Fintechs and Security – Part 4

  • Prologue – covers the overall challenge at a high level
  • Part One – Recruiting and Interviews
  • Part Two – Threat and Vulnerability Management – Application Security
  • Part Three – Threat and Vulnerability Management – Other Layers
  • Part Four – Logging
  • Part Five – Cryptography and Key Management, and Identity Management
  • Part Six – Trust (network controls, such as firewalls and proxies), and Resilience

Logging

Notice “Logging” is used here, not “SIEM”. With use of “SIEM”, there is often a mental leap, or stumble, towards a commercial solution. But there doesn’t necessarily need to be a commercial solution. This post invites the reader to take a step back from the precipice of engaging with vendors, and check first if that journey is one you want to make.

Unfortunately, in 2020, it is still the case that many fintechs are doing one of two things:

  • Procuring a commercial solution without thinking about what is going to be logged, or thinking about the actual business goals that a logging solution is intended to achieve.
  • Just going with the Cloud Service Provider’s (CSP) SaaS offering – e.g. Stackdriver (now called “Operations”) for Google Cloud, or Security Center for Azure.

Design Process

The process HLD takes into risks from threat modelling (and maybe other sources), and another input from compliance requirements (maybe security standards and legal requirements), and uses the requirements from the HLD to drive the LLD. The LLD will call out the use cases and volume requirements that satisfy the HLD requirements – but importantly, it does not cover the technological solution. That comes later.

The diagram above calls out Splunk but of course it doesn’t have to be Splunk.

Security Operations

The end goal of the design process is heavily weighted towards a security operations or protective monitoring capability. Alerts will be specified which will then be configured into the technological solution (if it supports this). Run-books are developed based on on-going continuous improvement – this “tuning” is based on adjusting to false positives mainly, and adding further alerts, or modifying existing alerts.

The decision making on how to respond to alerts requires intimate knowledge of networks and applications, trust relationships, data flows, and the business criticality of information assets. This is not a role for fresh graduates. Risk assessment drives the response to an alert, and the decision on whether or not to engage an incident response process.

General IT monitoring can form the first level response, and then Security Operations consumes events from this first level that are related to potential security incidents.

Two main points relating this SecOps function:

  • Outsourcing doesn’t typically work when it comes to the 2nd level. Outsourcing of the first level is more likely to be cost effective. Dr Anton Chuvakin’s post on what can, and cannot be outsourced in security is the most well-rounded and realistic that i’ve seen. Generally anything that requires in-house knowledge and intimacy of how events relate to business risks – this cannot be outsourced at all effectively.
  • The maturity of SecOps doesn’t happen overnight. Expect it to take more than 12 months for a larger fintech with a complex cloud footprint.

The logging capability is the bedrock of SecOps, and how it relates to other security capabilities can be simplified as in the diagram below. The boxes on the left are self-explanatory with the possible exception of Active Trust Management – this is heavily network-oriented and at the engineering end of the rainbow, its about firewalls, reverse and forward proxies mainly:

Custom Use Cases

For the vast majority of cases, custom use cases will need to be formulated. This involves building a picture of “normal”, so as to enable alerting on abnormal. So taking the networking example: what are my data flows? Take my most critical applications – what are source and destination IP addresses, and what is the port on the server-side of the client-server relationship? So then a possible custom use case could be: raise an alert when a connection is aimed at the server from anywhere other than the client(s).

Generic use cases are no-brainers. Examples are brute force attempts and technology or user behaviour-specific use cases. Some good examples are here. Custom use cases requires an understanding of how applications, networks, and operating systems are knitted together. But both custom and generic use cases require a log source to be called out. For network events, this will be a firewall as the best candidate. It generally makes very little sense to deploy network IDS nodes in cloud.

So for each application, generate a table of custom use cases, and identify a log source for each. Generic use cases are those configured auto-tragically in Splunk Enterprise Security for example. But even Splunk cannot magically give you custom use cases, or even ensure that all devices are included in the coverage for generic use cases. No – humans still have a monopoly over custom use cases and well, really, most of SIEM configuration. AI and Cyberdyne Systems won’t be able to get near custom use cases in our lifetimes, or ever, other than the fantasy world of vendor Powerpoint slides.

