The future of Cybersecurity Technology and Policy (IoT)

 

The future of Cybersecurity Technology and Policy

 

Abstract

This paper addresses the emerging cybersecurity technologies primarily related to (IoT) internet of things.  How these new technologies can show hope for change and innovation in the field.  Also, looking at government policy that has been lagging in its ability to step in and catch up with the dynamic change in technology and cybersecurity policy.  Understanding the technology and satisfying the initial need is completely two different things.  Also, we look at the overall impact that the government policy that is being used in cases against a hotel company and mobile device vendor is taking a toll on the innovation of IoT in this field.

Countering cyber-attacks at all levels

One of the fastest growing areas in technology is the introduction of the concept (IoT) Internet of things.  IoT is a very broad area.  It ultimately encompasses everything connected.  In fact, (Forbes & Morgan, 2004) says, “that by 2020 there will be over 26 billion connected devices… That’s a lot of connections (some even estimate this number to be much higher, over 100 billion)” As many attempts to try and define IoT there hasn’t been much of a great definition until the past year.  (Gartner Research, n.d.) defined it by saying, “The Internet of Things (IoT) is the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.”  Forbes went to greater lengths to simplify IoT as, “Simply put, this is the concept of basically connecting any device with an on and off switch to the Internet (and/or to each other).”  This includes but not limited to smartphones, smart electrical grids, toasters, and Fitbit’s and other wearables to show the range that we’re discussing.  Much like the definition which can be slightly vague, cybersecurity policy and mitigation is also heavily undefined in this area.  The upside to IoT is that it reduces human involvement along with improving accuracy and efficiency, resulting in economic benefit, (CHALLA et al., 2017, p. xx). According to the (IEEE) the institute of electrical and electronic engineers there are emerging technology that show positive signs of hope in this fast-growing new area, which are application authentication and key management practices, computed trust nodes, and lightweight security protocols for cloud-based Internet-of-Things (IoT) applications for battery-limited mobile devices.

 

Benefits to Cybersecurity

Each of these emerging technologies offer a different approach in establishing a level of trust in cybersecurity.  One emphasizes a solution built around secure authenticated key establishment scheme, another improves on a trust system or creation of trusted nodes within a network, and the last dives deeper into creating a lightweight protocol concentrating on cloud based cybersecurity.

Signature Based Authenticated Key Establishment Scheme

The basic premise for this new technology is that IoT as a concept has a high potential for invalid security and privacy.  Largely due to the inability to establish security at the design level for each connected object.  This is where most of the security challenges come into play.  Key contributing features that makes this a very promising emerging methodology or practice are:

  • An authentication model for IoT to follow. This model defines a term of mutual authentication.  Where a user authenticates through a gateway node and the IoT device authenticates through the gateway node as well.  Through this mutual authentication the users are then authenticated on the IoT device by proxy.
  • A secure signature based authentication and key agreement scheme. A legal user can access the information from a sensing device in the IoT applications if both mutually authenticate each other, (CHALLA et al., 2017, p. xx). After their mutual authentication, a secret session key is established between them for future communication.

Ultimate benefits of the wide use of this technical methodology have

concluded very efficient in communication and computational costs.  Which helps to solve the problem of identity on IoT devices.  The proposed scheme also protects itself from replay attacks by using random number generators as well as current timestamps.  The assumptions are that all users in the IoT environment are synchronized with their clocks.  There are eight phases to implementation:

  • System setup
  • Sensing device registration
  • User registration
  • Login
  • Authentication and key agreement
  • Password and biometric update
  • Smart card revocation
  • Dynamic sensing device addition

This new best practice can be applied to many different industries in regard to IoT much like the cybersecurity frameworks established by NIST for its categorizations of authentication in web based applications.  This could potentially be incorporated to help satisfy some of the “reasonable security measures” that FTC a government agency which has been known to uphold.  More on this later in the paper.  Establishing standard frameworks for cybersecurity in IoT may allow some businesses that are on the fence to moving to this technology to start implementing and eventually start innovating in the area.

 

Optimal Trust System Placement in SCADA Networks

Privacy and trust are also a large concern to the US smart grid system.  Mainly because the smart grid network itself highly depends on information and communication technology (ICT).  Supervisory control and data acquisitions (SCADA) are integral part of the modern day smart grid system.  Its primary function is control messages and measurements.  At the current moment, the system is in its fourth generation of architecture, which introduced two key new advanced technologies, (Hasan & Mouftah, 2016, p. xx).  The first would be cloud computing and the second IoT making the smart grid more susceptible to complete outage.  Slight modifications of these systems may cause a complete outage across the entire grid.  Smart grid operators use trust systems to monitor network traffic to and from different nodes.  These nodes are called trust nodes.  The nodes themselves include both a firewall and intrusion detection system.  Within making the decision of which nodes are the best to deploy these trust systems in a network there are two factors which need to be considered capital expenditures and operational expenditures, (Hasan & Mouftah, 2016, p. xx).  To deploy the trust system properly considering operational expenditures and capital expenditures.  Nodes can house only a fixed number of trust systems deployed to them due to budgetary constraints.  The SCADA networks need to be segmented to minimize the amount of cyber-attack traffic and for the trust nodes to be more effective.   There are some potential risks that these SCADA systems need to watch out for.  There are three main types of attacks that are at risk in the current SCADA network.

  • Targets power plants. Disrupts operation or generation.
  • Targets power distribution and control systems. Disrupts state information that may lead to instability.
  • Targets consumer premises. It could potentially cause an increment in the load that could damage the grid.

The focus of the new emerging technology is on the optimal placement of the trust nodes on the SCADA network.  The ultimate solution was producing an algorithm where minimum spanning trees (MST) would represent the smaller segments and then would determine the least expensive method of determining these segments and deploying the trust systems to these trust nodes.  Thereby segmenting the electrical grid enough to protect in from cyberattacks and in the most cost-efficient way possible.  The emerging technology directly effects not only the US smart grid and its efficiency, but also on a local level being able to apply this algorithm to other industries where cost is an issue possibly in the automotive and more factory related industries with clearly large systems that need to be segmented for better protection.  With this new technology and the high priority to moving towards smaller micro grids, this technology is essential and the energy industry globally should be able to benefit from this.

CP-ABE Scheme for Mobile Devices

The last emerging technology is the development of the CP-ABE Scheme for battery limited mobile devices.  In the IoT world many new applications have an emphasis on one device in general that’s the smartphone.  The ability to create secure applications is a must.  This emerging tech focuses on the encryption mechanisms of (CP-ABE) Ciphertext Policy Attribute Based Encryption.  The problem is that most CP-ABE schemes are based on bilinear maps and require long decryption keys, ciphertexts and incur significant computational costs, (Odelu, Das, Khurram Khan, Choo, & Jo, 2017, p. xx).  These limitations prevent the CP-ABE scheme from being deployed on mobile battery limited devices.  The new emerging technology is the ability to create RSA based CP-ABE that has a constant length of secret key.  The ultimate key decryption and encryption times are O (1) of time of complexity which is ground breaking as other solutions have failed to be this efficient up until this point.

CPE-ABE has been around for years but the efficiency that this new method has brought has now made this more applicable to modern IoT technologies primarily the smartphone but not limited to this.  The implementation of the RSA based CPE-ABE is broken down into four main algorithms:

  • Setup – This algorithm takes a security parameter and the universe of attributes as inputs and then outputs a master public key and its corresponding master secret key
  • Encrypt – This algorithm takes an access policy the master public key and plaintext as inputs. The encryption algorithm outputs a ciphertext
  • KeyGen – The inputs are an attribute set, the master public key and the master secret key. The key generation then outputs a user secret key corresponding to the attributes.
  • Decrypt – It takes a ciphertext generated with an access policy, the master public key and the secret key and outputs plaintext using the decryption algorithm, (Odelu, Das, Khurram Khan, Choo, & Jo, 2017, p. xx).

