The Future of Cyber Security: 2022 Predictions by Darktrace
06
Jan 2022
Discover cyber security predictions for 2022 by Darktrace's experts. Learn how to navigate future cyber threats and enhance your security strategy!
2021 brought some of the most significant cyber-attacks in history – from the Kaseya supply chain ransomware attack to cyber-criminals attempting to poison the water supply in Florida, to the already infamous Log4Shell vulnerability.
Darktrace cyber and AI experts spent the year not only delivering various crucial AI innovations in the defensive cyber security space, but also advising over 6,500 organizations around the world on how to use this AI to fight back against sophisticated attacks in the wild – and win.
So, we asked our experts, what does 2022 have in store for cyber security?
“Software supply chain attacks become a given in 2022.”
Justin Fier, Director of Cyber Intelligence & Analytics
Our security research uncovered that the most attacked industry in 2021 was the information technology (IT) and communications sector, whereas, in 2020, it was the financial services industry. This shift may not be surprising given the high-profile software supply chain attacks on SolarWinds, Kaseya, GitLab, and, most recently, the uncovered vulnerability ‘Log4Shell’ embedded in a widely used software library that left billions of devices exposed.
Attackers see software and developer infrastructure, platforms, and providers as an entry vector into government, corporations, and critical infrastructure. Threat actors will embed malicious software throughout the software supply chain, including proprietary source code, developer repositories, open-source libraries, and more. We will likely see further supply chain attacks against software platforms and further publicized vulnerabilities.
They will also advance their email attacks to more directly hijack the communications chain with supplier account hijacks to send spear phishing emails from genuine, trusted accounts, as we saw in the November 2021 FBI account takeover.
If attackers can embed themselves at the beginning of the development process, organizations will have to detect and stop the attacker after they have gotten through. This threat reinforces the need for security to be integrated earlier in the development process and the importance of quickly containing attacks to prevent business disruption. Since these are multi-stage attacks, organizations can use AI at every step to contain and remediate the threat.
“Ransomware in 2022: more of the same, but different.”
Marcus Fowler, Director of Strategic Threat
In parallel to the global pandemic, there has been a growing ransomware pandemic. Our researchers discovered that the number of attacks on US organizations tripled in 2021 compared to 2020, and attacks on UK organizations doubled.
This crisis brought 30 nations together to discuss a counter-ransomware initiative focused on cryptocurrency regulation, security resilience, attack disruption, and international cyber diplomacy. Despite these landmark policy efforts, even if government pressures force ransomware groups to disband or criminally charge ransomware gangs, they will continue to rebrand and crop back up with even more sophisticated techniques and capabilities.
If we let ransomware permeate, attackers will likely evolve techniques in 2022 and may target cloud service providers, and backup and archiving providers. There will come a time when this is no longer seen as a cyber inconvenience – when organizations can’t just stand there and take it anymore. Critical infrastructure organizations and businesses alike will continue to assess how quickly they can restore operations in the aftermath of an attack and how long they will be able to rely on cyber insurers to cover ransom payments and costly systems repairs.
If playing defense against ransomware is not sustainable, what is the answer? Eventually, organizations will build systems to withstand cyber-attacks. In the meantime, organizations need security software that learns, makes micro-decisions, and takes proportional responses to detect and stop attacks early enough, before data exfiltration or encryption occurs.
“Human and AI relationships will improve with explainability.”
Max Heinemeyer, Director of Threat Hunting
Defenders have applied AI to the existential threat of cyber-attacks for nearly a decade now, from detecting threats to using autonomous micro-decision making to respond to attacks at machine speed. The breakthroughs in helping security teams perform at their most optimal state may not be through those advanced mathematical algorithms alone. In 2022, it will likely be through Explainable Artificial Intelligence (XAI).
The processes and methods that allow human users to comprehend and trust the results and output created by machine learning will be at the forefront in Security Operations Centers. This focus on time to understanding rather than simply time to alert will advance how companies measure security team effectiveness. There will be an increase in focus on XAI in sharp contrast with the concept of a “black box”, as security experts want to understand AI’s expected impacts and potential biases.
Examples of this include using natural language processing (NLP) to explain the hypotheses behind a cyber-attack, the investigation steps performed by AI, the outcomes of those steps, the recommended actions to take – and even how to prevent the attack from happening again.
“The ‘Great Resignation’ will drive an uptick in insider threat.”
Toby Lewis, Head of Threat Analysis
With the ‘Great Resignation’ of employees during the pandemic, we can expect to see disgruntled employees steal information or employees unintentionally taking information with them to their next job. We have also seen criminal groups attempt to recruit insiders by offering a large sum of money or a portion of the ransom.