Don’t forget to test custom use case alerting. So for network events, spin up a VM in a centrally trusted area, like a management Vnet/VPC for example. Port scan from there to see if alerts are triggered. Netcat can be very useful here too, for spoofing source addresses for example.

Correlation

Correlation was the phrase used by vendors in the heady days of the 00s. The premise was something like this: event A, event B, and event C. Taken in isolation (topical), each seem innocuous. But bake them together and you have a clear indicator that skullduggery is afoot.

I suggest you park correlation in the early stage of a logging capability deployment. Maybe consider it for down the road, once a decent level of maturity has been reached in SecOps, and consider also that any attempt to try and get too clever can result in your SIEM frying circuit boards. The aim initially should be to reduce complexity as much as possible, and nothing is better at adding complexity than correlation. Really – basic alerting on generic and custom use cases gives you most of the coverage you need for now, and in any case, you can’t expect to get anywhere near an ideal state with logging.

SaaS

Operating system logs are important in many cases. When you decide to SaaS a solution, note that you lose control over operating system events. You cannot turn off events that you’re not interested in (e.g. Windows Object auditing events which have had a few too many pizzas).Pizza This can be a problem if you decide to go with a COTS where licensing costs are based on volume of events. Also, you cannot turn on OS events that you could be interested in. The way CSPs play here is to assume everything is interesting, which can get expensive. Very expensive.

Note – its also, in most cases, not such a great idea to use a SaaS based SIEM. Why? Because this function has connectivity with everything. It has trust relationships with dev/test, pre-prod, and production. You really want full control over this platform (i.e. be able to login with admin credentials and take control of the OS), especially as it hosts lots of information that would be very interesting for attackers, and is potentially the main target for attackers, because of the trust relationships I mentioned before.

So with SaaS, its probably not the case that you are missing critical events. You just get flooded. The same applies to 3rd party applications, but for custom, in-house developed applications, you still have control of course of the application layer.

Custom, In-house Developed Applications

You have your debugging stream and you have your application stream. You can assign critical levels to events in your code (these are the classic syslog severity levels). The application events stream is critical. From an application security perspective, many events are not immediately intuitively of interest, but by using knowledge of how hackers work in practice, security can offer some surprises here, pleasant or otherwise.

If you’re a developer, you can ease the strain on your infosec colleagues by using consistent JSON logging keys across the board. For example, don’t start with ‘userid’ and then flip to ‘user_id’ later, because it makes the configuration of alerting more of a challenge than it needs to be. To some extent, this is unavoidable, because different vendors use different keys, but every bit helps. Note also that if search patterns for alerting have to cater for multiple different keys in JSON documents, the load on the SIEM will be unnecessarily high.

It goes without saying also: think about where your application and debug logs are being transmitted and stored. These are a source of extremely valuable intelligence for an attacker.

The Technology

The technological side of the logging capability isn’t the biggest side. The technology is there to fulfil a logging requirement, it is not in itself the logging capability. There are also people and processes around logging, but its worth talking about the technology.

What’s more common than many would think – organisation acquires a COTS SIEM tool but the security engineers hate it. Its slow and doesn’t do much of any use. So they find their own way of aggregating network-centralised events with a syslog bucket of some description. Performance is very often the reason why engineers will be grep’ing over syslog text files.

Whereas the aforementioned sounds ineffective, sadly its more effective than botched SIEM deployments with poorly designed tech. It also ticks the “network centralised logging” box for auditors.

The open-source tools solution can work for lots of organisations, but what you don’t get so easily is the real-time alerting. The main cost will be storage. No license fees. Just take a step back, and think what it is you really want to achieve in logging (see the design process above). The features of the open source logging solution can be something like this:

  • Rsyslog is TCP and covers authentication of hosts. Rsyslog is a popular protocol because it enables TCP layer transmission from most log source types (one exception is some Cisco network devices and firewalls), and also encryption of data in transit, which is strongly recommended in a wide open, “flat” network architecture where eavesdropping is a prevalent risk.
  • Even Windows can “speak” rsyslog with the aid of a local agent such as nxlog.
  • There are plenty of Host-based Intrusion Detection System (HIDS) agents for Linux and Windows – OSSEC, Suricata, etc.
  • Intermediate network logging Rsyslog servers can aggregate logs for network zones/subnets. There are the equivalent of Splunk forwarders or Alienvault Sensors. A cron job runs an rsync over Secure Shell (SSH), which uploads the batches of events data periodically to a Syslog Lake, for want of a better phrase.
  • The folder structure on the Syslog server can reflect dates – years, months, days – and distinct files are named to indicate the log source or intermediate server.
  • Good open source logging tools are getting harder to find. Once a tool gets a reputation, it aint’ free any mo. There are still some things you can do with ELK for free (but not alerting). Graylog is widely touted. At the time of writing you can still log e.g. 100 GB/day, and you don’t pay if you forego support or any of the other Enterprise features.