Real world usage for this kind of technology isn’t limited to mobile phones.  Since this is an attribute based encryption system this can be used almost anywhere where attribute based encryption is used.  Which includes token based authentication in JSON Web Token and the creation of JWE or an encrypted JSON Web Token which is used in OAuth system all over the internet in almost every authenticated application.  JSON Web Tokens are used currently right now as an attribute based system.  Instead of attributes the RFC calls them claims where claims are encrypted and sent with a token to the user trying to authenticate.  The claims are then evaluated and the user is given a long-lived token for subsequent requests until the token is expired.  This creates a stateless session for any web application user experience.  OAuth is a security framework that is widely used to authenticate a user across multiple services.  With the emergence of this new technology businesses will be able to use this new RSA based system much like the current systems that are using claims in JWT’s.  The entire online web community will take advantage of this new emerging technology in the coming years.

Federal Government Nurturing the Technologies

Cooperative efforts between the government community and the technology community is needed when discussing the new technology concepts such as IoT.    There is still a lot of work to be done.  A good place to start would be the Federal Trade and Commission’s (FTC).  In an Act, there is a requirement “reasonable security measures” which the agency uses to regulate unfairness.  (IEEE & Loza de Siles, n.d.) says, “Under the Act, this agency regulates conduct involving the Internet and otherwise as that conduct relates to consumers and competition.”    In this act, there are three main components that categorizes unfair or deceptive acts:

  • The act or practice results in substantial consumer injury
  • The consumer cannot reasonably avoid that injury
  • The harm caused by the act or practice is outweighed by countervailing benefits to consumers or to competition.

An actor’s unfair act or practice may not be the cause of consumer injury for the actor to be liable under the Act, (IEEE & Loza de Siles, n.d.).     The FTC prosecuted several Whyndam companies for unfair acts or practices as to the Cybersecurity risks to hotel guests’ personal information where hackers ended up exploiting those risks on three separate occasions, injuring 619,000 consumers.  (IEEE & Loza de Siles, n.d.) continues, “Under the FTC’s unfairness authority, IoT and other companies must use “reasonable security measures” to protect consumers’ data.”  This is very promising that consumers are being protected in this manner as this is long overdue.  However, the vagueness again much like the definition of IoT is still the issue.  There needs to be more policy writing that will foster more concrete laws that move with the dynamic changing landscape.  This does show the overall support of the government agency in the protection of this newly emerging field.

 

HTC is another example of how the FTC was willing to go after offenders in this grey area of this Act.  The FTC alleged that HTC failed to implement reasonable security measures where HTC, among other illegal conduct, introduced permission re-delegation vulnerabilities in its customized, pre-installed mobile applications on Android-based phones and thereby undermined the operating system’s more protective security model, (IEEE & Loza de Siles, n.d.).  This shows how even though the policy is archaic there is still a government entity looking to look out for consumers. Accordingly, the important take-away regarding the FTC’s Tried and True Guidance is that what constitutes “industry-tested and accepted methods” of data security is dynamic and a constantly moving target, (IEEE & Loza de Siles, n.d.).   But when does this “reasonable security measures” end.  One could clearly see how this may deter innovators from pursuing such areas of interest.  In the end, there needs to be more capable policy writers to keep up with the times. It looks as though there are severe re-writes that need to happen in the next five to ten years.  Only then will innovators and security experts truly see eye to eye.

Conclusion

One of the fastest growing areas in technology is the introduction of the concept (IoT) Internet of things.  However, a very exciting time.  There is a some very important new emerging technologies to take note of.  That will allow for more innovation in the IoT field.  As the field continues to grow there will allows be more potential risks.  The emerging security solutions and methodologies are grossly behind.  The policy is even more behind the technology to help combat some of the threats that IoT faces.  For this field to get the growth it needs cyber policy needs to be written to allow for innovators in the field to have comfort in developing in this space.  Until this is done there will not be enough significant innovation to elevate all the security threats due to the inability to in fuse a startup in this space without thinking an investment is going to go directly to liability issues in a few years or even worse in its first year.  The ability to see the government take initiative to protect is however very refreshing.

 

References

CHALLA, S., WAZID, M., KUMAR DAS, A., KUMAR, N., REDDY, A., YOON, E., & YOO, K. (2017). Secure signature-based authenticated key establishment scheme for future iot applications. IEEE Access5, 3028-3043. Retrieved from http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7867773

Forbes, & Morgan, J. (2004, May 13). A simple explanation of ‘the internet of things’. Retrieved from https://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-things-that-anyone-can-understand/#697fb71f1d09

Gartner Research. (n.d.). Internet of things defined – tech definitions by gartner. Retrieved from http://www.gartner.com/it-glossary/internet-of-things/

Hasan, M. M., & Mouftah, H. T. (2016). Optimal trust system placement in smart grid scada networks. IEEE Access4, 2907-2919. doi:10.1109/access.2016.2564418

IEEE, & Loza de Siles, E. (n.d.). Cybersecurity Law and Emerging Technologies Part 1 – IEEE Future Directions. Retrieved from http://sites.ieee.org/futuredirections/tech-policy-ethics/may-2017/cybersecurity-law-and-emerging-technologies-part-1/

Odelu, V., Das, A. K., Khurram Khan, M., Choo, K. R., & Jo, M. (2017). Expressive cp-abe scheme for mobile devices in iot satisfying constant-size keys and ciphertexts. IEEE Access5, 3273-3283. doi:10.1109/access.2017.2669940

RFC 7516 – JSON Web Encryption (JWE). (n.d.). Retrieved from https://tools.ietf.org/html/rfc7516

RFC 7519 – JSON Web Token (JWT). (n.d.). Retrieved from https://tools.ietf.org/html/rfc7519

 

Scammers or Terrible Social Engineers?

Scammers are on the rise these days, from email scams to phone scams, and even in the mail. Let’s start with email/internet scams. My goal is to use up as much of the scammers time as I can an I use a few ways to verify the scammers location. Usually you will get an email from some prince or someone who is in the hospital wanting to give you their life funds because they don’t trust their family. Don’t respond or give them any information. They all use the same terminology when speaking to you as well. “Can you KINDLY respond back to me”. “Kindly” is one of their favorite words. Another red flag is the payment method, they will ask for a money graham or western union transfer to a name you have not heard of. Most scammers I have dealt with have been very bad at answering questions because that is a waste of their time. Their goal is to make you feel like you are dealing with a very smart individual who will send you what you have ordered or what you are talking about in the discussion. Check the email address they send it from and use reverse email website to see if you can find out more on who you are talking about.

Such site includes:

Pipl.com

Thatsthem.com

Truepeoplesearch.com

 

These sites are free and easy to user when it comes to reverse email look-ups. They won’t give you a real name so it’s not worth trying to locate.

Another thing to try to get the scammers to do is click a link that has been tagged by an IP logger. What is an IP logger you might say. It is a link that has been modified or changed so that the person clicking on it will give out their location. Scammers work on a network of different locations. Most of the time the location of where they want the money sent isn’t where they are. They have a pickup person in one place who sends the funds to someone in another location. This makes the whole operation harder to locate and most of the time the funds to leave the united states or the country the scam is located in. If you can split your operation you are harder to find. The Two main IP loggers I use are:

https://ip-logger.gear.host/

https://iplogger.org/

They are very accurate and do well.

Example, A website I am currently investigating is http://www.cheappurebredpuppies.com/ they have pulled information off other dog breeders websites and pulled them to their own using older pictures as well. I have used two different Email addresses to contact them, both times I have gotten a different name to send a money graham too. That is what they use for their operation as well, harder to track and non-refundable. The thing is if they don’t get what they want from you they will either threaten you or move on to the next person they are scamming. This is one of the examples when you trying to purchase an item from them. On the contrary when they are buying something from you they use similar tactics and usually want to send you more money than the item is worth. The reason for this is so you can cash it and they have your bank realize its fraud while you send the money back to them. In one case I have had them send an expedited check to me at my job to test out them sending the document to me.

