Tag: web

Facebook’s In-app Browser on iOS Tracks ‘Anything You Do on Any Website’

Researcher shows how Instagram and Facebook’s use of an in-app browser within both its iOS apps can track interactions with external websites.Researcher shows how Instagram and Facebook’s use of an in-app browser within both its iOS apps can track interactions with external websites.Read More

It Might Be Our Data, But It’s Not Our Breach

Image: Shutterstock.

A cybersecurity firm says it has intercepted a large, unique stolen data set containing the names, addresses, email addresses, phone numbers, Social Security Numbers and dates of birth on nearly 23 million Americans. The firm’s analysis of the data suggests it corresponds to current and former customers of AT&T. The telecommunications giant stopped short of saying the data wasn’t theirs, but it maintains the records do not appear to have come from its systems and may be tied to a previous data incident at another company.

Milwaukee-based cybersecurity consultancy Hold Security said it intercepted a 1.6 gigabyte compressed file on a popular dark web file-sharing site. The largest item in the archive is a 3.6 gigabyte file called “dbfull,” and it contains 28.5 million records, including 22.8 million unique email addresses and 23 million unique SSNs. There are no passwords in the database.

Hold Security founder Alex Holden said a number of patterns in the data suggest it relates to AT&T customers. For starters, email addresses ending in “att.net” accounted for 13.7 percent of all addresses in the database, with addresses from SBCGLobal.net and Bellsouth.net — both AT&T companies — making up another seven percent. In contrast, Gmail users made up more than 30 percent of the data set, with Yahoo addresses accounting for 24 percent. More than 10,000 entries in the database list “none@att.com” in the email field.

Hold Security found these email domains account for 87% of all domains in the data set. Nearly 21% belonged to AT&T customers.

Holden’s team also examined the number of email records that included an alias in the username portion of the email, and found 293 email addresses with plus addressing. Of those, 232 included an alias that indicated the customer had signed up at some AT&T property; 190 of the aliased email addresses were “+att@”; 42 were “+uverse@,” an oddly specific reference to a DirecTV/AT&T entity that included broadband Internet. In September 2016, AT&T rebranded U-verse as AT&T Internet.

According to its website, AT&T Internet is offered in 21 states, including Alabama, Arkansas, California, Florida, Georgia, Indiana, Kansas, Kentucky, Louisiana, Michigan, Missouri, Nevada, North Carolina, Ohio, Oklahoma, Tennessee, Texas and Wisconsin. Nearly all of the records in the database that contain a state designation corresponded to those 21 states; all other states made up just 1.64 percent of the records, Hold Security found.

Image: Hold Security.

The vast majority of records in this database belong to consumers, but almost 13,000 of the entries are for corporate entities. Holden said 387 of those corporate names started with “ATT,” with various entries like “ATT PVT XLOW” appearing 81 times. And most of the addresses for these entities are AT&T corporate offices.

How old is this data? One clue may be in the dates of birth exposed in this database. There are very few records in this file with dates of birth after 2000.

“Based on these statistics, we see that the last significant number of subscribers born in March of 2000,” Holden told KrebsOnSecurity, noting that AT&T requires new account holders to be 18 years of age or older. “Therefore, it makes sense that the dataset was likely created close to March of 2018.”

There was also this anomaly: Holden said one of his analysts is an AT&T customer with a 13-letter last name, and that her AT&T bill has always had the same unique misspelling of her surname (they added yet another letter). He said the analyst’s name is identically misspelled in this database.

KrebsOnSecurity shared the large data set with AT&T, as well as Hold Security’s analysis of it. AT&T ultimately declined to say whether all of the people in the database are or were at some point AT&T customers. The company said the data appears to be several years old, and that “it’s not immediately possible to determine the percentage that may be customers.”

“This information does not appear to have come from our systems,” AT&T said in a written statement. “It may be tied to a previous data incident at another company. It is unfortunate that data can continue to surface over several years on the dark web. However, customers often receive notices after such incidents, and advice for ID theft is consistent and can be found online.”

The company declined to elaborate on what they meant by “a previous data incident at another company.”

But it seems likely that this database is related to one that went up for sale on a hacker forum on August 19, 2021. That auction ran with the title “AT&T Database +70M (SSN/DOB),” and was offered by ShinyHunters, a well-known threat actor with a long history of compromising websites and developer repositories to steal credentials or API keys.