Splunk

Splunk sales people have a dart board with my picture on it. To be fair, the official Splunk line is that they want to help their customers save events indexing money because it benefits them in the longer term. And they’re right, this does work for Splunk and their customers. But many of the resellers are either lacking the skills to help, or they are just interested in a quick and dirty install. “Live for today, don’t worry about tomorrow”.

Splunk really is a Lamborghini, and the few times when i’ve been involved in bidding beauty parades for SIEM, Splunk often comes out cheaper believe it or not. Splunk was made for logging and was engineered as such. Some of the other SIEM engines are poorly coded and connect to a MySQL database for example, whereas Splunk has its own database effectively. The difference in performance is extraordinary. A Splunk search involving a complex regex with busy indexers and search heads takes a fraction of the time to complete, compared with a similar scenario from other tools on the same hardware.

Three main ways to reduce events indexing costs with Splunk:

  • Root out useless events. Windows is the main culprit here, in particular Auditing of Objects. Do you need, for example, all that performance monitoring data? Debug events? Firewall AND NIDS events? Denied AND accepted packets from firewalls?
  • Develop your use cases (see above) and turn off all other logging. You can use filters to achieve this.
  • You can be highly selective about which events are forwarded to the Splunk indexer. One conceptual model just to illustrate the point is given below:

Threat Hunting

Threat Hunting is kind of the sexy offering for the world of defence. Offence has had more than its fair share of glamour offerings over the years. Now its defence’s turn. Or is it? I mean i get it. It’s a good thing to put on your profile, and in some cases there are dramatic lines such as “be the hunter or the hunted”.

However, a rational view of “hunting” is that it requires LOTS of resources and LOTS of skill – two commodities that are very scarce. Threat hunting in most cases is the worst kind of resources sink hole. If you take vulnerability management (TVM) and the kind of basic detection discussed thus far in this article, you have a defence capability that in most cases fits the risk management needs of the organisation. So then there’s two questions to ask:

  • How much does threat hunting offer on top of a suitably configured logging and TVM capability? Not much in the best of cases. Especially with credentialed scanning with TVM – there is very little of your attack surface that you cannot cover.
  • How much does threat hunting offer in isolation (i.e. threat hunting with no TVM or logging)? This is the worst case scenario that will end up getting us all fired in security. Don’t do it!!! Just don’t. You will be wide open to attack. This is similar to a TVM program that consists only of one-week penetration tests every 6 months.

Threat Intelligence (TI)

Ok so here’s a funny story. At a trading house client here in London around 2016: they were paying a large yellow vendor lots of fazools every month for “threat intelligence”. I couldn’t help but notice a similarity in the output displayed in the portal as compared with what i had seen from the client’s Alienvault. There is a good reason for this: it WAS Alienvault. The feeds were coming from switches and firewalls inside the client network, and clearly $VENDOR was using Alienvault also. So they were paying heaps to see a duplication of the data they already had in their own Alienvault.

The aforementioned is an extremely bad case of course. The worst of the worst. But can you expect more value from other threat intelligence feeds? Well…remember what i was saying about the value of an effective TVM and detection program? Ok I’ll summarise the two main problems with TI:

  • You can really achieve LOTS in defence with a good credentialed TVM program plus even a half-decent logging program. I speak as someone who has lots of experience in unrestricted penetration testing – believe me you are well covered with a good TVM and detection SecOps function. You don’t need to be looking at threats apart from a few caveats…see later.
  • TI from commercial feeds isn’t about your network. Its about the whole planet. Its like picking up a newspaper to find out what’s happening in the world, and seeing on the front cover that a butterfly in China has flapped its wings recently.

Where TI can be useful – macro developments and sector-specific developments. For example, a new approach to Phishing, or a new class of vulnerability with software that you host, or if you’re in the public sector and your friendly national spy agency has picked up on hostile intentions towards you. But i don’t want to know that a new malware payload has been doing the rounds. In the time taken to read the briefing, 2000 new payloads have been released to the wild.