 

Second is Tech support scammers. They are getting craftier, I have A set of videos on this. Microsoft will never call you if your computer has a virus. This section will be a little shorter and I’ll link my YouTube page to it. Their goal is to craft webpages that look like Microsoft errors and be very identical the actual Microsoft website if you have not paid attention to how it looks. Pay attention to the web address line and make sure it is a Microsoft website. Scammers do not affiliate themselves with the actual company. They state that they are techs to fix your computer approved my Microsoft. They have many techniques to make you think you have virus’s. Please visit my YouTube page for more on how they work. https://www.youtube.com/channel/UCsPThvyPrIr7otuVgnFVzTg

 

In conclusion, Scammers, or social engineers are out there daily trying to steal your money from you, they come in many forms. IRS calls to door to door salesman. Be careful who you talk to and who you share your information with or who you allow to use your computer.

 

Signing off!

 

WannaCry Ransomware : What is it and How to Protect against it

 

The WannaCry ransomware burst into the spotlight over the weekend as reports of infections streamed in from around the globe. This has affected systems in more than 150 countries with more than 230,000 computers infected.

What is Ransomware?

Ransomware is a type of malicious software(computer virus) that encrypts and blocks access to data until a ransom is paid. It usually spreads via spam emails and malicious download links and displays a message requesting payment to decrypt it.

 

The WannaCry ransomware A.K.A. Wanna Decryptor, uses a leaked NSA exploit Eternal Blue that targets Windows SMB service which can be used to hijack computers running unpatched, vulnerable Microsoft Windows operating system.

The ransomware that has affected systems in more than 150 countries recently. It leverages Social Engineering/Spear Phishing as their attack vector by sending some malicious links or a PDF file, which when clicked, installs the ransomware. Once installed, it scans the entire network for other vulnerable devices and spreads.

Follow these steps to prevent infection:

  • Update your system.
  • Upgrade to windows 10 if you are using older versions. Keep it updated.
  • If you are using older versions of windows , apply these patches immediately.
  • Enable Firewall, block access to SMB ports – TCP – 137,139 and 445 and UDP – 137 and 138.

https://blogs.technet.microsoft.com/msrc/2017/05/12/customer-guidance-for-wannacrypt-attacks/

  • SMB is enabled by default on Windows. Disable SMB service –

https://support.microsoft.com/en-in/help/2696547/how-to-enable-and-disable-smbv1,-smbv2,-and-smbv3-in-windows-vista,-windows-server-2008,-windows-7,-windows-server-2008-r2,-windows-8,-and-windows-server-2012

  • Have a pop-up blocker running on your web browser.
  • Update your antivirus.
  • Backup your data regularly.
  • Do not open any attachments from any Unknown sources.

 

WHAT IF YOU ARE INFECTED?

Never Pay ransom.

Its upto you whether to pay the ransom or not. There is no guarantee that you will get your files back.

Social Networking Threats

SECURITY IS ALL ABOUT KNOWING WHO AND WHAT TO TRUST

 

 

Social networking service (also social networking site, SNS or social media) is an online platform that is used by people to build social networks or social relations with other people who share similar personal or career interests, activities, backgrounds or real-life connections.

Social Network Sites such as Twitter, Facebook, Google+ , Pinterest, Instagram have attracted millions of users, many have integrated these sites into their daily practices. There are many sites, with various technological features which support a wide range of interests and practices. Most of them can be linked to their pre-existing social networks which help strangers connect and interact based on shared interests or activities.

This interaction reveals a lot of information, often including personal information visible to anyone who wants to view it. Hence privacy is often a key concern by the users.

Since millions of people are willing to interact with others, it is also a new attack ground for malware authors. They can spread malicious code and send spam messages by taking advantage of the user’s inherent trust in their relationship network.

Here are some of the threats targeting different social networks today.

  • Social engineering:

Social engineering refers to the method of influencing and persuading people to reveal sensitive information in order to perform some malicious action. It is easier to fool someone than to find vulnerabilities to hack a system.

An attacker chats with someone and then try to elicit information. By using a fascinating picture while chatting, the attacker can try to lure the victim. Then, slowly the attacker can ask certain questions by which the target can elicit information. They ask different questions to get the target’s email and password. Attackers first create deep trust with the target and then make the final attack. Gaining Trust is one of the phases in social engineering.

Common attacks:

Email with a link or an attachment that has malicious code embedded. Clicking or Downloading it will run the code and infect the target system.

This is one serious problem people face online today. Do not trust anyone online. Avoid sharing personal information.

 

  • Identity Theft:

It Is easy to access an account when the attacker has some personal information. For example, a common technique used is by clicking on “forgot password” and trying to recover the information through email or security questions. Once they have access to your email account, they then have access to all information on your social networking sites.

This can be prevented using 2FA (Two Factor Authentication).

Never share your personal information online.

 

  • Phishing bait :

Phishing is the attempt to obtain sensitive information such as usernames, passwords, often for malicious reasons, by masquerading as a trustworthy entity in an electronic communication. Phishing is an example of social engineering techniques used to deceive users.

Attacker could create a clone of a website that is infected with malware and tell you to enter personal information. Phishing is typically carried out by email spoofing or instant messaging, and it often directs users to enter details at a fake website whose look and feel are almost identical to the legitimate one.

Always make sure the URL’s are legitimate  before opening them.

 

  • Shortened links / URLs:    

Always be careful while opening a shortened URL.

URL shortening services such as bit.ly ,tinyurl, goo.gl are used to fit long URLs into tight spaces. They also do a nice job of obfuscating the link so it isn’t immediately apparent to victims that they’re clicking on a malicious link. These shortened links are easy to share.

 

Only click on links from trusted sources. This may not always protect you, but helps lower the risk.

Update browsers and operating systems regularly with the latest security updates.

 

 

  • Apps :

Try not to use apps like :

  • Facebook color changer
  • Celebrity Face Match
  • Who viewed your facebook profile
  • NSFW videos
  • Twitter instant followers
  • Pinterest bogus pins
  • Instagram free likes

These things asks you to post it on your profile or share it with your friends or watch a video tutorial. And some provide those functions. But what it actually does is allow attacker to obtain access to your profile and spam. Which can also infect mobile devices.

Change your passwords regularly. Delete unnecessary apps. Do not trust third party notifications. Be cautious about giving unverified apps or services access/permission to your account. Download apps from trusted source.

 

  • CSRF – cross site request forgery:

Cross-site request forgery, also known as one-click attack or session riding and abbreviated as CSRF (sometimes pronounced sea-surf) or XSRF, is a type of malicious exploit of a website where unauthorized commands are transmitted from a user that the website trusts. Unlike cross-site scripting (XSS), which exploits the trust a user has for a particular site, CSRF exploits the trust that a site has in a user’s browser.

When you click on a link on a webpage, your browser sends a request to the Web server. These requests can broadly be categorized into two types: GET and POST.  A GET request is simply a request for a page, e.g. When you browse www.google.com. A POST request is sent when you send data to the server, e.g. if you search anything on Google, this would be sent as a POST request.

But what if it were possible to send a request from a user’s browser without the user’s consent?

It’s possible.

It’s simple and it’s called Cross Site Request Forgery.

Malicious requests are sent from a site that a user visits to another site that the attacker believes the victim is validated against.

The malicious requests are routed to the target site via the victim’s browser, which is authenticated against the target site.

PREVENTING CSRF :
The most common method to prevent Cross-Site Request Forgery attacks is to append unpredictable challenge tokens to each request and associate them with the user’s session. Tokens should be unique per user session, but it can also be unique per request. By including a challenge token with each request, the developer can ensure that the request is valid and not coming from a source other than the user.