Image: BleepingComputer

ShinyHunters established the starting price for the auction at $200,000, but set the “flash” or “buy it now” price at $1 million. The auction also included a small sampling of the stolen information, but that sample is no longer available. The hacker forum where the ShinyHunters sales thread existed was seized by the FBI in April, and its alleged administrator arrested.

But cached copies of the auction, as recorded by cyber intelligence firm Intel 471, show ShinyHunters received bids of up to $230,000 for the entire database before they suspended the sale.

“This thread has been deleted several times,” ShinyHunters wrote in their auction discussion on Sept. 6, 2021. “Therefore, the auction is suspended. AT&T will be available on WHM as soon as they accept new vendors.”

The WHM initialism was a reference to the White House Market, a dark web marketplace that shut down in October 2021.

“In many cases, when a database is not sold, ShinyHunters will release it for free on hacker forums,” wrote BleepingComputer’s Lawrence Abrams, who broke the news of the auction last year and confronted AT&T about the hackers’ claims.

AT&T gave Abrams a similar statement, saying the data didn’t come from their systems.

“When asked whether the data may have come from a third-party partner, AT&T chose not to speculate,” Abrams wrote. “‘Given this information did not come from us, we can’t speculate on where it came from or whether it is valid,’” AT&T told BleepingComputer.

Asked to respond to AT&T’s denial, ShinyHunters told BleepingComputer at the time, “I don’t care if they don’t admit. I’m just selling.”

On June 1, 2022, a 21-year-old Frenchman was arrested in Morocco for allegedly being a member of ShinyHunters. Databreaches.net reports the defendant was arrested on an Interpol “Red Notice” at the request of a U.S. federal prosecutor from Washington state.

Databreaches.net suggests the warrant could be tied to a ShinyHunters theft in May 2020, when the group announced they had exfiltrated 500 GB of Microsoft’s source code from Microsoft’s private GitHub repositories.

“Researchers assess that Shiny Hunters gained access to roughly 1,200 private repositories around March 28, 2020, which have since been secured,” reads a May 2020 alert posted by the New Jersey Cybersecurity & Communications Integration Cell, a component within the New Jersey Office of Homeland Security and Preparedness.

“Though the breach was largely dismissed as insignificant, some images of the directory listing appear to contain source code for Azure, Office, and some Windows runtimes, and concerns have been raised regarding access to private API keys or passwords that may have been mistakenly included in some private repositories,” the alert continues. “Additionally, Shiny Hunters is flooding dark web marketplaces with breached databases.”

Last month, T-Mobile agreed to pay $350 million to settle a consolidated class action lawsuit over a breach in 2021 that affected 40 million current and former customers. The breach came to light on Aug. 16, 2021, when someone starting selling tens of millions of SSN/DOB records from T-Mobile on the same hacker forum where the ShinyHunters would post their auction for the claimed AT&T database just three days later.

T-Mobile has not disclosed many details about the “how” of last year’s breach, but it said the intruder(s) “leveraged their knowledge of technical systems, along with specialized tools and capabilities, to gain access to our testing environments and then used brute force attacks and other methods to make their way into other IT servers that included customer data.”

A sales thread tied to the stolen T-Mobile customer data.

A cybersecurity firm says it has intercepted a large, unique stolen data set containing the names, addresses, email addresses, phone numbers, Social Security Numbers and dates of birth on nearly 23 million Americans. The firm’s analysis of the data suggests it corresponds to current and former customers of AT&T. The telecommunications giant stopped short of saying the data wasn’t theirs, but it maintains the records do not appear to have come from its systems and may be tied to a previous data incident at another company.Read More

cisco ransomware jtZF1K

Cisco Confirms It’s Been Hacked by Yanluowang Ransomware Gang

Networking equipment major Cisco on Wednesday confirmed it was the victim of a cyberattack on May 24, 2022 after the attackers got hold of an employee’s personal Google account that contained passwords synced from their web browser.
“Initial access to the Cisco VPN was achieved via the successful compromise of a Cisco employee’s personal Google account,” Cisco Talos said in a detailed write-up.Networking equipment major Cisco on Wednesday confirmed it was the victim of a cyberattack on May 24, 2022 after the attackers got hold of an employee’s personal Google account that contained passwords synced from their web browser.
“Initial access to the Cisco VPN was achieved via the successful compromise of a Cisco employee’s personal Google account,” Cisco Talos said in a detailed write-up.Read More

OpenTIP, command line edition

For more than a year, we have been providing free intelligence services via the OpenTIP portal. Using the web interface, anyone can upload and scan files with our antivirus engine, get a basic sandbox report, look up various network indicators (IP addresses, hosts, URLs). Later on, we presented an easy-to-use HTTPS-based programming interface, so that you could use the service in your own scripts and integrate it in existing workflow.