Summary

  • Start out with a design process that takes input feeds from compliance and risk (perhaps threat modelling), use the resulting requirements to drive the LLD, which may or may not result in a decision to procure tech that meets the requirements of the LLD.
  • An effective logging capability can only be designed with intimate knowledge of the estate – databases, crown jewels, data flows – for each application. Without such knowledge, it isn’t possible to build even a barely useful logging capability. Call out your generic and custom use cases in your LLD, independent of technology.
  • Get your basic alerting first, correlation can come later, if ever.
  • Outsourcing is a waste of resources for second level SecOps.
  • With SaaS, your SIEM itself is dangerously exposed, and you have no control over what is logged from SaaS log sources.
  • You are not mandated to get a COTS. Think about what it is that you want to achieve. It could be that open source tools across the board work for you.
  • Splunk really is the Lamborghini of SIEMs and the “expensive” tag is unjustified. If you carefully design custom and generic use cases, and remove everything else from indexing, you suddenly don’t have such an expensive logger. You can also aggregate everything in a Syslog pool before it hits Splunk indexers, and be more selective about what gets forwarded.
  • I speak as someone with lots of experience in unrestricted penetration testing: Threat Hunting and Threat Intelligence aren’t worth the effort in most cases.

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Netdelta – Install and Configure

Netdelta is a tool for monitoring networks and flagging alerts upon changes in advertised services. Now – I like Python and especially Django, and around 2014 or so i was asked to setup a facility for monitoring for changes in that organisation’s perimeter. After some considerable digging, i found nada, as in nothing, apart from a few half-baked student projects. So i went off and coded Netdelta, and the world has never been the same since.

I guess when i started with Netdelta i didn’t see it as a solution that would be widely popular because i was under the impression you could just do some basic shell scripting with nmap, and ndiff is specifically designed for delta flagging. However what became apparent at an early stage was that timeouts are a problem. A delta will be flagged when a host or service times out – and this happens a lot, even on a gigabit LAN, and it happens even more in public clouds. I built some analytics into Netdelta that looks back over the scan history and data and makes a call on the likelihood of a false positive (red, amber green).

Most organisations i worked with would benefit from this. One classic example i can think of – a trading house that had been on an aggressive M&A spree, maybe it was Black Friday or…? Anyway – they fired some network engineers and hired some new and cheaper ones, exacerbating what was already a poorly managed perimeter scenario. CISO wanted to know what was going off with these Internet facing subnets – enter Netdelta. Unauthorised changes are a problem! I am directly aware of no fewer than 6 incidents that occurred as a result of exposed SSH, SMB (Wannacry), and more recently RDP, and indirectly aware of many more.

Anyway without further waffle, here’s how you get Netdelta up and running. Warning – there are a few moving parts, but if someone wants it in Docker, let me know.

I always go with Ubuntu. The differences between Linux distros are like the differences between mueslis. My build was on 18.04 but its highly likely 19 variants will be just fine.

apt-get update
apt-get install curl nmap apache2 python3 python3-pip python3-venv rabbitmq-server mysql-server libapache2-mod-wsgi-py3 git
apt-get -y install software-properties-common
add-apt-repository ppa:certbot/certbot
apt-get install -y python-certbot-apache
Clone the repository from github into your <netdelta root> 
git clone https://github.com/SevenStones/netdelta.git

Filesystem

Create the user that will own <netdelta root>

useradd -s /bin/bash -d /home/<user> -m <user>

Create the directory that will host the Netdelta Django project if necessary

Add the user to a suitable group, and strip world permissions from netdelta directories

 groupadd <group> 
 usermod -G  <group> <user>
 usermod -G  <group> www-data
 chown -R www-data:<group> /var/www
 chown -R <user>:<group> <netdelta root> 

Make the logs dir, e.g. /logs, and you will need to modify /nd/netdelta_logger.py to point to this location. Note the celery monitor logs go to /var/log/celery/celery-monitor.log …which of course you can change.

