the unique characteristics of the software industry in the near future the damage which is imposed on the vendor’s point of view on an event of a software vulnerability would be very much minimal and unneglectable. The vulnerability issue which is related to the software product can be state to be very much on a higher side if after the detection of the vulnerability no patches or security measures are involved in the process. there should be always a high end testing of the vulnerability and why it is caused so that the end users are not affected by such events. On the other hand the report also states that the cost related to the include patches after the release of a software is always on a higher hand, so it must always be taken into consideration that the testing and other security issue related problems are solved before the software is in the hand of the common users. This would be directly beneficial from the point of view of the vendors as well as the user of the software.

References

Alves, H., Fonseca, B. and Antunes, N., 2016, September. Software Metrics and Security Vulnerabilities: Dataset and Exploratory Study. In Dependable Computing Conference (EDCC), 2016 12th European (pp. 37-44). IEEE.

Anand, P., 2016, August. Overview of Root Causes of Software Vulnerabilities-Technical and User-Side Perspectives. In Software Security and Assurance (ICSSA), 2016 International Conference on (pp. 70-74). IEEE.

Cai, J., Zou, P., Ma, J. and He, J., 2016. SwordDTA: A dynamic taint analysis tool for software vulnerability detection. Wuhan University Journal of Natural Sciences, 21(1), pp.10-20.

Dam, H.K., Tran, T., Pham, T., Ng, S.W., Grundy, J. and Ghose, A., 2017. Automatic feature learning for vulnerability prediction. arXiv preprint arXiv:1708.02368.

Ghaffarian, S.M. and Shahriari, H.R., 2017. Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques: A Survey. ACM Computing Surveys (CSUR), 50(4), p.56.

Hovsepyan, A., Scandariato, R. and Joosen, W., 2016, September. Is Newer Always Better?: The Case of Vulnerability Prediction Models. In Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and management (p. 26). ACM.

Hovsepyan, A., Scandariato, R., Joosen, W. and Walden, J., 2017, September. Software vulnerability prediction using text analysis techniques. In Proceedings of the 4th international workshop on Security measurements and metrics (pp. 7-10). ACM.

Jimenez, M., Papadakis, M. and Le Traon, Y., 2016, October. Vulnerability Prediction Models: A case study on the Linux Kernel. In Source Code Analysis and Manipulation (SCAM), 2016 IEEE 16th International Working Conference on (pp. 1-10). IEEE.

Joh, H. and Malaiya, Y.K., 2016. Periodicity in software vulnerability discovery, patching and exploitation. International Journal of Information Security, pp.1-18.

Lagerström, R., Baldwin, C., MacCormack, A., Sturtevant, D. and Doolan, L., 2017, July. Exploring the Relationship Between Architecture Coupling and Software Vulnerabilities. In International Symposium on Engineering Secure Software and Systems (pp. 53-69). Springer, Cham.

Li, H., Kwon, H., Kwon, J. and Lee, H., 2016. CLORIFI: software vulnerability discovery using code clone verification. Concurrency and Computation: Practice and Experience, 28(6), pp.1900-1917.

Li, X., Chang, X., Board, J.A. and Trivedi, K.S., 2017, January. A novel approach for software vulnerability classification. In Reliability and Maintainability Symposium (RAMS), 2017 Annual (pp. 1-7). IEEE.

Nord, R.L., Ozkaya, I., Schwartz, E.J., Shull, F. and Kazman, R., 2016, August. Can Knowledge of Technical Debt Help Identify Software Vulnerabilities?. In CSET@ USENIX Security Symposium.

Piancó, M., Fonseca, B. and Antunes, N., 2016, June. Code Change History and Software Vulnerabilities. In Dependable Systems and Networks Workshop, 2016 46th Annual IEEE/IFIP International Conference on (pp. 6-9). IEEE.

Piessens, F. and Verbauwhede, I., 2016, March. Software security: Vulnerabilities and countermeasures for two attacker models. In Proceedings of the 2016 Conference on Design, Automation & Test in Europe (pp. 990-999). EDA Consortium.

Rahimi, S. and Zargham, M., 2017. Vulnerability scrying method for software vulnerability discovery prediction without a vulnerability database. IEEE Transactions on Reliability, 62(2), pp.395-407.

Shin, Y. and Williams, L., 2016, October. An empirical model to predict security vulnerabilities using code complexity metrics. In Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (pp. 315-317). ACM.

Shin, Y., Meneely, A., Williams, L. and Osborne, J.A., 2016. Evaluating complexity, code churn, and developer activity metrics as indicators of software vulnerabilities. IEEE Transactions on Software Engineering, 37(6), pp.772-787.

Sibal, R., Sharma, R. and Sabharwal, S., 2017. Prioritizing software vulnerability types using multi-criteria decision-making techniques. Life Cycle Reliability and Safety Engineering, 6(1), pp.57-67.

Spanos, G., Angelis, L. and Kosmidou, K., 2017. Is the Marketing Value of Software Vendors Affected by Software Vulnerability Announcements?. In Strategic Innovative Marketing (pp. 465-469). Springer, Cham.

Spanos, G., Angelis, L. and Kosmidou, K., 2017. Is the Market Value of Software Vendors Affected by Software Vulnerability Announcements?. In Strategic Innovative Marketing (pp. 465-469). Springer, Cham.

Stuckman, J., Walden, J. and Scandariato, R., 2017. The Effect of Dimensionality Reduction on Software Vulnerability Prediction Models. IEEE Transactions on Reliability, 66(1), pp.17-37.

Sultana, K.Z., Deo, A. and Williams, B.J., 2016, June. A preliminary study examining relationships between nano-patterns and software security vulnerabilities. In Computer Software and Applications Conference (COMPSAC), 2016 IEEE 40th Annual (Vol. 1, pp. 257-262). IEEE.

Sultana, K.Z., Deo, A. and Williams, B.J., 2017, January. Correlation Analysis among Java Nano-Patterns and Software Vulnerabilities. In High Assurance Systems Engineering (HASE), 2017 IEEE 18th International Symposium on (pp. 69-76). IEEE.

Yang, J., Ryu, D. and Baik, J., 2016, January. Improving vulnerability prediction accuracy with secure coding standard violation measures. In Big Data and Smart Computing (BigComp), 2016 International Conference on (pp. 115-122). IEEE.

Yu, C., Mannan, A.M., Yvone, G.M., Ross, K.N., Zhang, Y.L., Marton, M.A., Taylor, B.R., Crenshaw, A., Gould, J.Z., Tamayo, P. and Weir, B.A., 2016. High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines. Nature biotechnology, 34(4), pp.419-423.

Zhu, X., Cao, C. and Zhang, J., 2017. Vulnerability severity prediction and risk metric modeling for software. Applied Intelligence, pp.1-9.

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