Oh wow, this could be bad! And I just recommended
PGP to my students. I wonder if it’s the plug-in and not the
actual encryption packages? Either way, I’m glad I taught my
students to build their own encryption system.
Stop Using
Common Email Encryption Tools Immediately, Researchers Warn
Throughout the many arguments over encrypted
communications, there has been at least one
constant: the venerable tools for strong email encryption are
trustworthy. That may no longer be true.
On Tuesday, well-credentialed cybersecurity
researchers will detail what they call critical vulnerabilities in
widely-used tools for applying PGP/GPG and S/MIME encryption.
According to Sebastian Schinzel, a professor at the Münster
University of Applied Sciences in Germany, the flaws could reveal the
“plaintext” that email encryption is supposed to cover up—in
both current and old emails.
The researchers are advising everyone to
temporarily stop using plugins for mail clients like Microsoft
Outlook and Apple
Mail that automatically encrypt and decrypt emails—at least until
someone figures out how to remedy the situation. Instead, experts
say, people should switch to tools like Signal, the encrypted
messaging app that’s bankrolled
by WhatsApp co-founder Brian Acton.
When contacted by Fortune, Schinzel
declined to divulge further details ahead of Tuesday’s
announcement, but he pointed to a blog
post from the world’s biggest digital rights
group, the Electronic Frontier Foundation (EFF,) for further advice.
The downside of trusting crooks to be honest.
Catalin Cimpanu reports:
Ransomware has infected the servers of the Riverside Fire and Police department for the second time in a month.
The first ransomware infection took place on April 23, last month and encrypted ten months worth of work data related to active investigations.
Officials said they didn’t pay the ransom and were able to recover some of the data from previous backups. Other data they recovered from public court records, but to this day, the Riverside Fire and Police department have not fully recovered from the first attack.
[From the article:
The
second infection took place last week, May 4, but only came to light
today when US Secret Service agents arrived in the Ohio town to help
with the investigation.
This
time around officials
appear to have learned their lesson and were actively
making backups on a daily basis. Officials said the second
ransomware infection only locked up data for the last eight hours of
work, and the department fully recovered after the second attack.
"Everything
was backed-up, but we lost about eight hours worth of information we
have to re-enter," City Manager Mark Carpenter told
local media.
"It was our police and fire records, so we just re-enter the
reports."
… This
is not the first ransomware infection that hit a police department
and has wiped data on investigations. Police in Cockrell Hill, Texas
suffered a similar incident in January 2017 when they lost
nearly eight years worth of evidence.
Police
and fire departments are regularly hit with ransomware, but usually,
they manage to recover either by restoring backups or by paying the
ransom. Past victims include the police departments in the Mad
River Township, Ohio;
Roxana,
Illinois;
Tewksbury,
Massachusetts;
Rockport,
Oregon;
Mount
Pleasant, South Carolina;
just to name a few.
A
new(ish) term that defines a category of Identity Theft.
Sizing
Up the Impact of Synthetic Identity Fraud
With
recent data breaches and the associated flood of PII onto the dark
web, synthetic identity fraud
is easier to commit than ever. Credit card losses due to this fraud
exceeded $800 million in the U.S. last year, says Julie Conroy, a
research director at Aite Group. Perhaps more shocking is just how
much of the fraud is going undetected, flying under the radar as
credit write-offs.
"One of the challenging aspects of this is
often it doesn't get recognized as fraud and gets written off as a
credit loss; so understanding the scope of the problem has been a
challenge," Conroy says in an interview with Information
Security Media Group about Aite's latest research. "A number of
institutions are starting to see fundamental shifts to things like
their credit delinquency curves that are only explainable by
synthetic identity fraud."
(Related)
Synthetic
Identity Theft
A type of fraud in which a criminal combines real
(usually stolen) and fake information to create a new identity, which
is used to open fraudulent accounts and make fraudulent purchases.
Synthetic identity
theft allows the criminal to steal money from any credit
card companies or lenders
who extend credit based on the fake identity.
Cambridge
again? Don’t they have Computer Security managers there?
Phee
Waterfield and Timothy Revell report:
Data from millions of Facebook users who used a popular personality app, including their answers to intimate questionnaires, was left exposed online for anyone to access, a New Scientist investigation has found.
Academics at the University of Cambridge distributed the data from the personality quiz app myPersonality to hundreds of researchers via a website with insufficient security provisions, which led to it being left vulnerable to access for four years. Gaining access illicitly was relatively easy.
The data was highly sensitive, revealing personal details of Facebook users, such as the results of psychological tests. It was meant to be stored and shared anonymously, however such poor precautions were taken that deanonymising would not be hard.
Read
more on New
Scientist
The flip side
of blocking Russian Facebook ads?
When
governments censor websites and block messaging apps like Telegram,
here's where to turn for proof
In Iran, use of the messaging app Telegram has
officially been banned.
For some 40 million Iranians, Telegram has been an
integral part of daily life, a place to talk with friends and family
beyond the reach of government censors. Which is why, after
anti-government protests broke out in the final days of 2017, the
government instructed the country's internet service providers to
implement temporary controls that
would make Telegram harder to use — before outright
banning its use this month.