Strip world permissions from all netdelta and apache root dirs:

chmod -Rv o-rwx <web root>
chmod -Rv o-rwx <netdelta root>

Virtualenv

The required packages are in requirements.txt, in the root of the git repo. Your virtualenv build with Python 3 goes approximately like this …

python3 -m venv /path/to/new/virtual/environment

You activate thusly: source </path/to/new/virtual/environment/>/bin/activate

Then suck in the requirements as root, remembering to fix permissions after you do this.

pip3 install wheel
pip3 install -r <netdelta root>/requirements.txt

You can use whatever supported database you like. MySQL is assumed here.

The Python framework mysqlclient was used with earlier versions of Django and MySQL. but with Python 3 and later Django versions, the word on the street is PyMySQL is the way to go. With this though, it took some trickery to get the Django project up and running; in the form of init.py for the project (<netdelta root>/netdelta/.init.py) and adding a few lines …

import pymysql 
pymysql.install_as_MySQLdb()

While in virtualenv, and under your netdelta root, add a superuser for the DF

Patch libnmap

Two main mods to the libnmap in usage with Netdelta were necessary. First, with later versions of Celery (>3.1), there was a security issue with “deamonic processes are not allowed to have children”, for which an alternative fork of libnmap fixed the problem. Then we needed to return to Netdelta the process id of the running nmap port scanner process.

cd /opt
git clone https://github.com/pyoner/python-libnmap.git
cp ./python-libnmap/libnmap/process.py <virtualenv root>/lib/python3.x/site-packages/libnmap/

then patch libnmap to allow Netdelta to kill scanning processes

<netdelta_root>/scripts/fix-libnmap.bash

Change the environment variables to match your install and use the virtualenv name as a parameter

Database Setup

Create a database called netdetla and use whichever encoding snd collation you like.

CREATE DATABASE netdelta CHARACTER SET utf8 COLLATE utf8_general_ci;

Then from <netdelta root> with virtualenv engaged:

python manage.py makemigrations nd
python manage.py migrate

Web Server

I am assuming all you good security pros don’t want to use the development server? Well as you’re only dealing with port scan data then….your call. I’m assuming Apache as a production web server.

You will need to give Apache a stub web root and enable the wsgi module. For the latter i added this to apache2.conf – this gives you some control over the exact version of Python loaded.

LoadModule wsgi_module "/usr/lib/python3.7/site-packages/mod_wsgi/server/mod_wsgi-py37.cpython-37m-i386-linux-gnu.so"
WSGIPythonHome "/usr"

Under the DocumentRoot line in your apache config file, give the pointers for WSGI.

WSGIDaemonProcess <site> python-home=<virtualenv root> python-path=<netdelta root>  WSGIProcessGroup <site>  WSGIScriptAlias / <netdelta root>/netdelta/wsgi.py  Alias /static/ <netdelta root>/netdelta/

Note also you will need to adjust your wsgi.py under <netdelta root>/netdelta/ –

# Add the site-packages of the chosen virtualenv to work with site.addsitedir('<virtualenv root>/lib/python3.7/site-packages')

Celery

From the current shell
in …<virtualenv> ….under <netdelta root>

celery worker -E -A nd -n default -Q default --loglevel=info -B --logfile=<netdelta root>/logs/celery.log

Under systemd (you will almost certainly want to do this) with the root user. The script pointed to by systemd for

systemctl start celery

can have all the environment checking (this isn’t intended to be a tutorial in BASH scripting), but the core of it…

cd <netdelta root>
nohup $VIRTUALENV_DIR/bin/celery worker -E -A nd -n ${SITE} -Q ${SITE} --loglevel=info -B --logfile=${SITE_LOGS}/celery.log >/dev/null 2>&1 &

And then you can put together your own scripts for status, stop, restart.

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Fintechs and Security – Part Three

  • Prologue – covers the overall challenge at a high level
  • Part One – Recruiting and Interviews
  • Part Two – Threat and Vulnerability Management – Application Security
  • Part Three – Threat and Vulnerability Management – Other Layers
  • Part Four – Logging
  • Part Five – Cryptography and Key Management, and Identity Management
  • Part Six – Trust (network controls, such as firewalls and proxies), and Resilience
Threat and Vulnerability Management (TVM) – Other Layers

This article covers the key principles of vulnerability management for cloud, devops, and devsecops, and herein addresses the challenges faced by fintechs.