OpenTIP web interface – upload, look up, get results!

Of course, it is much easier to use the API when there is a set of working examples. It is also more convenient to integrate with existing tools and scripts when you have a command line utility that interacts with the service. We decided have both in one package, by releasing Python-based command line tools for the service that also implement a client class that you can reuse in your own tools.

A few words about privacy

The OpenTIP service has its own Terms of Use, End-User Agreement and a Privacy Policy; and the command line tools can only be accessed with an API token, that in turn can be only obtained after agreeing to all the terms. Please read them carefully. By default, the “opentip” scanner may upload the files being checked if their hashes are not yet known to the service, so please ensure that you are familiar with the policies. And, of course, the sample upload can be turned off.

Setting things up

The command line tools need the “apikey”, that is, a usual web API access token. You can generate it at this page (you may be required to register or log in into the web version of the service). The key can then be permanently set up as an environment variable “OPENTIP_APIKEY” or provided as a command line option “–apikey VALUE_OF_THE_KEY”. By default, the API key has certain rate limitations that may be changed in future, so please contact us if your scripts hit the rate limits.

The tools and the Python 3 client class can be all installed from pip:

pip3 install opentip

The code is also published on Github, so you can easily inspect and package it yourself. At the time of writing, the package has no external dependencies and should run on any modern Python 3 distribution.

Once installed, Python will also generate two executables (scripts, or binary wrappers, depending on the platform), named “opentip” and “check_iocs”.

The OpenTIP Scanner

The scanner is named “opentip” (or “opentip.exe”), as is the primary tool for quickly checking files and directories. The standard usage banner is pretty simple and self-descriptive:

usage: opentip [-h] [–no-upload] [–exclude EXCLUDE] [–log LOG] [–apikey APIKEY] [–quiet] path [path …]

Check files and directories with OpenTIP.kaspersky.com, optionally upload and scan unknown files

positional arguments:
path File or directory location to scan

optional arguments:
-h, –help show this help message and exit
–no-upload DO NOT upload unknown files to scan with the Sandbox, default behaviour is to upload
–exclude EXCLUDE Do not scan or upload the files matching the pattern
–log LOG Write results to the log file
–apikey APIKEY OpenTIP API key, received from https://opentip.kaspersky.com/token
–quiet Do not log clean files

The easiest and most basic mode of operation is to provide the location of the files or directories to scan. Directories are processed recursively, and unknown files are uploaded for checking by default (subject to the privacy policy, use “–no-upload” to change default behavior). The results are printed on stdout, and can also be redirected to a log file. The “–exclude” option allows you to disable the checks for any path locations, and with the “–quiet” option the script will print out only the positive detections.

$ opentip .
2022-08-01 16:23:22,638 ./package/main.py: Malware: Trojan.Python.Lofy.a
2022-08-01 16:23:22,766 ./package/package.json: NotCategorized
2022-08-01 16:23:22,965 ./package/index.js: NoThreats

Typical output of the scanner

Since the package has no external dependencies, it can be used to quickly deploy the scanner and check a fleet of remote machines, and the OPENTIP_APIKEY environment variable makes it easier to use the scanner in containers.

The IOC checker script

The second tool, named “check_iocs”, has a different purpose: you can use it to quickly query the OpenTIP service for file hashes, domains, IPs and URLs.

usage: check_iocs [-h] [–apikey APIKEY] [–out OUT] type value

Check IOCS (file hashes, IP addresses, domain names, URLs using the service OpenTIP.kaspersky.com

positional arguments:
type hash, ip, domain, url
value Value of the IOC (hash, ip, domain, url, filename with the iocs)

optional arguments:
-h, –help show this help message and exit
–apikey APIKEY OpenTIP API key, received from https://opentip.kaspersky.com/token
–out OUT, -o OUT Write output as JSON to this filename

The script requires two arguments: the type of the input data (“hash”, “ip”, “domain”, “url”, “filename”) and either the actual value of the data to check, or the path of the filename that contains the list of values, one per line.