 

  • Clickjacking :

Clickjacking (UI redress attack) is a malicious technique of tricking a user into clicking on something different from what the user perceives they are clicking on, thus taking control of their computer while clicking on seemingly innocuous web pages. It is a browser security issue that is a vulnerability across a variety of browsers and platforms. A clickjack takes the form of a script that can execute without the user’s knowledge, such as clicking on a button that appears to perform another function.

For example, imagine an attacker who builds a web site that has a button on it that says “click here for a free iPod”. However, on top of that web page, the attacker has loaded an iframe with your mail account, and lined up exactly the “delete all messages” button directly on top of the “free iPod” button. The victim tries to click on the “free iPod” button but instead actually clicked on the invisible “delete all messages” button.

To prevent, keep your browser updated.

Digital Forensics Comparison of Data Source Relevance per Investigations

Digital Forensics Comparison of Data Source Relevance

Many different sciences are grounded in the fact that certain information will never change.  For instance, gravity never changes, water molecules can be a liquid, solid, and a gas, and DNA can help match identity in human beings.  In digital forensic this is different because the medium in which they work is technology and technology changes all the time.  Keeping up on the latest in technological advances and their data sources which are common places to get specific information can be the difference between winning and losing a case.  Knowing where to look and in which order can change based on the type of investigation that a digital forensic investigator is working on.  We will look at the collection and examination of data sources based on the more common investigation that have been seen.

Network Intrusion Investigation

Network intrusions are a continual problem and will be for some time.  There won’t be a shortage of network intrusion investigations happening anytime soon.  (Fung 2013) says, “The Pentagon reports getting 10 million attempts a day.”  Which is scary and incredible statistic on its own.  But this isn’t just at the government agency level.  BP the energy company has been experiencing 50,000 attempts of cyber intrusion per day, (Fung 2013). In a recent report from Verizon not only are network intrusions steadily moving up, but it shows the time to compromise decreasing, (Verizon, 2016, p. xx).  This puts a large amount of pressure on the digital forensics community to speed their time for discovery.

Some of the different types of data that would need to be collected in a network intrusion investigation would be:

  • IDS and Firewall logs
  • HTTP, FTP, SMTP logs
  • Network Applications logs
  • Backtracking Transmission with TCP connections
  • Artifacts and remnants of network traffic on hard drives of seized systems
  • Live traffic captured by packet sniffer
  • Individual systems ARP tables, SNMP messages

Collection

Collecting data from these different areas are more challenging than other data in other areas of the system.  The data given will differ in all investigation but the object is to find any time of consistency in network intrusion investigations.  Many of the network intrusion investigations deal with network state.  Discovering the network state allows forensic experts to find possible entry points.  One of the first things that needs to be done is painting a picture of the network configuration.  Knowing a blue print of external facing applications and or api’s.  A beneficial tool in this scenario will be the ability to create an accurate timeline of events.  So, the number one priority of this investigation would be obtaining system and application logs.  This will allow a forensic expert to formulate a timeline. In Table 1 we can see that there are numerous types of data sources to pull data from.  However, the internal network and system logs which include Firewall, IDS, and Active Directory logs proves the most viable data sources to look for in this specific type of investigation.  There is also a very high probability of collection since most of the information is obtained by taking a snapshot of the logs from a cooperative network administrator.

Table 1. Shows the different data sources in a network intrusion investigation

In a network intrusion investigation, a forensic expert wants visibility at the packet level.  Both in bound and out bound.  The below prioritization of data sources is as follow:

  1. Internal Network System Logs
  2. ISP Service Logs
  3. Computer and or server hard drives

Examination

Examining the data that was found is a separate story.  Internal logs will contain the information that a forensic expert needs to build the important event timeline, however there will be could be large amount of data to examine.  Thanks to tools like encase this becomes slightly easier for the forensic expert.  This is where IDS systems play a huge role.  Intrusion Detection Systems can capture anomaly based events or statistical based events.  These will be flagged by an alert.  Focusing on the alerts that were presented can give a great starting point in the examination of a network intrusion investigation.  This is not the end all be all data source to look at in a network intrusion investigation in fact many things could change the type of data that a forensic expert gets back.  (Forensic Mag, 2013) says “any number of activities or events might influence or affect the collected data in unknown ways, including TCP relaying, proxy servers, complex packet routing, Web and e-mail anonymizers, Internet Protocol (IP) address or e-mail spoofing, compromised third party systems, session hijacking and other person-in-the-middle attacks, and domain name system (DNS) poisoning.”  Also, if there is a sophisticated network intrusion logs have the potential in being deleted or cleared.  The examination of the internal network logs is invaluable in this type of investigation.

ISP server logs also pose a great data source primarily because they can give you a general location of where the network intrusion came from.  Ultimately leading to an arrest.  Obtaining this session data can be done by obtaining a warrant for a specific customer.  This will give a forensic expert all pertinent data that an ISP has to a specific investigation, (Forensic Mag, 2013).

Malware Intrusion Investigation

Malware intrusion investigations include but not limited to worms, Trojans, botnets, rootkits and ransomware.  Malware is a huge problem in the United States and abroad.  (Panda Labs, 2016) says, “18 million new malware samples were captured in this quarter alone, an average of 200,000 each day.”  As seen below in Figure 1.  The most unbelievable part of this statistic is that this is based on just one quarter.  Malware investigations are on the rise.  Understanding how malware enters a computer and how it communicates gives the forensic expert a huge advantage in locating the exact places on a compromise system to look.  Which in turn increases the efficiency of the investigation.

Figure 1. Malware identified over the years.

Collection

Malware investigations unlike the network intrusion investigation predominantly looks at the malware itself.  Understanding how the malware was introduce may lead to a conviction.  Understand the level of complexity, damage and data leakage will be found on the hard drive of the infected computer or server itself.  More importantly at the RAM level.  As a matter of fact, (SANS Digital Forensics and Incident Response Blog, 2016), says “Investigators who do not look at volatile memory are leaving evidence at the crime scene.” Much like the data collected for the network intrusion investigation forensic experts need to understand a basic knowledge of what the operating system considers normal behavior.  For this network, golden images and IDS solutions may help identify normal behavior.  But the volatile memory on disk will be the number one for this type of investigation.  (SANS Digital Forensics and Incident Response Blog, 2016), continues by saying “It is this evidence that often proves to be the smoking gun that unravels the story of what happened on a system.”

Table 2. Depicts the order of data sources in a Malware installation investigation.

 

Examination

The examination of the volatile memory on the compromised computer or server will yield user actions, as well as evil processes and furtive behaviors implemented by malicious code, (SANS Digital Forensics and Incident Response Blog, 2016).  As RAM, would be the top data source that a forensic expert would be looking at, the Registry if this is a windows machine would also be of interest.  Time zone information, audit policy, wireless SSIDs, locations of auto-start programs, user activities and mounted devices can all be obtained from the windows registry, (Nelson, Phillips, & Steuart, 2010, p. xx).  As demonstrated in figure 2 below.  In figure 3 there is usb device information that can be obtain from the registry.  This would all be valuable information when studying if the malware moved from computer to computer on the internal network and it behaves in general.  Also, studying network logs to see if the malware is communicating with an external server would also be a data source to examine.  The prioritized list of all of the data sources for the malware installation investigation would like as followed:

  1. Computer / Server HD
  2. Internal Network System Logs
  3. ISP Server Logs

Figure 2. Shows the history obtained from a Windows 7 registry.

Figure 3. Depicts a registry value where USB device that was plugged into the computer

 

Figure 4. Shows the created date and last access date of a wireless network

 

Insider File Deletion Investigation

One of the biggest threats to a business is the insider threat. Insiders include anyone authorized beyond the authority of the public.  (Cohen, 2012, p. xx) says, “Specifically, 76% of disloyal insiders were identified after being caught to have taken steps to conceal their identities, actions, or both, 60% compromised another’s user’s account to carry out their acts, and 88% involved either modification or deletion of information.”  This includes a disgruntled employee that has possibly turned or a possible hired employee planted in the company working on behalf of another company.  One of the main reasons that this is such a difficult threat to detect is largely because the employee is given regular access to a company’s network.  Which allows for them to know where sensitive data is kept.