The previous post covered TVM from the application security point of view, but what about everything else? Being cloud and “dynamic”, even with Kubernetes and the mythical Immutable Architecture, doesn’t mean you don’t have to worry about the security of the operating systems and many devices in your cloud. The devil loves to hear claims to the effect that devops never SSHs to VM instances. And does SaaS help? Well that depends if SaaS is a good move – more on that later.

Fintechs are focussing on application security, which is good, but not so much in the security of other areas such as containers, IaaS/SaaS VMs, and little thought is ever given to the supply of patches and container images (they need to come from an integral source – preferably not involving pulling from the public Internet, and the patches and images need to be checked for integrity themselves).

And in general with vulnerability assessment (VA), we in infosec are still battling a popular misconception, which after a quarter of a decade is still a popular misconception – and that is the value, or lack of, of unauthenticated scanners such as OpenVAS and Nessus. More on this later.

The Overall Approach

The design process for a TVM capability was covered in Part One. Capabilities are people, process, and technology. They’re not just technology. So the design of TVM is not as follows: stick an OpenVAS VM in a VPC, fill it with target addresses, send the auto-generated report to ops. That is actually how many fintechs see the TVM challenge, or they just see it as being a purely application security show.

So there is a vulnerability reported. Is it a false positive? If not, then what is the risk? And how should the risk be treated? In order to get a view of risk, security professionals with an attack mindset need to know

  • the network layout and data flows – think from the point of view of an attacker – so for example if a front end web micro-service is compromised, what can the attacker can do from there? Can they install recon tools such as a port scanner or sniffer locally and figure out where the back end database is? This is really about “trust relationships”. That widget that routes connections may in itself seem like a device that isn’t worthy of attention, but it routes connections to a database hosting crown jewels…you can see its an important device and its configuration needs some intense scrutiny.
  • the location and sensitivity of critical information assets.
  • The ease and result of an exploit – how easy is it to gain a local shell presence and then what is the impact?

The points above should ideally be covered as part of threat modelling, that is carried out before any TVM capability design is drafted.

if the engineer or analyst or architect has the experience in CTF or simulated attack, they are in a good position to speak confidently about risk.

Types of Tool

I covered appsec tools in part two.

There are two types: unauthenticated and credentialed or authenticated scanners.

Many years ago i was an analyst running VA scans as part of an APAC regional accreditation service. I was using Nessus mostly but some other tools also. To help me filter false positives, I set up a local test box with services like Apache, Sendmail, etc, pointed Nessus at the box, then used Ethereal (now Wireshark) to figure out what the scanner was actually doing.

What became abundantly obvious with most services, is that the scanner wasn’t actually doing anything. It grabs a service banner and then …nothing. tumbleweed

I thought initially there was a problem with my setup but soon eliminated that doubt. There are a few cases where the scanner probes for more information but those automated efforts are somewhat ineffectual and in many cases the test that is run, and then the processing of the result, show a lack of understanding of the vulnerability. A false negative is likely to result, or at best a false positive. The scanner sees a text banner response such as “apache 2.2.14”, looks in its database for public disclosed vulnerability for that version, then barfs it all out as CRITICAL, red colour, etc.

Trying to assess vulnerability of an IaaS VM with unauthenticated VA scanners is like trying to diagnose a problem with your car without ever lifting the hood/bonnet.

So this leads us to credentialed scanners. Unfortunately the main players in the VA space pander to unauthenticated scans. I am not going to name vendors here, but its clear the market is poorly served in the area of credentialed scanning.

It’s really very likely that sooner rather than later, accreditation schemes will mandate credentialed scanning. It is slowly but surely becoming a widespread realisation that unauthenticated scanners are limited to the above-mentioned testing methodology.

So overall, you will have a set of Technical Security Standards for different technologies such as Linux, Cisco IoS, Docker, and some others. There are a variety of tools out there that will get part of the job done with the more popular operating systems and databases. But in order to check compliance to your Technical Security Standards, expect to have to bridge the gap with your own scripting. With SSH this is infinitely feasible. With Windows, it is harder, but check Ansible and how it connects to Windows with Python.

Asset Management

Before you can assess for vulnerability, you need to know what your targets are. Thankfully Cloud comes with fewer technical barriers here. Of course the same political barriers exist as in the on-premise case, but the on-premise case presents many technical barriers in larger organisations.

Google Cloud has a built-in feature, and with AWS, each AWS Service (eg Amazon EC2, Amazon S3) have their own set of API calls and each Region is independent. AWS Config is highly useful here.