$check_iocs hash list_of_md5.txt
[IOC]: d41d8cd98f00b204e9800998ecf8427e : Unknown
[IOC]: 46c5070ed139ca8121c07eda20587e3f : {‘Zone’: ‘Grey’, ‘FileGeneralInfo’: {‘FileStatus’: ‘NotCategorized’, ‘Sha1′: ’24F7BAF656DCAC1FF43E4479AD8A5F4DF8052900’, ‘Md5′: ’46C5070ED139CA8121C07EDA20587E3F’, ‘Sha256′: ’04FC2B072775EA05AB6C9E117EFBFD1C56D2F1B45D1AC175001A186452269F3C’, ‘FirstSeen’: ‘1970-01-01T00:00:00Z’, ‘LastSeen’: ‘1970-01-01T00:00:00Z’, ‘Size’: 464, ‘Type’: ‘text’}, ‘DynamicAnalysisResults’: {‘Detections’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}], ‘SuspiciousActivities’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}, {‘Zone’: ‘Grey’}], ‘NetworkActivities’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}, {‘Zone’: ‘Green’}, {‘Zone’: ‘Grey’}]}}
[IOC]: 0067bc5d4d92fe9445e41f347944196e : {‘Zone’: ‘Red’, ‘FileGeneralInfo’: {‘FileStatus’: ‘Malware’, ‘Sha1’: ‘F666104C83CB18F2ED345A11C34EE9A32CD2ABC1’, ‘Md5’: ‘0067BC5D4D92FE9445E41F347944196E’, ‘Sha256’: ‘8B615582D92D42FEEFCEEBA03E65D16773F2B227ED1CD17C82462641A9D249D9’, ‘FirstSeen’: ‘2022-07-27T11:48:00Z’, ‘LastSeen’: ‘2022-07-30T12:44:00Z’, ‘Size’: 10466, ‘Type’: ‘Txt’, ‘HitsCount’: 10}, ‘DetectionsInfo’: [{‘LastDetectDate’: ‘2022-07-30T12:50:35.887Z’, ‘Zone’: ‘Red’, ‘DetectionName’: ‘Trojan.Python.Lofy.a’}], ‘DynamicAnalysisResults’: {‘Detections’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}], ‘SuspiciousActivities’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}, {‘Zone’: ‘Grey’}], ‘NetworkActivities’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}, {‘Zone’: ‘Green’}, {‘Zone’: ‘Grey’}]}}
[IOC]: e1dc5ff6a1febdd4db11901fc295364f : {‘Zone’: ‘Green’, ‘FileGeneralInfo’: {‘FileStatus’: ‘NoThreats’, ‘Sha1’: ‘49217E09D0C33FF3C958AFBDCB60F977E10104E0’, ‘Md5’: ‘E1DC5FF6A1FEBDD4DB11901FC295364F’, ‘Sha256’: ‘EAB0020A475BB1CF70CA5C9569DEFE5F1A7160A9D334144DA47924418EE2C9E7’, ‘FirstSeen’: ‘2022-07-30T10:03:00Z’, ‘LastSeen’: ‘2022-07-30T10:20:00Z’, ‘Size’: 34768, ‘Type’: ‘Js’, ‘HitsCount’: 10}, ‘DynamicAnalysisResults’: {‘Detections’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}], ‘SuspiciousActivities’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}, {‘Zone’: ‘Grey’}], ‘NetworkActivities’: [{‘Zone’: ‘Red’}, {‘Zone’: ‘Yellow’}, {‘Zone’: ‘Green’}, {‘Zone’: ‘Grey’}]}}

Typical output of the check_iocs tool

The output is much more comprehensive than the one provided by the scanner and is JSON-encoded, so that it can be parsed automatically.

The Python API class

Both command line tools are actually using a single Python class to access the OpenTIP service, and you can use the source code of the tools as a reference for your own scripts.