Collection

In this insider deletion investigation access to an offender’s hard drive of their computer would be a great first step.  Collection of this would more than likely show nothing since the insider more than likely would try and cover his or her tracks.  But using the person’s hard drive would give a forensics expert the ability to see if there are more devices that need to be considered in the investigation such as removable devices and remote storage.  In the event of file deletion, access to the computers that the data was deleted from can tell information about what account deleted the file.  (Cohen, 2012, p. xx) continues by saying, “While it is possible that an insider might use known malicious attack methods typically detected by intrusion detection methodologies and system, doing things that trigger such systems is rarely if ever necessary for an authorized insider.”  So as the network and system logs still might prove useful this would be very difficult to identify.

Figure 4. Shows Active directory of a user and his/her last login.

Examination

The data that will be gained from the registry of the insider’s computer HD registry would be the best starting point here.  Allowing a forensic expert to gauging a since of normal computer usage and seeing if there are any anomalies.  Using the data from the network active directory that controls the user accounts for the entire company would allow forensic experts to pin point the account that was used in the deletion.  In an examination combining the physical sensors, key card access, and account access from system logs proves to be invaluable.  In figure 4 above there is useful information that can be gotten from Active directory as well.  Examiner use this to combine this data together to understand consistencies and inconsistencies.  This could also give a forensic expert an approximate time of when this happened allow the examiner to build a potential timeline for the investigation.  As seen below in table 3 the starting point would be the compromised files on the hard drive of the given computer or server.

Table 3.  Data sources ranking in an insider deletion investigation

Conclusion

As we can see there are many different areas where a forensic expert can look for data.  As technology continues to advance these numbers will grow.  The amount of time that it takes to compromise a system versus the amount of time it takes to discover is still very far apart.  Which leads to the ultimate consensus in my findings that to be the forensic investigator on anyone of these investigations one would have to look everywhere.  Having a general understanding of the crime does help in many scenarios but not all.  When certain security measures aren’t put into place there is little an examination can do specifically in the insider threat scenario.  The forensic examination is only as good as the carelessness of the insider and the security that was in place at the time.  Having general guidelines, a clear understanding of the investigation, and a priority list of known data source places can go a very long way.

References

National Institute of Justice (U.S.). (2004). Special report, forensic examination of digital evidence: a guide for law enforcement (199408). Retrieved from publisher not identified website: https://www.ncjrs.gov/pdffiles1/nij/199408.pdf

National Institute of Justice (U.S.). (2007). Report, investigations involving the internet and computer networks. Retrieved from website: https://www.ncjrs.gov/pdffiles1/nij/210798.pdf

SANS Digital Forensics and Incident Response Blog. (2016, October 29). Digital forensics and incident response blog | malware can hide, but it must run. Retrieved from https://digital-forensics.sans.org/blog/2016/10/29/malware-can-hide-but-it-must-run/

Cohen, F. (2012). Forensic methods for detecting insider turning behaviors. 2012 IEEE Symposium on Security and Privacy Workshops. doi:10.1109/spw.2012.21

Forensic Mag. (2013, May 28). The case for teaching network protocols to computer forensics examiners: part 1. Retrieved from http://www.forensicmag.com/article/2013/05/case-teaching-network-protocols-computer-forensics-examiners-part-1

Fung, B. (2013, March 8). How many cyberattacks hit the united states last year? Retrieved from http://www.nextgov.com/cybersecurity/2013/03/how-many-cyberattacks-hit-united-states-last-year/61775/

Panda Labs. (2016, October 20). Cybercrime reaches new heights in the third quarter. Retrieved from http://www.pandasecurity.com/mediacenter/pandalabs/pandalabs-q3/

Shephard, D. (2015, March 16). 84 fascinating & scary it security statistics. Retrieved from https://www.netiq.com/communities/cool-solutions/netiq-views/84-fascinating-it-security-statistics/

Verizon. (2016). 2016 data breach investigations report. Author.

 

Top Places for Malware to hide 2017

With most of the commercial anti-virus software vendors using signature based malware classification methods this becomes a bit of a game of creating code that is obfuscated just enough to change the signature to be undetected.  (Shijo & Salim, 2015, p. xx) say, “In static analysis features are extracted from the binary code of programs and are used to create models describing them.”  This is the most commonly used method of detection and obfuscation is the simple work around. Signatures need to be frequently updated to catch the common malware, while malware makers can simply change the obfuscation of the code.  One never catches up with the other. (Shijo & Salim, 2015, p. xx) continues by saying, “The static analysis fails at different code obfuscation techniques used by the virus coders and also at polymorphic and metamorphic malware’s.”  What also fails is the dynamic analysis due to the behavior of a program that is monitored while in execution.  The problem is malware has to be done in a secure environment for a specific amount of time this is a limitation due to the amount of time that it takes to create this maleware.

The first way that malware tries to hide itself is in the windows registry.(AlienVault, 2016) says, “the Windows registry is quite large and complex, which means there many places where malware can insert itself to achieve persistence.” An simple example is the Poweliks sets a null entry utilizing one of the built-in Windows APIs, ZwSetValueKey, which allows it to create a registry key with an encoded data blob, (AlienVault, 2016).  From this point it can hide out and autostart and maintain persistence of many systems.

The second way malware will hide itself is process injection.  This is where the malware hijacks a running process and puts bits of code into it.  (AlienVault, 2016) says, “Malware leverages process injection techniques to hide code execution and avoid detection by utilizing known “good” processes such as svchost.exe or explorer.exe.”

A third example would be physical.  This is where the malware could possibly be stored on the slack partition of the drive.  (Berghel, 2007, p. xx)  says, ” At the sector level, any unused part of a partially filled sector is padded with either data from memory (RAM slack) or null characters (sector slack).”  The location is ideal because the Operating System doesn’t have access to this portion of the data normally.  This can lay dormant and resurface based off of specific commands.

References

AlienVault. (2016, October 3). Malware hiding techniques to watch for: alienvault labs. Retrieved from https://www.alienvault.com/blogs/labs-research/malware-hiding-techniques-to-watch-for-alienvault-labs

Shijo, P., & Salim, A. (2015). Integrated static and dynamic analysis for malware detection. Procedia Computer Science46, 804-811. doi:10.1016/j.procs.2015.02.149

Berghel, H. (2007). Hiding Data, Forensics, and Anti-Forensics. Communications Of The ACM50(4), 15-20. doi:10.1145/1232743.1232761

Browser Attacks and Network Intrusion

Research Synthesis and Analysis of Browser Attacks and Network Intrusion

Browser attacks and network intrusion are drawbacks users face every day for being connected to the internet in one way or another.  One has to access a browser to be served content on the web and one has to be connected to a network to view the web.  We will take a closer look at both in this paper.

Browser Attacks

Browser attacks come in many different forms, making them very difficult to defend against. OWASP, which stands for open web application security project is a nonprofit organization which has made an effort to identify the many types of browser based attacks in the wild.  OWASP is more well-known for its project called OWASP top ten project.  The top ten biggest browser based attacks are as follows:

  1. Injection
  2. Broken Authentication & Session Management
  3. XSS or Cross Site Scripting
  4. Insecure Direct Object Reference
  5. Security Misconfiguration
  6. Sensitive Data Exposure
  7. Missing Function Level Access Control
  8. Cross Site Request Forgery
  9. Using Components with knows vulnerabilities
  10. Invalidated Redirect & Forwards

These are the ten main categories that browser attacks fall into.  An even more daunting task is that even though the list may have been created in 2013, most of these categories are still visible on the internet and can be used in today’s internet landscape.

