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Marrying the Firewall with the Threat Intelligence You Need

by skathuria ‎10-08-2014 02:27 PM - edited ‎10-08-2014 03:45 PM

threatintelligence.pngTo avoid becoming the next victim in the long line of data breach impacted organizations, many have started using a diverse and wide array of threat intelligence sources such as honeypots, social media monitoring, malware reverse engineering approaches, or others, as described by Anton Chuvakin in this blog.


A Hale and Hearty Network

by skathuria on ‎07-15-2014 11:48 AM


As I was reading this article describing examples of certain healthcare practitioners using data mining and analytics of patients’ lifestyles (e.g. foods they eat, activity levels, where they live, etc.) to help predict their risk factor for ailments, I started to draw a parallel to the state of the network. I was thinking about how security analytics of a network may help predict the onset of a data breach. The common goal in both cases, human and network, is to maintain a certain level of health – call it an “equilibrium” state, one that doesn’t require immediate intervention or repair.


Inspired by the table shared in the article describing what certain collected data about a patient could indicate about his/her health habits, I came up with a table containing types of network state related which could be indicators for a potential data exploit/breach.


State of Network


Weak password for an online account

This could allow a hacker to uncover the password (by using automated tools), gain access to user data (name, address, phone #, bank account/credit card data) and perform unauthorized transaction (e.g., purchase of product/service or withdrawal of money from bank account) on the user’s behalf.

Multiple unsuccessful attempts to search for usernames and passwords via Web browser exploitation techniques

This could result in a data breach.

Improper isolation of HR records, financial, medical, credit/debit card, or other PII data within Enterprise data center/private cloud network

This could inadvertently allow an insider (e.g. employee) access to the network for obtaining and selling data on black market for profit.

Excessive communication requests to a Web server or other resource, slowing it down considerably or rendering it unavailable

This could indicate someone is trying to gain access to the server for malicious intent.

No application layer protection at Enterprise edge

This could allow a hacker to launch an application-layer attack and access data for further exploitation.


Enterprise and service providers would benefit greatly from self-monitoring and constantly improving the health of networks, to minimize the possibility of a data breach.


One of the ways to do this is via technology, including application-aware, next generation firewalls, and strong SIEM solutions and network security management solutions (for firewall management), which provide visibility, analyze network security posture, and alert administrators about unusual network activity.


In addition, humans themselves should be held accountable for security. For one, it is imperative that the IT security team is proactively monitoring the network security posture, carefully balancing access to certain network resources, applications and data with control over the same. In addition, trust plays a big role in maintaining security and privacy, so it is ultimately the responsibility of individuals (business owners and employees) to not exploit data for personal gain.




Trusted security “informant” Brian Krebs just shared that the United States Postal Inspection Service is investigating reports that fraudsters are installing skimming devices on automated stamp vending machines at post office locations across the United States. Alarming, right? We’ve heard umpteen times about various retail brick and mortar stores falling victim to payment card skimmers, but here’s a first.


Moreover, according to the Verizon 2014 Data Breach Investigations Report, payment card skimming, is one of just nine total patterns of threats which are tied to 92% of the 100, 000 security incidents analyzed over the last 10 years. And, according to the same study, this type of criminal activity has been primarily targeted at the Finance and Retail industries to date. Looks like perpetrators are looking for a wider range of targets.


What is further disturbing is that now it has become somewhat easier for would-be criminals to more surreptitiously steal data. For one, they can purchase skimming devices that are Bluetooth enabled, which allows them to download the track and PIN data easily and remotely, from the safety of a parking lot! In addition, they can get skimming devices with built-in SIM cards, allowing for remote configuration, remote uploading of data, and tampering alerts that, if triggered, can cache the data and send it out immediately to the thieves, making it difficult for the victims to discover that there has been a data exfiltration.


Given the recent multiplicity of payment card skimming occurrences targeted at retail and post office locations, I have become quite wary of shopping using my credit and debit cards. Are you, too? The thing is, it’s convenient to pay by card vs. cash. 


Still, prevention is better than cure. If you aren’t already, take note of and follow Verizon’s suggestions. I certainly plan to:

  1. Protect the card PIN by covering it with a hand to block any possible miniscule cameras that may be recording as you enter it.
  2. Be mindful of surroundings – if you see multiple payment card devices installed, just check if they all look “the same” – should the device you are about to enter your card into look different from the others, don’t use it.
  3. Inform the merchant and/or bank if something seems out of place (e.g., the payment card device appears to have been tampered with, or someone seems to be attaching a foreign object to the device, etc.) so they can investigate the matter.