The OpenTIP client can be easily instantiated with a few lines:

from opentip.client import OpenTIP
client = OpenTIP(APIKEY)

To query the OpenTIP for a known indicator, use a single call:

client.get_verdict_by_ioc(ioc_type, ioc)

For example:

>>> client.get_verdict_by_ioc(‘hash’, ‘0067bc5d4d92fe9445e41f347944196e’)

To scan a file (with upload turned on by default), returning a tuple of (filename, results), call:



>>> client.scan_file(‘package/main.py’)
(‘package/main.py’, ‘{“Zone”:”Red”,”FileGeneralInfo”:{“FileStatus”:”Malware”,”Sha1″:”F666104C83CB18F2ED345A11C34EE9A32CD2ABC1″,”Md5″:”0067BC5D4D92FE9445E41F347944196E”,”Sha256″:”8B615582D92D42FEEFCEEBA03E65D16773F2B227ED1CD17C82462641A9D249D9″,”FirstSeen”:”2022-07-27T11:48:00Z”,”LastSeen”:”2022-07-30T12:44:00Z”,”Size”:10466,”Type”:”Txt”,”HitsCount”:10},”DetectionsInfo”:[{“LastDetectDate”:”2022-07-30T12:50:35.887Z”,”Zone”:”Red”,”DetectionName”:”Trojan.Python.Lofy.a”}],”DynamicAnalysisResults”:{“Detections”:[{“Zone”:”Red”},{“Zone”:”Yellow”}],”SuspiciousActivities”:[{“Zone”:”Red”},{“Zone”:”Yellow”},{“Zone”:”Grey”}],”NetworkActivities”:[{“Zone”:”Red”},{“Zone”:”Yellow”},{“Zone”:”Green”},{“Zone”:”Grey”}]}}’)

To disable file upload for unknown files, instantiate the OpenTIP with no_upload=True.

>>> client = OpenTIP(OPENTIP_APIKEY, no_upload=True)
>>> client.no_upload

Any ideas are welcome

This is just the beginning, and we welcome any kind of input, pull requests and feature requests to make the service more convenient. If you have any issues or questions regarding the scripts, please contact us by creating a Github issue or using the OpenTIP contact form.

We released Python-based command line tools for our OpenTIP service that also implement a client class that you can reuse in your own tools.Read More

Education hammered by exploits and backdoors in 2021 and 2022

In May of 2021, education underwent a siege of exploit attempts using the vulnerability CVE-2021-21551, which exploits a Dell system driver bug and helps attackers to gain access to a network. Considering that many schools across the United States use Dell hardware, it’s understandable to see such a large amount of this exploit. 

In fact, both Rockland Schools in Massachusetts and Visalia USD in California were hit with ransomware attacks during this period. The states that detected this threat the most were Minnesota and Michigan, with Detroit being the biggest target in the US. 

In September of 2021, there was a spike of the malicious setting, RiskwareTool.IFEOHijack, with detections having increased from July 2021 onward. This threat is flagged when malware modifies a registry setting that changes the default Windows debugger to a malware executable. It is a red flag that needs to be investigated immediately. Unfortunately, it doesn’t pinpoint which malware made the modification, but the increased presence of this threat, especially in Oklahoma and Washington State, calls for deeper threat hunting on the victims’ networks. During the same period, a spike in exploit detections was observed and Howard University was breached.

The Trojan TechSupportScam covers an array of applications all designed to fool users into calling a “tech support” number to solve a problem created by the application, such as a blue screen, error message, activation alert, etc. These tools started spiking in January of 2022.  Educational institutions in New Jersey have had to deal with this threat more than any other state, however the public school district of Albuquerque, NM suffered a breach during the same month that could have been influenced by this spike in scams. Students and staff likely encountered these threats when installing risky software and/or visiting shady sites.

Finally, Pennsylvania schools have been dealing with an active campaign of backdoors, specifically QBot, since March of 2022, which will likely result in greater infections during the rest of 2022.

Beyond spikes in detections, the education sector has dealt with an onslaught of attacks ranging from spyware and denial of service tools to ransomware.  Throughout the year, almost every month has a report of an educational institution under attack. The first half of 2021 saw attacks against schools in Florida, New York, Oregon, Massachusetts, and California, while the second half saw attacks against Texas, Washington D.C., Wisconsin, and Illinois. The biggest attack of 2022, so far, would be the breach of Austin Peay State University in April, though time will tell if that remains true.

The education industry has the largest userbase out of all industries, considering the constant rotation of students and faculty. Therefore, the greatest threat to these organizations are the users themselves, who may download their own applications, visit dangerous websites, and even make system modifications to get around monitoring tools.

Recommendations for education

Our recommendation for this sector includes keeping an eye out for all new exploits that might affect your organization, especially commonly used systems. In a lot of cases, organizations may have a difficult time updating quickly, because of operational needs, but in the case of schools, a single vulnerability might be duplicated across 99% of its endpoints, which turns each of those systems into backdoors for the bad guys. So, making vulnerability patching one of the highest priorities will reduce attacks and decrease malicious file installation.

