Threat actors are increasingly adopting security automation and machine learning – security teams will have to follow suit, or risk falling behind.
Many organizations still conduct incident response based on manual processes. Many playbooks that we have seen in our customer base, for example, hand off to other stakeholders within the organization to wait for additional forensic data, and to execute remediation and containment actions.
While this may seem like good practice to avoid inadvertent negative consequences such as accidentally shutting down critical systems or locking out innocent users, it also means that many attacks are not contained in a sufficiently short time to avoid the worst of their consequences.
Manual Processes Cannot Compete with Automation
Reports are mounting about threat actors and hackers leveraging security automation and machine learning to increase the scale and volume, as well as the velocity of attacks. The implications for organizations should be cause for concern, considering that we have been challenged to effectively respond to less sophisticated attacks in the past.
Ransomware is a case in point. In its most simple form, a ransomware attack does not require the full cyber kill chain to be successful. A user receives an email attachment, executes it, the data is encrypted and the damage is done. At that point, incident response turns into disaster recovery.
Automated attacks have been with us for a long time. Worms and Autorooters have been around since the beginning of hacking, with WannaCry and its worming capability only the most recent example. But these have only automated some aspects of the attack, still permitting timely and successful threat containment further along the kill chain.
Threat actors have also leveraged automated command and control infrastructure for many years. DDoS Zombie Botnets, for example, are almost fully automated. To sum it up, the bad guys have automated, the defenders have not. Manual processes cannot compete with automation.
With the increase in the adoption of automation and machine learning by cyber criminals, enterprises will find that they will have to automate as well. The future mantra will be “Automate or Die”.
Making the Cure More Palatable Than the Disease
But automating containment actions is still a challenging topic. Here at DFLabs we still encounter a lot of resistance to the idea by our customers. Security teams understand that the escalating sophistication and velocity of cyber-attacks means that they must become more agile to rapidly respond to cyber incidents. But the risk of detrimentally impacting operations means that they are reluctant to do so, and rarely have the political backing and clout even if they want to.
Security teams will find themselves having to rationalize the automation of incident response to other stakeholders in their organization more and more in the future. This will require being able to build a business case to justify the risk of automating containment. They will have to explain why the cure is not worse than the disease.
There are three questions that are decisive in evaluating whether to automate containment actions:
- How reliable are the detection and identification?
- What is the potential detrimental impact if the automation goes wrong?
- What is the potential risk if this is not automated?
Our approach at DFLabs to this is to carefully evaluate what to automate, and how to do this safely. We support organizations in selectively applying automation through our R3 Rapid Response Runbooks. Incident Responders can apply dual-mode actions that combine manual, semi-automated and fully automated steps to provide granular control over what is automated. R3 Runbooks can also include conditional statements that apply full automation when it is safe to do so but request that a human vet’s the decision in critical environments or where it may have a detrimental impact on operational integrity.