Whether intentional or unintentional, insiders will become a growing priority for businesses in 2022. With more organizations relying on cloud communication and collaboration applications, these threats become even more difficult to detect across sprawling digital infrastructures. With employees working remotely, enforcing the return of equipment and data will become even more difficult.
Organizations will rely more heavily on security technology that understands employee behavior from multiple angles, including cloud, SaaS, user, and the endpoint. This technology automatically takes action when an employee behaves out of character – by sending emails to outside sources, accessing files they usually wouldn’t, or other anomalous activities. These approaches will work alongside new zero trust technologies and adhere to zero trust architectures to protect organizations from insider threats.
“AI innovations help defenders proactively simulate attacks.”
Nicole Eagan, Chief Strategy Officer, AI Officer
AI has delivered various crucial innovations in the defensive cyber security space for threat detection, investigation, and response. 2022 will see AI innovations expand from a focus on defense to adjacent areas, such as proactive security and attack simulations.
Recent advancements that enable AI to perform attack path modeling, adversary simulation, and continuous red teaming will enable organizations to visualize and test the most probable scenarios of concern and mitigate cyber risks with safety measures and controls. The fundamental priorities of cyber security organizations will change shape as they place more focus on emerging technologies to identify vulnerabilities, launch controlled attacks, and test their defenses.
While this so-called proactive and predictive approach to managing cyber risk hasn’t hit the boardroom just yet, it has the potential to change how companies, regulators, audit committees, and cyber insurance companies assess their future cyber risk.
Thank you to all of our subject matter experts for providing supplementary insights to support these predictions.
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Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Author
Justin Fier
SVP, Red Team Operations
Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.
Darktrace’s view on Operation Lunar Peek: Exploitation of Palo Alto firewall devices (CVE 2024-2012 and 2024-9474)
Introduction: Spike in exploitation and post-exploitation activity affecting Palo Alto firewall devices
As the first line of defense for many organizations, perimeter devices such as firewalls are frequently targeted by threat actors. If compromised, these devices can serve as the initial point of entry to the network, providing access to vulnerable internal resources. This pattern of malicious behavior has become readily apparent within the Darktrace customer base. In 2024, Darktrace Threat Research analysts identified and investigated at least two major campaigns targeting internet-exposed perimeter devices. These included the exploitation of PAN-OS firewall exploitation via CVE 2024-3400 and FortiManager appliances via CVE 2024-47575.
More recently, at the end of November, Darktrace analysts observed a spike in exploitation and post-exploitation activity affecting, once again, Palo Alto firewall devices in the days following the disclosure of the CVE 2024-0012 and CVE-2024-9474 vulnerabilities.
Threat Research analysts had already been investigating potential exploitation of the firewalls’ management interface after Palo Alto published a security advisory (PAN-SA-2024-0015) on November 8. Subsequent analysis of data from Darktrace’s Security Operations Center (SOC) and external research uncovered multiple cases of Palo Alto firewalls being targeted via the likely exploitation of these vulnerabilities since November 13, through the end of the month. Although this spike in anomalous behavior may not be attributable to a single malicious actor, Darktrace Threat Research identified a clear increase in PAN-OS exploitation across the customer base by threat actors likely utilizing the recently disclosed vulnerabilities, resulting in broad patterns of post-exploitation activity.
How did exploitation occur?
CVE 2024-0012 is an authentication bypass vulnerability affecting unpatched versions of Palo Alto Networks Next-Generation Firewalls. The vulnerability resides in the management interface application on the firewalls specifically, which is written in PHP. When attempting to access highly privileged scripts, users are typically redirected to a login page. However, this can be bypassed by supplying an HTTP request where a Palo Alto related authentication header can be set to “off”. Users can supply this header value to the Nginx reverse proxy server fronting the application which will then send it without any prior processing [1].
CVE-2024-9474 is a privilege escalation vulnerability that allows a PAN-OS administrator with access to the management web interface to execute root-level commands, granting full control over the affected device [2]. When combined, these vulnerabilities enable unauthenticated adversaries to execute arbitrary commands on the firewall with root privileges.