Safe shopping everyone!



As many would have rightly guessed, Target has been sued due to the significant data breach affecting its customers in 2013. According to this Reuters article, “Trustmark National Bank and Green Bank NA accused the defendants [,Target Corp and Trustwave Holdings Inc, which provides credit card security services,] of failing to properly secure customer data, enabling the theft of about 40 million payment card records plus 70 million other records.”


This reminds me of the prominent TJX (operator of TJ Maxx stores) data breach eight years ago that affected ~94M records, making it the largest single data breach to date. You can learn more about it on the Hacks of Ages timeline that Erin O’Malley so eloquently described recently. Juniper will add the Target breach to it.


According to the Ponemon Institute 2013 Cost of Data Breach Study: Global Analysis report, German and U.S. companies had the most costly data breaches ($199 and $188 per record, respectively). For U.S. retailer TJX, the financial losses were significant. The company agreed to pay $9.75 million to 41 states. Of this, per the settlement, $5.5 million was to be dedicated to data protection and consumer protection efforts by the states, and $1.75 million was to aid in reimbursement of the costs and fees of the investigation. Further, $2.5 million of the settlement was to be used to fund a Data Security Trust Fund to be used by State Attorneys General to advance enforcement efforts and policy development in the field of data security and protecting consumers’ personal information.


Let’s see how Target financially fares with regards to the settlement. In the meanwhile, I hope that both these and other enterprises will take effective, preventative measures to detect and stop such attacks early. If they don’t protect their customers’ data, certainly, sooner or later, they will have to pay the price. And, as my esteemed colleague, John Pennington, warned loudly and clearly in his blog, which summarizes the findings of a compelling study of the cybercriminal world, “Take action or be hacked!”


Target’s Data Breach Saga Continues . . .

by skathuria ‎03-14-2014 01:25 PM - edited ‎03-14-2014 01:34 PM


As a regular shopper at Target, I’ve been closely following the data breach ordeal. This week, I learned that the company did, in fact, have security intelligence in place, but the company’s Security Operations Center (SOC) didn’t react in time to prevent the damage. Astonishing!


It’s my hope that the following questions will eventually be answered, too . . .



If you’re an IT professional like me who likes to stay in touch with and expand your network, you’re probably familiar with LinkedIn (LNKD), operator of the world’s largest Internet-based professional network with 161 million members spanning over 200 countries and territories. In early June, the company learned that the encrypted passwords of over 6.4 million subscribers had been compromised and posted online.


In response to this incident, LinkedIn Director, Vicente Silveira, in a blog, said, “To the best of our knowledge, no email logins associated with the passwords have been published, nor have we received any verified reports of unauthorized access to any member’s account as a result of this event.” The company disabled passwords of those members believed to be at risk and sent them a message explaining how to reset their passwords. LinkedIn also stated that since the incident, it had enhanced its security measures (beyond SHA-1) by applying an additional layer of data protection know as “salting” to better secure members’ information.


Here’s how salting works. Before generating the hash (note: hash function is the transformation of a string of characters into a usually shorter fixed-length value or key that represents the original string) for each user password, you would create a random string of characters of a predetermined length and prepend this string to each plain text password. As long as the string (aka. a "salt") is of sufficient length and sufficiently random, the resulting hash will almost certainly be different each time the hash function is executed. By randomizing the hashes, lookup tables, reverse lookup tables, and rainbow tables become ineffective. Because an attacker won't know in advance what the salt will be, he or she can’t pre-compute a lookup table or rainbow table to crack passwords. If each user's password is hashed with a different salt, the reverse lookup table attack won't work either. Furthermore, in case an attacker tries to use brute force cracking in order to obtain passwords, Mykonos Web Security may be used to help prevent that.


On the other hand, if a legitimate user is logging into the Web site, because the user’s password associated salt is stored in the user database along with the hashed password, the authentication server will take the user supplied password and apply the user’s salt to obtain the hashed password. If there is a match, the user will successfully be authenticated.


Certain LinkedIn users were so dismayed by the data breach incident that they filed a class action lawsuit against LinkedIn seeking over $5 million in damages because the company allegedly didn’t follow its privacy policy and lacked sufficient security controls, in this case, salting, to protect its user database. Let’s hope this incident will be instructive for LinkedIn and other online businesses regarding the importance of implementing advanced Web application and data security controls to prevent a data breach, and avoid potential financial losses and the loss of customers resulting from such breaches.


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