SaaS

I covered this issue in more detail in a previous post.

Remember the old times of on-premise? Admins were quite busy managing patches and other aspects of operating systems. There are not too many cases where a server is never accessed by an admin for more than a few weeks. There were incompatibilities and patch installs often came with some banana skins around dependencies.

The idea with SaaS is you hand over your operating systems to the CSP and hope for the best. So no access to SMB, RDP, or SSH. You have no visibility of patches that were installed, or not (!), and you have no idea which OS services are enabled or not. If you ask your friendly CSP for more information here, you will not get a reply, and if you do they will remind you that handed over your 50-million-lines-of-source-code OSes to them.

Here’s an example – one variant of the Conficker virus used the Windows ‘at’ scheduling service to keep itself prevalent. Now cloud providers don’t know if their customers need this or not. So – they verge on the side of danger and assume that they do. They will leave it enabled to start at VM boot up.

Note that also – SaaS instances will be invisible to credentialed VA scanners. The tool won’t be able to connect to SSH/RDP.

I am not suggesting for a moment that SaaS is bad. The cost benefits are clear. But when you moved to cloud, you saved on managing physical data centers. Perhaps consider that also saving on management of operating systems maybe taking it too far.

Patching

Don’t forget patching and look at how you are collecting and distributing patches. I’ve seen some architectures where the patching aspect is the attack vector that presents the highest danger, and there have been cases where malicious code was introduced as a result of poor patching.

The patches need to come from an integral source – this is where DNSSEC can play a part but be aware of its limitations – e.g. update.microsoft.com does not present a ‘dnskey’ Resource Record. Vendors sometimes provide a checksum or PGP cryptogram.

Some vendors do not present any patch integrity checksums at all and will force users to download a tarball. This is far from ideal and a workaround will be critical in most cases.

Redhat has their Satellite Network which will meet most organisations’ requirements.

For cloud, the best approach will usually be to ingress patches to a management VPC/Vnet, and all instances (usually even across differing code maturity level VPCs), can pull from there.

Delta Testing

Doing something like scanning critical networks for changes in advertised listening services is definitely a good idea, if not for detecting hacker shells, then for picking up on unauthorised changes. There is no feasible means to do this manually with nmap, or any other port scanner – the problem is time-outs will be flagged as a delta. Commercial offerings are cheap and allow tracking over long histories, there’s no false positives, and allow you to create your own groups of addresses.

Penetration Testing

There’s ideal state, which for most orgs is going to be something like mature vulnerability management processes (this is vulnerability assessment –> deduce risk with vulnerability –> treat risk –> repeat), and the red team pen test looks for anything you may have missed. Ideally, internal sec teams need to know pretty much everything about their network – every nook and cranny, every switch and firewall config, and then the pen test perhaps tells them things they didn’t already know.

Without these VM processes, you can still pen test but the test will be something like this: you find 40 holes of the 1000 in the sieve. But it’s worse than that, because those 40 holes will be back in 2 years.

There can be other circumstances where the pen test by independent 3rd party makes sense:

  • Compliance requirement.
  • Its better than nothing at all. i.e. you’re not even doing VA scans, let alone credentialed scans.

Wrap-up

  • It’s far from all about application security. This area was covered in part two.
  • Design a TVM capability (people, process, technology), don’t just acquire a technology (Qualys, Rapid 7, Tenable SC. etc), fill it with targets, and that’s it.
  • Use your VA data to formulate risk, then decide how to treat the risk. Repeat. Note that CVSS ratings are not particularly useful here. You need to ascertain risk for your environment, not some theoretical environment.
  • Credentialed scanning is the only solution worth considering, and indeed it’s highly likely that compliance schemes will soon start to mandate credentialed scanning.
  • Use a network delta tester to pick up on hacker shells and unauthorised changes in network services and firewalls.
  • Being dynamic with Kubernetes and microservices has not yet killed your platform risk or the OS in general.
  • SaaS may be a step too far for many, in terms of how much you can outsource.
  • When you SaaS’ify a service, you hand over the OS to a CSP, and also remove it from the scope of your TVM VA credentialed scanning.
  • Penetration testing has a well-defined place in security, which isn’t supposed to be one where it is used to inform security teams about their network! Think compliance, and what ideal state looks like here.

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