Post-Exploitation Patterns of Activity
Darktrace Threat Research analysts examined potential indicators of PAN-OS software exploitation via CVE 2024-0012 and CVE-2024-9474 during November 2024. The investigation identified three main groupings of post-exploitation activity:
Exploit validation and initial payload retrieval
Command and control (C2) connectivity, potentially featuring further binary downloads
Potential reconnaissance and cryptomining activity
Exploit Validation
Across multiple investigated customers, Darktrace analysts identified likely vulnerable PAN-OS devices conducting external network connectivity to bin services. Specifically, several hosts performed DNS queries for, and HTTP requests to Out-of-Band Application Security Testing (OAST) domains, such as csv2im6eq58ujueonqs0iyq7dqpak311i.oast[.]pro. These endpoints are commonly used by network administrators to harden defenses, but they are increasingly used by threat actors to verify successful exploitation of targeted devices and assess their potential for further compromise. Although connectivity involving OAST domains were prevalent across investigated incidents, this activity was not necessarily the first indicator observed. In some cases, device behavior involving OAST domains also occurred shortly after an initial payload was downloaded.
Initial Payload Retrieval
Following successful exploitation, affected devices commonly performed behaviors indicative of initial payload download, likely in response to incoming remote command execution. Typically, the affected PAN-OS host would utilize the command line utilities curl and Wget, seen via use of user agents curl/7.61.1 and Wget/1.19.5 (linux-gnu), respectively.
In some cases, the use of these command line utilities by the infected devices was considered new behavior. Given the nature of the user agents, interaction with the host shell suggests remote command execution to achieve the outgoing payload requests.
While additional binaries and scripts were retrieved in later stages of the post-exploitation activity in some cases, this set of behaviors and payloads likely represent initial persistence and execution mechanisms that will enable additional functionality later in the kill chain. During the investigation, Darktrace analysts noted the prevalence of shell script payload requests. Devices analyzed would frequently make HTTP requests over the usual destination port 80 using the command line URL utility (curl), as seen in the user-agent field.
The observed URIs often featured requests for text files, such as “1.txt”, or shell scripts such as “y.sh”. Although packet capture (PCAP) samples were unavailable for review, external researchers have noted that the IP address hosting such “1.txt” files (46.8.226[.]75) serves malicious PHP payloads. When examining the contents of the “y.sh” shell script, Darktrace analysts noticed the execution of bash commands to upload a PHP-written web shell on the affected server.
While not all investigated cases saw initial shell script retrieval, affected systems would commonly make an external HTTP connection, almost always via Wget, for the Executable and Linkable Format (ELF) file “/palofd” from the rare external IP 38.180.147[.]18.
Such requests were frequently made without prior hostname lookups, suggesting that the process or script initiating the requests already contained the external IP address. Analysts noticed a consistent SHA1 hash present for all identified instances of “/palofd” downloads (90f6890fa94b25fbf4d5c49f1ea354a023e06510). Multiple open-source intelligence (OSINT) vendors have associated this hash sample with Spectre RAT, a remote access trojan with capabilities including remote command execution, payload delivery, process manipulation, file transfers, and data theft [3][4].
Several targeted customer devices were observed initiating TLS/SSL connections to rare external IPs with self-signed TLS certificates following exploitation. Model data from across the Darktrace fleet indicated some overlap in JA3 fingerprints utilized by affected PAN-OS devices engaging in the suspicious TLS activity. Although JA3 hashes alone cannot be used for process attribution, this evidence suggests some correlation of source process across instances of PAN-OS exploitation.
These TLS/SSL sessions were typically established without the specification of a Server Name Indication (SNI) within the TLS extensions. The SNI extension prevents servers from supplying an incorrect certificate to the requesting client when multiple sites are hosted on the same IP. SSL connectivity without SNI specification suggests a potentially malicious running process as most software establishing TLS sessions typically supply this information during the handshake. Although the encrypted nature of the connection prevented further analysis of the payload packets, external sources note that JavaScript content is transmitted during these sessions, serving as initial payloads for the Sliver C2 platform using Wget [5].
C2 Communication and Additional Payloads
Following validation and preliminary post-compromise actions, examined hosts would commonly initiate varying forms of C2 connectivity. During this time, devices were frequently detected making further payload downloads, likely in response to directives set within C2 communications.
Palo Alto firewalls likely exploited via the newly disclosed CVEs would commonly utilize the Sliver C2 platform for external communication. Sliver’s functionality allows for different styles and formatting for communication. An open-source alternative to Cobalt Strike, this framework has been increasingly popular among threat actors, enabling the generation of dynamic payloads (“slivers”) for multiple platforms, including Windows, MacOS, Linux.
These payloads allow operators to establish persistence, spawn new shells, and exfiltrate data. URI patterns and PCAPs analysis yielded evidence of both English word type encoding within Sliverand Gzip formatting.