Major Issues, Problems

The problems with browser attacks are largely due to the overwhelming number of browsers that are available to users.  Not all browsers handle content the same way and not all browsers protect against vulnerabilities in the OWASP top ten in the same manner.  With the five biggest browsers being Chrome, IE, Firefox, Safari, and Opera there are also the problem of versions of these top five.  This enables a vulnerability to remain in the opened to be used to attack until a user gets around to updating their browser.  An even greater issue is that a web application could exist and is made in 2013 and heavily used by a company.  A company may not be able to upgrade the web application because of resources.  However, this ultimately doesn’t work in modern browsers leaving potentially 1000 of computers susceptible to all vulnerabilities since 2013 in this web browser.

If this wasn’t alarming enough users have created frameworks that allow security researchers and engineers to test these web applications in their companies.  One penetration testing framework is the BEEF framework.  This framework has compiled many of the vulnerabilities in the OWASP top ten into a single interface which is used to exploit browsers which they call “hooking”.  Beef was built by a group of developers to explore the vulnerabilities in browsers and test them specifically Beef is an excellent platform for testing a browser’s vulnerability to XSS and other injection attacks, (Null Byte, 2015).

New malware is being developed in the wild which is taking advantage of these browser vulnerabilities and exploiting them for man in the middle browser attacks.  (Khandelwal, 2016) says, “Besides process level restrictions bypass, the AtomBombing code injection technique also allows attackers to perform man-in-the-middle (MITM) browser attacks, remotely take screenshots of targeted user desktops, and access encrypted passwords stored on a browser.”  In a recent article the AtomBombing malware was dubbed to have no patch.  (Khandelwal, 2016) says, “Since the AtomBombing technique exploits legitimate operating system functions to carry out the attack, Microsoft cannot patch the issue without changing how the entire operating system works. This is not a feasible solution, so there is no notion of a patch.”

Analysis, Ideas, and Solutions

Looking at some of the above browser based attacks as you can see in the case of the AtomBombing there is little that can be done.  However, there are some general practices that can help an organization and or a normal computer user to defend against a large portion of these attacks, (How to Geek, n.d.).

  1. Keep your browser updated
  2. Enable Click-to-Play Plug-ins
  3. Uninstall Plug-ins you don’t need
  4. Keep Plug-ins updated
  5. Use a 64-bit Web Browser
  6. Run an Anti-Exploit Program
  7. Use Caution When Using Browser Extensions

In a work scenario, many of the above list will be able to be restricted through a group policy.  Many of these browser attacks have specific signature that can be spotted by a good intrusion detection system like SNORT or Dell SonicWall.  Also with a tool like Dell Kace you can track inventory of all web browsers that are being used within a company’s network to make sure there aren’t any legacy browsers floating around.

Network Intrusion

Network intrusion is something that everyone must deal with when connected to the internet whether it’s a person’s home network or work.  (Moskowitz, 2014) defines, “A network intrusion is any unauthorized activity on a computer network.”  Many believe this could be using the network for something it wasn’t intended to do whether consciously or subconsciously. (Moskowitz, 2014) continues, “In most cases, such unwanted activity absorbs network resources intended for other uses, and nearly always threatens the security of the network and/or its data. “

Major Issues, Problems

The largest problem that we have with network intrusion attacks is the scale of which the network is growing.  With the emergence of internet of things, toasters and thermostats now fall susceptible to old attack vectors in networking.  (Hodo et al., n.d.) says, “Research conducted by Cisco reports there are currently 10 billion devices connected, compared to the world population of over 7 billion and it is believed it will increase by 4% by the year 2020.” At an RSA conference a researcher discussed some very popular attack vectors that come up often when discussing network intrusion these are:

  1. Asymmetric Routing
  2. Buffer Overflow Attacks
  3. Scripts
  4. Protocol-Specific Attacks
  5. Traffic Flooding
  6. Trojans
  7. Worms

Intrusion to a network can come in two main forms whether External Intruders, where these are people that will more than likely use malware or exploits to gain access to a system or Internal Intruders, these are people misuse the system by changing important data or theft of confidential data.

Analysis, Ideas, and Solutions

Intrusion detection systems bring the most hope to the defense from many of these attack vectors discussed.  Whether (HIDS) Host-Based or (NIDS) network based.  There are many different flavors of IDS systems and selecting the right system is very important and unique to budget and normal network usage.  Some use signature based others are using anomaly based systems or pattern recognition.  Recently we’ve seen a rise in hybrid approaches taking the best of both worlds.  The four different techniques which are used are Statistical analysis, Evolutionary algorithm, Protocol verification, and Ruled Based or signature based systems.  Ultimately these systems when used appropriately will catch uncharacteristic traffic.  Some need a baseline of traffic to get started some work directly out of the box like a signature based system.  As the networks continue to get more and more complex so do these IDS systems.  The ability to pool known attacks into a signature share through all companies is a powerful tool but now the landscape is changing and attacks are becoming more targeted in nature.  Anomaly based systems need to be used in conjunction with signature based.  Many companies are faced with a resource issues as anomaly based systems need monitoring since the potential of false positives are a lot higher.

 

 

 

References

Hodo, E., Bellekens, X., Hamilton, A., Dubouilh, P., Iorkyase, E., Tachtatzis, C., & Atkinson, R. (n.d.). Threat analysis of iot networks using artificial neural network intrusion detection system. Paper presented at the meeting of the International Symposium on Networks, Computers and Communications, Hammamet, Tunisia.

How to Geek. (n.d.). 7 ways to secure your web browser against attacks. Retrieved from http://www.howtogeek.com/228828/7-ways-to-secure-your-web-browser-against-attacks/

Khandelwal, S. (2016, October 27). This code injection technique can potentially attack all versions of windows. Retrieved from http://thehackernews.com/2016/10/code-injection-attack.html

Moskowitz, R. (2014, December 25). Network intrusion: methods of attack | rsa conference. Retrieved from https://www.rsaconference.com/blogs/network-intrusion-methods-of-attack

Null Byte. (2015). Hack like a pro: how to hack web browsers with beef « null byte. Retrieved from http://null-byte.wonderhowto.com/how-to/hack-like-pro-hack-web-browsers-with-beef-0159961/

OWASP. (n.d.). Category:owasp top ten project – owasp. Retrieved from https://www.owasp.org/index.php/Top10#OWASP_Top_10_for_2013

 

The Theory (Hashing Functions, Salt, Pepper) – Explained

We need to hash passwords as a second line of defense. A server which can authenticate users necessarily contains, somewhere in its entrails, some data which can be used to validate a password. A very simple system would just store the passwords themselves, and validation would be a simple comparison. But if a hostile outsider were to gain a simple glimpse at the contents of the file or database table which contains the passwords, then that attacker would learn a lot. Unfortunately, such partial, read-only breaches do occur in practice (a mislaid backup tape, a decommissioned but not wiped-out hard disk, an aftermath of a SQL injection attack — the possibilities are numerous). See this blog post for a detailed discussion.

Since the overall contents of a server that can validate passwords are necessarily sufficient to indeed validate passwords, an attacker who obtained a read-only snapshot of the server is in position to make an offline dictionary attack: he tries potential passwords until a match is found. This is unavoidable. So we want to make that kind of attack as hard as possible. Our tools are the following:

  • Cryptographic hash functions: these are fascinating mathematical objects which everybody can compute efficiently, and yet nobody knows how to invert them. This looks good for our problem – the server could store a hash of a password; when presented with a putative password, the server just has to hash it to see if it gets the same value; and yet, knowing the hash does not reveal the password itself.
  • Salts: among the advantages of the attacker over the defender is parallelism. The attacker usually grabs a whole list of hashed passwords, and is interested in breaking as many of them as possible. He may try to attack several in parallels. For instance, the attacker may consider one potential password, hash it, and then compare the value with 100 hashed passwords; this means that the attacker shares the cost of hashing over several attacked passwords. A similar optimization is precomputed tables, including rainbow tables; this is still parallelism, with a space-time change of coordinates.The common characteristic of all attacks which use parallelism is that they work over several passwords which were processed with the exact same hash function. Salting is about using not one hash function, but a lot of distinct hash functions; ideally, each instance of password hashing should use its own hash function. A salt is a way to select a specific hash function among a big family of hash functions. Properly applied salts will completely thwart parallel attacks (including rainbow tables).
  • Slowness: computers become faster over time (Gordon Moore, co-founder of Intel, theorized it in his famous law). Human brains do not. This means that attackers can “try” more and more potential passwords as years pass, while users cannot remember more and more complex passwords (or flatly refuse to). To counter that trend, we can make hashing inherently slow by defining the hash function to use a lot of internal iterations (thousands, possibly millions).