Anecdotal reports are one thing. But to
understand how, exactly, Telegram was being blocked — and to what
extent in different parts of the country — researcher Mahsa
Alimardani turned to technical data gathered by a watchdog group
called the Open Observatory of
Network Interference, or OONI.
… All of the data collected by OONI's
measurement software — called probes — is stored in
a publicly accessible database, where anyone can go to understand
what's being blocked, filtered, or throttled in a particular country,
and how. That data can be used to track the evolution of information
controls over time or link censorship with political events like
elections and protests.
For my Computer Security and Software Architecture
students.
Risk
Management Framework for Information Systems and Organizations: A
System Life Cycle Approach for Security and Privacy
“This update
to NIST Special Publication 800-37 (Revision 2) responds to the
call by the Defense
Science Board, Executive
Order 13800, and OMB
Memorandum M-17-25 to develop the next-generation Risk Management
Framework (RMF) for information systems, organizations, and
individuals. There are seven major objectives for this update:
-
Provide closer linkage and communication between the risk management processes and activities at the C-suite or governance level of the organization and the individuals, processes, and activities at the system and operational level of the organization;
-
Institutionalize critical organization-wide risk management preparatory activities to facilitate a more effective, efficient, and cost-effective execution of the RMF;
-
Demonstrate how the Cybersecurity Framework can be aligned with the RMF and implemented using established NIST risk management processes;
-
Integrate privacy risk management concepts and principles into the RMF and support the use of the consolidated security and privacy control catalog in NIST Special Publication 800-53 Revision 5;
-
Promote the development of trustworthy secure software and systems by aligning life cycle-based systems engineering processes in NIST Special Publication 800-160 with the steps in the RMF;
-
Integrate supply chain risk management (SCRM) concepts into the RMF to protect against untrustworthy suppliers, insertion of counterfeits, tampering, unauthorized production, theft, insertion of malicious code, and poor manufacturing and development practices throughout the SDLC; and
-
Provide an alternative organization-generated control selection approach to complement the traditional baseline control selection approach…”
You need the latest tools to match competition.
Platform business models are booming—becoming
bigger and more powerful than ever. Just consider that a few tweets
from the president caused Amazon’s market capitalization to fall by
about $40 billion, or that Russian influencers were able to reach 126
million people through Facebook. At OpenMatters, we spend a lot of
time studying network
orchestration—business models where companies facilitate
relationships and interactions, rather than serving up all the
products, services, and pieces of content themselves. Think
Facebook, Uber, Pinterest, Alibaba, Airbnb, and the myriad “unicorns”
that are being showered in investor dollars. These companies are
groundbreaking, leveraging networks effects and near-zero
scaling cost to trounce competition or define new markets.
However, not all platform plays work—the business model alone
isn’t sufficient for success. There are lots of things that can
make a platform succeed or fail, of course, but an increasingly
central aspect of a successful platform strategy is machine learning.
… What happened is pretty clear: people got
tired of sorting through hundreds of unqualified applicants for every
job opening. The pile of resumes was too large, and the simple
algorithms attempting to serve up relevant content were insufficient
for the size and varied needs of the user base. Then, better
solutions emerged. Companies like LinkedIn and Glassdoor began
filling the gap—standing out by better curating professional
networks. Craigslist is another great example of an early platform
company that failed to innovate and curate, and is quickly
losing market share to added-value platforms like OfferUp or even
Facebook Marketplace.
… In addition to using machine learning to
parse and understand data generated by a network, platform companies
are now seeing the importance of AI for detecting and preventing
misuse. Fraudulent, criminal, and abusive behaviors are a problem
for many networks and companies are realizing that they can no longer
wash their hands of the actions of their users. Twitter has had to
take steps to curb
abuse, Yelp and LinkedIn are working on filtering out fake
content, and Facebook is likely at the beginning of a long journey to
prevent misuse following the Russian influencing scandal. These
platforms are simply too big and too complicated for manual or
human-led solutions to uncover and thwart misuse. Machine learning
and artificial intelligence are the only way to manage the content at
scale and as it evolves.
More than a Roomba, less than a Terminator?
Russia Just
Showed Off Its New Robot Tank — And Confirmed It Was On The Ground
In Syria
Russia has been on the forefront of building
unmanned ground vehicles and last week the
Russian Defense Ministry confirmed that their armed drone tank
Uran-9 was tested in Syria.
The Uran-9 is powerfully armed with anti-tank
missiles, an automatic cannon, and a machine gun. It can also be
reconfigured to carry different weapons like surface-to-air missiles.
Additionally, the unmanned vehicle is equipped with advanced optics
and targeting systems including a laser warning system and thermal
imaging.
… Since its Syrian intervention in 2015, the
resurgent Russian military has battle tested an arsenal of new
weapons including the Su-57 stealth fighter jet, the T-90 battle
tank, ship-launched cruise missiles and air defense systems.
… In the case of the Uran-9, it is remotely
controlled by an individual from a mobile vehicle that must remain
within 1.8 miles. The automatic turret is able to detect and acquire
targets, but the ultimate decision to fire rests with the controller.
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