For example, multiple devices contacted the Sliver-linked IP address 77.221.158[.]154 using HTTP to retrieve Gzip files. The URIs present for these requests follow known Sliver Gzip formatted communication patterns [6]. Investigations yielded evidence of both English word encoding within Sliver, identified through PCAP analysis, and Gzip formatting.
External connectivity during this phase also featured TCP connection attempts over uncommon ports for common application protocols. For both Sliver and non-Sliver related IP addresses, devices utilized destination ports such as 8089, 3939, 8880, 8084, and 9999 for the HTTP protocol. The use of uncommon destination ports may represent attempts to avoid detection of connectivity to rare external endpoints. Moreover, some external beaconing within included URIs referencing the likely IP of the affected device. Such behavior can suggest the registration of compromised devices with command servers.
Targeted devices also proceeded to download additional payloads from rare external endpoints as beaconing/C2 activity was ongoing. For example, the newly registered domain repositorylinux[.]org (IP: 103.217.145[.]112) received numerous HTTP GET requests from investigated devices throughout the investigation period for script files including “linux.sh” and “cron.sh”. Young domains, especially those that present as similar to known code repositories, tend to host harmful content. Packet captures of the cron.sh file reveal commands within the HTTP body content involving crontab operations, likely to schedule future downloads. Some hosts that engaged in connectivity to the fake repository domain were later seen conducting crypto-mining connections, potentially highlighting the download of miner applications from the domain.
Additional payloads observed during this time largely featured variations of shell scripts, PHP content, and/or executables. Typically, shell scripts direct the device to retrieve additional content from external servers or repositories or contain potential configuration details for subsequent binaries to run on the device. For example, the “service.sh” retrieves a tar-compressed archive, a configuration JSON file as well as a file with the name “solr” from GitHub, potentially associated with the Apache Solr tool used for enterprise search. These could be used for further enumeration of the host and/or the network environment. PHP scripts observed may involve similar web shell functionality and were retrieved from both rare external IPs identified as well by external researchers [7]. Darktrace also detected the download of octet-stream data occurring mid-compromise from an Amazon Web Services (AWS) S3 bucket. Although no outside research confirmed the functionality, additional executable downloads for files such as “/initd”(IP: 178.215.224[.]246) and “/x6” (IP: 223.165.4[.]175) may relate to tool ingress, further Trojan/backdoor functionality, or cryptocurrency mining.
Reconnaissance and Cryptomining
Darktrace analysts also noticed additional elements of kill chain operations from affected devices after periods of initial exploit activity. Several devices initiated TCP connections to endpoints affiliated with cryptomining pools such as us[.]zephyr[.]herominers[.]com and xmrig[.]com. Connectivity to these domains indicates likely successful installation of mining software during earlier stages of post-compromise activity. In a small number of instances, Darktrace observed reconnaissance and lateral movement within the time range of PAN-OS exploitation. Firewalls conducted large numbers of internal connectivity attempts across several critical ports related to privileged protocols, including SMB and SSH. Darktrace detected anonymous NTLM login attempts and new usage of potential PAN-related credentials. These behaviors likely constitute attempts at lateral movement to adjacent devices to further extend network compromise impact.
Conclusion
Darktrace Threat Research and SOC analysts increasingly detect spikes in malicious activity on internet-facing devices in the days following the publication of new vulnerabilities. The latest iteration of this trend highlighted how threat actors quickly exploited Palo Alto firewall using authentication bypass and remote command execution vulnerabilities to enable device compromise. A review of the post-exploitation activity during these events reveals consistent patterns of perimeter device exploitation, but also some distinct variations.
Prior campaigns targeting perimeter devices featured activity largely confined to the exfiltration of configuration data and some initial payload retrieval. Within the current campaign, analysts identified a broader scope post-compromise activity consisting not only of payloads downloads but also extensive C2 activity, reconnaissance, and coin mining operations. While the use of command line tools like curl featured prominently in prior investigations, devices were seen retrieving a generally wider array of payloads during the latest round of activity. The use of the Sliver C2 platform further differentiates the latest round of PAN-OS compromises, with evidence of Sliver activity in about half of the investigated cases.
Several of the endpoints contacted by the infected firewall devices did not have any OSINT associated with them at the time of the attack. However, these indicators were noted as unusual for the devices according to Darktrace based on normal network traffic patterns. This reality further highlights the need for anomaly-based detection that does not rely necessarily on known indicators of compromise (IoCs) associated with CVE exploitation for detection. Darktrace’s experience in 2024 of multiple rounds of perimeter device exploitation may foreshadow future increases in these types of comprise operations.