We have a few standard cryptographic hash functions; the most famous are MD5 and the SHA family. Building a secure hash function out of elementary operations is far from easy. When cryptographers want to do that, they think hard, then harder, and organize a tournament where the functions fight each other fiercely. When hundreds of cryptographers gnawed and scraped and punched at a function for several years and found nothing bad to say about it, then they begin to admit that maybe that specific function could be considered as more or less secure. This is just what happened in the SHA-3 competition. We have to use this way of designing hash function because we know no better way. Mathematically, we do not know if secure hash functions actually exist; we just have “candidates” (that’s the difference between “it cannot be broken” and “nobody in the world knows how to break it”).

A basic hash function, even if secure as a hash function, is not appropriate for password hashing, because:

  • it is unsalted, allowing for parallel attacks (rainbow tables for MD5 or SHA-1 can be obtained for free, you do not even need to recompute them yourself);
  • it is way too fast, and gets faster with technological advances. With a recent GPU (i.e. off-the-shelf consumer product which everybody can buy), hashing rate is counted in billions of passwords per second.

So we need something better. It so happens that slapping together a hash function and a salt, and iterating it, is not easier to do than designing a hash function — at least, if you want the result to be secure. There again, you have to rely on standard constructions which have survived the continuous onslaught of vindictive cryptographers.

Good Password Hashing Functions

PBKDF2

PBKDF2 comes from PKCS#5. It is parameterized with an iteration count (an integer, at least 1, no upper limit), a salt (an arbitrary sequence of bytes, no constraint on length), a required output length (PBKDF2 can generate an output of configurable length), and an “underlying PRF”. In practice, PBKDF2 is always used with HMAC, which is itself a construction built over an underlying hash function. So when we say “PBKDF2 with SHA-1”, we actually mean “PBKDF2 with HMAC with SHA-1”.

Advantages of PBKDF2:

  • Has been specified for a long time, seems unscathed for now.
  • Is already implemented in various framework (e.g. it is provided with .NET).
  • Highly configurable (although some implementations do not let you choose the hash function, e.g. the one in .NET is for SHA-1 only).
  • Received NIST blessings (modulo the difference between hashing and key derivation; see later on).
  • Configurable output length (again, see later on).

Drawbacks of PBKDF2:

  • CPU-intensive only, thus amenable to high optimization with GPU (the defender is a basic server which does generic things, i.e. a PC, but the attacker can spend his budget on more specialized hardware, which will give him an edge).
  • You still have to manage the parameters yourself (salt generation and storage, iteration count encoding…). There is a standard encoding for PBKDF2 parameters but it uses ASN.1 so most people will avoid it if they can (ASN.1 can be tricky to handle for the non-expert).

bcrypt

bcrypt was designed by reusing and expanding elements of a block cipher called Blowfish. The iteration count is a power of two, which is a tad less configurable than PBKDF2, but sufficiently so nevertheless. This is the core password hashing mechanism in the OpenBSD operating system.

Advantages of bcrypt:

  • Many available implementations in various languages (see the links at the end of the Wikipedia page).
  • More resilient to GPU; this is due to details of its internal design. The bcrypt authors made it so voluntarily: they reused Blowfish because Blowfish was based on an internal RAM table which is constantly accessed and modified throughout the processing. This makes life much harder for whoever wants to speed up bcrypt with a GPU (GPU are not good at making a lot of memory accesses in parallel). See here for some discussion.
  • Standard output encoding which includes the salt, the iteration count and the output as one simple to store character string of printable characters.

Drawbacks of bcrypt:

  • Output size is fixed: 192 bits.
  • While bcrypt is good at thwarting GPU, it can still be thoroughly optimized with FPGA: modern FPGA chips have a lot of small embedded RAM blocks which are very convenient for running many bcrypt implementations in parallel within one chip. It has been done.
  • Input password size is limited to 51 characters. In order to handle longer passwords, one has to combine bcrypt with a hash function (you hash the password and then use the hash value as the “password” for bcrypt). Combining cryptographic primitives is known to be dangerous (see above) so such games cannot be recommended on a general basis.

scrypt

scrypt is a much newer construction (designed in 2009) which builds over PBKDF2 and a stream cipher called Salsa20/8, but these are just tools around the core strength of scrypt, which is RAM. scrypt has been designed to inherently use a lot of RAM (it generates some pseudo-random bytes, then repeatedly read them in a pseudo-random sequence). “Lots of RAM” is something which is hard to make parallel. A basic PC is good at RAM access, and will not try to read dozens of unrelated RAM bytes simultaneously. An attacker with a GPU or a FPGA will want to do that, and will find it difficult.

Advantages of scrypt:

  • A PC, i.e. exactly what the defender will use when hashing passwords, is the most efficient platform (or close enough) for computing scrypt. The attacker no longer gets a boost by spending his dollars on GPU or FPGA.
  • One more way to tune the function: memory size.

Drawbacks of scrypt:

  • Still new (my own rule of thumb is to wait at least 5 years of general exposure, so no scrypt for production until 2014 – but, of course, it is best if other people try scrypt in production, because this gives extra exposure).
  • Not as many available, ready-to-use implementations for various languages.
  • Unclear whether the CPU / RAM mix is optimal. For each of the pseudo-random RAM accesses, scrypt still computes a hash function. A cache miss will be about 200 clock cycles, one SHA-256 invocation is close to 1000. There may be room for improvement here.
  • Yet another parameter to configure: memory size.

OpenPGP Iterated And Salted S2K

I cite this one because you will use it if you do password-based file encryption with GnuPG. That tool follows the OpenPGP format which defines its own password hashing functions, called “Simple S2K”, “Salted S2K” and “Iterated and Salted S2K“. Only the third one can be deemed “good” in the context of this answer. It is defined as the hash of a very long string (configurable, up to about 65 megabytes) consisting of the repetition of an 8-byte salt and the password.

As far as these things go, OpenPGP’s Iterated And Salted S2K is decent; it can be considered as similar to PBKDF2, with less configurability. You will very rarely encounter it outside of OpenPGP, as a stand-alone function.

Unix “crypt”

Recent Unix-like systems (e.g. Linux), for validating user passwords, use iterated and salted variants of the crypt() function based on good hash functions, with thousands of iterations. This is reasonably good. Some systems can also use bcrypt, which is better.

The old crypt() function, based on the DES block cipher, is not good enough:

  • It is slow in software but fast in hardware, and can be made fast in software too but only when computing several instances in parallel (technique known as SWAR or “bitslicing”). Thus, the attacker is at an advantage.
  • It is still quite fast, with only 25 iterations.
  • It has a 12-bit salt, which means that salt reuse will occur quite often.
  • It truncates passwords to 8 characters (characters beyond the eighth are ignored) and it also drops the upper bit of each character (so you are more or less stuck with ASCII).

But the more recent variants, which are active by default, will be fine.

Bad Password Hashing Functions

About everything else, in particular virtually every homemade method that people relentlessly invent.

For some reason, many developers insist on designing function themselves, and seem to assume that “secure cryptographic design” means “throw together every kind of cryptographic or non-cryptographic operation that can be thought of”. See this question for an example. The underlying principle seems to be that the sheer complexity of the resulting utterly tangled mess of instruction will befuddle attackers. In practice, though, the developer himself will be more confused by his own creation than the attacker.