Next, systems that have been infected may leave behind artifacts of its operations, for example the IFEOHijack registry setting. Additionally, threats that may be installed on day one, might not activate until a user does something specific, or a certain date comes around, allowing the threat to hide in the meantime. To combat this threat, consider creating a secure, default system image that can be easily duplicated to endpoints, returning them to a default state. While this is likely already done by many schools every year, consider increasing the frequency to every quarter, maybe even every month, and have students save their files on cloud-based storage solutions.

By utilizing a default image, an organization can erase hidden malware, reset modified settings, and provide confidence in quickly isolating or wiping out an infected system. For the education industry, it’s not so much about what threats are actively targeting schools, but rather what threats have been left behind, that open doors for other, future attacks.

Summer of exploitation leads to healthcare under fire

May 2021 was a tough month for the Healthcare and Medical sector–the most notable threat trend at the time was the heavy use of a new popular exploit against Dell systems, leading to immense effort by attackers to utilize the exploit before it became less effective due to patching.  

During this period, hospitals in central Florida were hit with malicious attacks that disrupted their operations and forced them to conduct business via pen and paper. In addition, a hospital system in Southern California was forced to modify how it did business due to a cyberattack. The San Diego-based health system quickly moved its information technology program offline, to reduce the damage done by the attack. However it also put a roadblock in the way of legitimate employees and customers trying access their medical information online.

Figure 1. United States Healthcare and Medical Threat Family Detections by Month

After the spike in May, CVE 2021-21551 detections dropped to about a quarter of the original numbers, and remained there throughout the year, except for another spike in February 2022. It seems the primary target for these attacks were healthcare and medical organizations in Pensacola, FL, but detections for New York, Wisconsin and New Jersey weren’t far behind.

Heavy detections of TrickBot were observed, especially against organizations in York, Pennsylvania during the first three months of 2021. But detections of this threat all over the United States quickly dropped beginning in April 2021 and steadily declined throughout the time period. TrickBot isn’t a stranger to healthcare organizations and has historically targeted them for the sake of launching ransomware or causing operational disruption.

This threat is even a concern to the US Government, which released an alert, through the CISA portal, back in October of 2020, about the danger of the TrickBot organization specifically targeting Healthcare organizations.

Figure 2. United States Healthcare & Medical Family Threat Detections Pie Chart

In August and September, we observed significant spikes of AI behavioral-based detections, which lines up with a series of newsworthy healthcare breaches during the same period. 

For example, a healthcare group in central Indiana was the victim of an attack that lead to a ransomware infection and the loss of information from patients and employees, then released on the dark web. The attack itself occurred in early August and forced organizations to turn away ambulances for several days, an action which led to the death of a person in Germany.

Another attack in early August, this time against a healthcare management firm in Dallas, Texas, resulted in the theft of valuable information, including patient information, health insurance and financial data. 

Securing healthcare and medical organizations

Our recommendations for securing healthcare and medical organizations start with acknowledging that securing these organizations from every possible threat is not possible. Therefore, when considering how to defend against a ransomware attack, be sure to account for getting operations back online after an attack. This includes having plans for operating the business without the use of computers, establishing secure backups of sensitive data off-site and off-line, while still following HIPPA protocol.

Beyond that, this industry has dealt with lots of heavy attacks originating from both attempts to exploit vulnerabilities, as well as spear phishing. Quickly patching vulnerabilities is a high priority, however given that quick patching isn’t always an option, times like these require risk reduction, such as removing non-patchable endpoints from direct Internet access, creating additional layers of authentication to access high value systems, and a thorough review of user accounts and permissions, to tighten up who has access to what.

Finally, many of these organizations utilize mobile stations for inputting or reviewing data. These systems should not be able to do things like using USB drives. They should have screen protectors to prevent unintended information disclosure, and these systems should be completely wiped with a new image on a regular basis, to ensure removal of any hidden rootkit-level threats. 

New HTTP Request Smuggling Attacks Target Web Browsers

Threat actors can abuse weaknesses in HTTP request handling to launch damaging browser-based attacks on website users, researcher says.Threat actors can abuse weaknesses in HTTP request handling to launch damaging browser-based attacks on website users, researcher says.Read More