Credit to Adam Potter (Senior Cyber Analyst), Alexandra Sentenac (Senior Cyber Analyst), Emma Foulger (Principal Cyber Analyst) and the Darktrace Threat Research team.
Cloud Security: Addressing Common CISO Challenges with Advanced Solutions
Cloud adoption is a cornerstone of modern business with its unmatched potential for scalability, cost efficiency, flexibility, and net-zero targets around sustainability. However, as organizations migrate more workloads, applications, and sensitive data to the cloud it introduces more complex challenges for CISO’s. Let’s dive into the most pressing issues keeping them up at night—and how Darktrace / CLOUD provides a solution for each.
1. Misconfigurations: The Silent Saboteur
Misconfigurations remain the leading cause of cloud-based data breaches. In 2023 alone over 80% of data breaches involved data stored in the cloud.1 Think open storage buckets or overly permissive permissions; seemingly minor errors that are easily missed and can snowball into major disasters. The fallout of breaches can be costly—both financially and reputationally.
How Darktrace / CLOUD Helps:
Darktrace / CLOUD continuously monitors your cloud asset configurations, learning your environment and using these insights to flag potential misconfigurations. New scans are triggered when changes take place, then grouped and prioritised intelligently, giving you an evolving and prioritised view of vulnerabilities, best practice and mitigation strategies.
2. Hybrid Environments: The Migration Maze
Many organizations are migrating to the cloud, but hybrid setups (where workloads span both on-premises and cloud environments) create unique challenges and visibility gaps which significantly increase complexity. More traditional and most cloud native security tooling struggles to provide adequate monitoring for these setups.
How Darktrace / CLOUD Helps:
Provides the ability to monitor runtime activity for both on-premises and cloud workloads within the same user interface. By leveraging the right AI solution across this diverse data set, we understand the behaviour of your on-premises workloads and how they interact with cloud systems, spotting unusual connectivity or data flow activity during and after the migration process.
This unified visibility enables proactive detection of anomalies, ensures seamless monitoring across hybrid environments, and provides actionable insights to mitigate risks during and after the migration process.
3. Securing Productivity Suites: The Last Mile
Cloud productivity suites like Microsoft 365 (M365) are essential for modern businesses and are often the first step for an organization on a journey to Infrastructure as a Service (IaaS) or Platform as a Service (PaaS) use cases. They also represent a prime target for attackers. Consider a scenario where an attacker gains access to an M365 account, and proceeds to; access sensitive emails, downloading files from SharePoint, and impersonating the user to send phishing emails to internal employees and external partners. Without a system to detect these behaviours, the attack may go unnoticed until significant damage is done.
How Darktrace helps:
Darktrace’s Active AI platform integrates with M365 and establishes an understanding of normal business activity, enabling the detection of abnormalities across its suite including Email, SharePoint and Teams. By identifying subtle deviations in behaviour, such as:
• Unusual file accesses
• Anomalous login attempts from unexpected locations or devices.
• Suspicious email forwarding rules created by compromised accounts.
Darktrace’s Autonomous Response can act precisely to block malicious actions, by disabling compromised accounts and containing threats before they escalate. Precise actions also ensure that critical business operations are maintained even when a response is triggered.
4. Agent Fatigue: The Visibility Struggle
To secure cloud environments, visibility is critical. If you don’t know what’s there, how can you secure it? Many solutions require agents to be deployed on every server, workload, and endpoint. But managing and deploying agents across sprawling hybrid environments can be both complex and time-consuming when following change controls, and especially as cloud resources scale dynamically.
How Darktrace / CLOUD Helps:
Darktrace reduces or eliminates the need for widespread agent deployment. Its agentless by default, integrating directly with cloud environments and providing instant visibility without the operational headache. Darktrace ensures coverage with minimal friction. By intelligently graphing the relationships between assets and logically grouping your deployed Cloud resources, you are equipped with real-time visibility to quickly understand and protect your environment.
So why Darktrace / CLOUD?
Darktrace’s Self-Learning AI redefines cloud security by adapting to your unique environment, detecting threats as they emerge, and responding in real-time. From spotting misconfigurations to protecting productivity suites and securing hybrid environments. Darktrace / CLOUD simplifies cloud security challenges without adding operational burdens.
From Chaos to Clarity
Cloud security doesn’t have to be a game of endless whack-a-mole. With Darktrace / CLOUD, CISOs can achieve the visibility, control, and proactive protection they need to navigate today’s complex cloud ecosystems confidently.