By Oscar Prado | October 03, 2019
In today’s world technology evolves rapidly. New tools, approaches, and trends seem to come out on almost a daily basis. It’s our duty to keep pace with these changes, adapt to new technologies and apply all our knowledge, skills, and abilities to find and report all vulnerabilities as soon as possible.
In this article, we will discuss some of the main technology trends for 2019, the cybersecurity risks these trends may cause, and security prospects in upcoming years.
With the spread of
IoT (Internet of Things) technologies,
more devices are exposed every day to the Internet,
but they are not necessarily secure.
IoT devices provide additional entry points for attackers,
giving them a whole repertoire of mechanisms
to compromise confidential information.
According to Bank Info Security ,
attackers continue targeting the same
reported and disclosed 3 years ago.
IoT malware, such as Mirai,
keeps growing, escalating and mutating.
Your mobile, webcam, router or even your printer can be a target.
And these attacks are not particularly difficult to perform;
you can even find Youtube tutorials about them.
If you’re part of the industry,
you aren’t safe either,
SCADA systems, smart sensors, and drives
IoT devices that can be compromised
as a result of a
Mirai Botnet attack.
This may be discouraging,
even more so if we consider that in upcoming years,
the amount of
IoT devices will increase considerably.
We can, however, mitigate some risks now through system hardening,
and something as simple as changing the default credentials
as well as using secure passwords.
All of these can prevent an
Most companies are now migrating to the cloud.
The advantages of Infrastructure as Code (
IaC) are clear:
maintainability, scalability, and pricing, among others.
With cloud computing service providers like
Amazon Web Services,
Digital Ocean or
with large dedicated teams maintaining their servers,
our small infrastructure team seems obsolete in comparison.
It’s better to outsource this aspect to bigger companies
and stop worrying about physical infrastructure.
Well, this is not completely true.
We cannot disregard the security aspect;
the providers fulfilled their duty,
now we must fulfill ours.
According to Ben Morris,
Bishop Fox ,
speaking at Defcon Security Conference #27,
hundreds of thousands of
Amazon Elastic Block Storage (
have misconfigurations that led to sensitive data leakages:
passwords, authentication keys, and encryption keys, among others.
And what’s worse is in 2018,
70 million records were leaked
due to poorly configured
AWS S3 buckets .
The main cause of this kind of vulnerability was again the human factor.
A lack of knowledge
or negligence regarding infrastructure settings
can directly impact your company.
AWS configuration can be detected using automated tools.
Asserts, one of our products,
can detect these flaws, using the
AWS Cloudtrail module.
However, some of the cloud leakages
were also caused by hardware vulnerabilities ,
Meltdown  or
that exploit vendor chips' vulnerabilities
to gain access to shared memory pools on physical systems.
So, it is important to keep up to date with both software and hardware
to avoid these kinds of attacks.
Fluid Attacks, we have all our infrastructure as code.
as our cloud computing service provider,
to configure our infrastructure,
Gitlab as service
to regenerate our datacenter
on every new version of our products.
We implement infrastructure hardening using ephemeral secrets
in a serverless approach.
Fluid Attacks, we take security very seriously,
since it’s our value promise.
Machine Learning, Neural Networks,
and Artificial Intelligence have demonstrated
that they have several applications,
and cybersecurity is not an exception.
This topic has been widely addressed in several blog entries,
so instead, let’s discuss
Fluid Attacks' opinion
about the prospects for Machine Learning in the cybersecurity field
Fluid Attacks, we do not discourage
the use of automated tools in security tests;
However, a real security issue comes up
when only automated tools are used,
since these tools can report false positives.
For example, in the case of neural networks,
some inputs can fool the entire algorithm.
Automated tools also do not have the human malice
to correlate vulnerabilities and then create more complex attack vectors.
We see machine learning emerging technologies more as tools
rather than the holy grail of cybersecurity that will replace human hackers.
These tools can help our analysts to decide where to look first,
what portions of code may have vulnerabilities
and require further attention,
or which inputs may not have been properly sanitized.
In today’s world, businesses usually have an online alternative
for purchasing or selling products or services.
These online alternatives have to be handled with extreme care
since most cyberattacks aim to profit from these functionalities.
E-commerce attacks come in all shapes and sizes :
phishing, identity theft,
DDOS, credit card frauds, and more.
Most attacks are based on social engineering. These are attacks that try to trick the victim into performing actions (click a link or provide confidential information) that help the attacker gain control over the victim’s transactions.
According to Verizon, in its annual Data Breach Investigations Report , social engineering is the second most used tactic to extract confidential information. This is worrying because it doesn’t matter how secure an application is if users are fooled into providing access credentials. This, of course, applies to E-commerce as well.
One effective way to help reduce social engineering attacks is to train people via presentations and workshops on how to identify a phishing attack, along with basic security measures they can execute before providing personal information when purchasing online. A few of these are checking the URL and certificates, and being suspicious when the application asks for too much information, etc.
As technology evolves, cybersecurity should evolve as well.
But often what should happen differs from what does happen.
Cyberattacks become more complex
and solutions, patches, and fixes take too much time to develop and deploy.
On the bright side, with increasing cyberattacks,
cybersecurity is becoming more relevant.
Companies are investing more in security,
developing tools such as machine learning, neural networks, and
and considering security risk consequences
before exposing applications to the Internet.
As a result, more companies now believe what
Fluid Attacks has always known,
security should be applied
to the entire Software Development Life Cycle (