Complexity is bad. Homemade is bad. New is bad. If you remember that, you’ll avoid 99% of problems related to password hashing, or cryptography, or even security in general.

Password hashing in Windows operating systems used to be mindbogglingly awful and now is just terrible (unsalted, non-iterated MD4).

Key Derivation

Up to now, we considered the question of hashing passwords. A close problem is about transforming a password into a symmetric key which can be used for encryption; this is called key derivation and is the first thing you do when you “encrypt a file with a password”.

It is possible to make contrived examples of password hashing functions which are secure for the purpose of storing a password validation token, but terrible when it comes to generating symmetric keys; and the converse is equally possible. But these examples are very “artificial”. For practical functions like the one described above:

  • The output of a password hashing function is acceptable as a symmetric key, after possible truncation to the required size.
  • A Key Derivation Function can serve as a password hashing function as long as the “derived key” is long enough to avoid “generic preimages” (the attacker is just lucky and finds a password which yields the same output). An output of more than 100 bits or so will be enough.

Indeed, PBKDF2 and scrypt are KDF, not password hashing function — and NIST “approves” of PBKDF2 as a KDF, not explicitly as a password hasher (but it is possible, with only a very minute amount of hypocrisy, to read NIST’s prose in such a way that it seems to say that PBKDF2 is good for hashing passwords).

Conversely, bcrypt is really a block cipher (the bulk of the password processing is the “key schedule”) which is then used in CTR mode to produce three blocks (i.e. 192 bits) of pseudo-random output, making it a kind of hash function. bcrypt can be turned into a KDF with a little surgery, by using the block cipher in CTR mode for more blocks. But, as usual, we cannot recommend such homemade transforms. Fortunately, 192 bits are already more than enough for most purposes (e.g. symmetric encryption with GCM or EAX only needs a 128-bit key).

Miscellaneous Topics

How many iterations ?

As much as possible ! This salted-and-slow hashing is an arms race between the attacker and the defender. You use many iterations to make the hashing of a password harder for everybody. To improve security, you should set that number as high as you can tolerate on your server, given the tasks that your server must otherwise fulfill. Higher is better.

Collisions and MD5

MD5 is broken: it is computationally easy to find a lot of pairs of distinct inputs which hash to the same value. These are called collisions.

However, collisions are not an issue for password hashing. Password hashing requires the hash function to be resistant to preimages, not to collisions. Collisions are about finding pairs of messages which give the same output without restriction, whereas in password hashing the attacker must find a message which yields a given output that the attacker does not get to choose. This is quite different. As far as we known, MD5 is still (almost) as strong as it has ever been with regards to preimages (there is a theoretical attack which is still very far in the ludicrously impossible to run in practice).

The real problem with MD5 as it is commonly used in password hashing is that it is very fast, and unsalted. However, PBKDF2 used with MD5 would be robust. You should still use SHA-1 or SHA-256 with PBKDF2, but for Public Relations. People get nervous when they hear “MD5”.

Salt Generation

The main and only point of the salt is to be as unique as possible. Whenever a salt value is reused anywhere, this has the potential to help the attacker.

For instance, if you use the user name as salt, then an attacker (or several colluding attackers) could find it worthwhile to build rainbow tables which attack the password hashing function when the salt is “admin” (or “root” or “joe”) because there will be several, possibly many sites around the world which will have a user named “admin”. Similarly, when a user changes his password, he usually keeps his name, leading to salt reuse. Old passwords are valuable targets, because users have the habit of reusing passwords in several places (that’s known to be a bad idea, and advertised as such, but they will do it nonetheless because it makes their life easier), and also because people tend to generate their passwords “in sequence”: if you learn that Bob’s old password is “SuperSecretPassword37”, then Bob’s current password is probable “SuperSecretPassword38” or “SuperSecretPassword39”.

The cheap way to obtain uniqueness is to use randomness. If you generate your salt as a sequence of random bytes from the cryptographically secure PRNG that your operating system offers (/dev/urandom, CryptGenRandom()…) then you will get salt values which will be “unique with a sufficiently high probability”. 16 bytes are enough so that you will never see a salt collision in your life, which is overkill but simple enough.

UUID are a standard way of generating “unique” values. Note that “version 4” UUID just use randomness (122 random bits), like explained above. A lot of programming frameworks offer simple to use functions to generate UUID on demand, and they can be used as salts.

Salt Secrecy

Salts are not meant to be secret; otherwise we would call them keys. You do not need to make salts public, but if you have to make them public (e.g. to support client-side hashing), then don’t worry too much about it. Salts are there for uniqueness. Strictly speaking, the salt is nothing more than the selection of a specific hash function within a big family of functions.

“Pepper”

Cryptographers can never let a metaphor alone; they must extend it with further analogies and bad puns. “Peppering” is about using a secret salt, i.e. a key. If you use a “pepper” in your password hashing function, then you are switching to a quite different kind of cryptographic algorithm; namely, you are computing a Message Authentication Code over the password. The MAC key is your “pepper”.

Peppering makes sense if you can have a secret key which the attacker will not be able to read. Remember that we use password hashing because we consider that an attacker could grab a copy of the server database, or possible of the whole disk of the server. A typical scenario would be a server with two disks in RAID 1. One disk fails (electronic board fries – this happens a lot). The sysadmin replaces the disk, the mirror is rebuilt, no data is lost due to the magic of RAID 1. Since the old disk is dysfunctional, the sysadmin cannot easily wipe its contents. He just discards the disk. The attacker searches through the garbage bags, retrieves the disk, replaces the board, and lo! He has a complete image of the whole server system, including database, configuration files, binaries, operating system… the full monty, as the British say. For peppering to be really applicable, you need to be in a special setup where there is something more than a PC with disks; you need a HSM. HSM are very expensive, both in hardware and in operational procedure. But with a HSM, you can just use a secret “pepper” and process passwords with a simple HMAC (e.g. with SHA-1 or SHA-256). This will be vastly more efficient than bcrypt/PBKDF2/scrypt and their cumbersome iterations. Also, usage of a HSM will look extremely professional when doing a WebTrust audit.

Client-side hashing

Since hashing is (deliberately) expensive, it could make sense, in a client-server situation, to harness the CPU of the connecting clients. After all, when 100 clients connect to a single server, the clients collectively have a lot more muscle than the server.

To perform client-side hashing, the communication protocol must be enhanced to support sending the salt back to the client. This implies an extra round-trip, when compared to the simple client-sends-password-to-server protocol. This may or may not be easy to add to your specific case.

Client-side hashing is difficult in a Web context because the client uses Javascript, which is quite anemic for CPU-intensive tasks.

In the context of SRP, password hashing necessarily occurs on the client side.

Conclusion

Use bcrypt. PBKDF2 is not bad either. If you use scrypt you will be a “slightly early adopter” with the risks that are implied by this expression; but it would be a good move for scientific progress (“crash dummy” is a very honourable profession).

Malicious Image files on Facebook spreading Locky Ransomware

 

Security researchers have discovered ransomwares being spread by forcibly exploiting vulnerabilities in  social networking sites including Facebook and LinkedIn. It is found that the malware is being spread through Scalable Vector Graphics (.SVG) files on Facebook Messenger. SVG is XML-based file. So it can embed content such as JavaScript. This malware manages to bypass Facebook’s file extension filter. The malware being distributed is the locky ransomware.

In the case of the Locky ransomware, all files on the affected computer are encrypted until a ransom is paid.

When the file is opened, users were prompted to install an extension. This extension downloads the Nemucod downloader which can spread the malware, which then encrypts the files.

Users should never download attachments from people they don’t know, or open those attachments with unusual file extension such as svg, js or hta. If the extension is downloaded, do not open them.

Video Demonstration of the Attack

All hats welcome