KI offenbart die größten Cyber-Bedrohungen des Jahres 2018: Teil eins - der Aufstieg der nicht-traditionellen IT
27
Jan 2019
27
Jan 2019
In the first installment of a two-part series, Darktrace’s Max Heinemeyer reviews the IoT, Cloud, and SaaS trends of last year and forecasts what he expects to see in 2019.
Once confined to just a handful of primitive PCs, today the internet has become so deeply integrated into all facets of our lives — from sensors in public trash cans to app-controlled Batmobiles — that the line between physical and virtual has begun to disappear.
Yet this rapid proliferation of nontraditional IT has rendered traditional cyber security strategies insufficient, and the result has been highly damaging. Cyber-crime cost the world more than half a trillion dollars last year, in large part because conventional security tools are rarely compatible with IoT devices, while perimeter defenses struggle to protect the borderless networks engendered by the cloud. In fact, even visualizing these new forms of IT — much less safeguarding them against sophisticated cyber-attacks — has proven to be a daunting challenge for companies and governments around the world. As a result, cloud services and IoT appliances have become key security blind spots.
By monitoring and analyzing raw traffic from all our clients’ internet-connected devices and cloud deployments, we saw a number of trends emerge in 2018. As the first installment of a two-part series, this article will review the IoT, Cloud, and SaaS trends of last year and forecast what we expect to see in 2019.
IoT attacks have increased by 100%
Figure 1: The Internet of Things is projected to undergo major expansion.
Internet of Things devices now far outnumber human beings, further contributing to the challenge of identifying all such devices on an organization’s network. On average, upwards of 15% of the devices visualized by our cyber AI were unknown to our clients, and given that a single compromise can cost companies millions in damages and reputational harm, failing to comprehensively monitor the entire digital infrastructure is to play with fire. Indeed, Darktrace has discovered threats in everything from corporate CCTV cameras to parking payment kiosks to smart lockers at an amusement park. All of these devices were connected to the corporate network, and none were previously known to the security team.
This lack of visibility into the Internet of Things has enabled cyber-attackers to manipulate and exploit it as low-hanging fruit, with our cyber AI detecting a 100% increase in IoT attacks over the last year. And as innovative businesses and smart cities continue to adopt connected devices at an alarming rate, these attacks will almost certainly multiply in 2019. To address the fundamental limitations of IoT cyber hygiene, organizations must be willing to rethink their security tactics, both to gain visibility over their networks and to neutralize IoT attacks that have already breached weak perimeter defenses.
28% rise in cloud and SaaS threats
Figure 2: Cloud services will become increasingly ubiquitous in the coming years.
The global migration to cloud and SaaS infrastructures only intensified in 2018, while no less than 83% of enterprise workloads are projected to be run in the cloud by 2020. This development is hardly surprising: not only does the cloud cut expenses for organizations, it provides scalable and flexible services that can evolve as needed. But as these organizations take the next step in cloud innovation, they must also consider the evolution of their security stacks.
Security teams must now cope with an environment wherein they have limited visibility and control. Attackers are aware of the weaknesses inherent to most cloud security systems, and over the last year Darktrace has discovered 28% more threats within Cloud and SaaS than observed in 2017. In fact, the Gartner Risk Management Council identified cloud computing as the most significant emerging cyber-risk of 2018, since even CASBs and native security controls fail to identify the entire spectrum of cyber-threat.
The future of nontraditional IT attacks
Although the perpetual evolution of the cyber-threat landscape prevents anyone from forecasting tomorrow’s attacks with total confidence, we can use these insights to predict some major trends this year and beyond. One overarching trend is the increasing automation of attacks on IoT devices and in the cloud, while there is every reason to suspect that more automated, even artificial intelligence-powered attacks are on the horizon.
For the same reasons that cloud environments are a challenge to protect, they can also be difficult to infiltrate, since they expose attack surfaces that are expansive and constantly shifting. Malware equipped with AI elements, meanwhile, could continuously scan a company’s cloud deployment until it spots a vulnerability, and then use its own ‘judgment’ to exploit that vulnerability before it disappears — without having to ‘phone home’ to the criminals behind the attack for instructions. And when targeting an IoT device, this kind of AI malware could leverage contextualization to blend in to its surroundings, sitting passively while learning to emulate the device’s normal behavior.
The blind spots introduced by the explosion of IoT devices and cloud services — as well as the difficulty of securing the network perimeter given the vulnerabilities that these technologies present — will undoubtedly rank among the most severe security challenges of 2019. And as AI-powered attacks become a fact of life, securing such nontraditional IT will require thinking beyond traditional cyber defenses.
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Darktrace Cyber-Analysten sind erstklassige Experten für Threat Intelligence, Threat Hunting und Incident Response. Sie bieten Tausenden von Darktrace Kunden auf der ganzen Welt rund um die Uhr SOC-Support. Einblicke in das SOC-Team wird ausschließlich von diesen Experten verfasst und bietet Analysen von Cyber-Vorfällen und Bedrohungstrends, die auf praktischen Erfahrungen in diesem Bereich basieren.
AUTOR
ÜBER DEN AUTOR
Max Heinemeyer
Leiter der Produktabteilung
Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.
The State of AI in Cybersecurity: How AI will impact the cyber threat landscape in 2024
22
Apr 2024
About the AI Cybersecurity Report
We surveyed 1,800 CISOs, security leaders, administrators, and practitioners from industries around the globe. Our research was conducted to understand how the adoption of new AI-powered offensive and defensive cybersecurity technologies are being managed by organizations.
Are organizations feeling the impact of AI-powered cyber threats?
Nearly three-quarters (74%) state AI-powered threats are now a significant issue. Almost nine in ten (89%) agree that AI-powered threats will remain a major challenge into the foreseeable future, not just for the next one to two years.
However, only a slight majority (56%) thought AI-powered threats were a separate issue from traditional/non AI-powered threats. This could be the case because there are few, if any, reliable methods to determine whether an attack is AI-powered.
Identifying exactly when and where AI is being applied may not ever be possible. However, it is possible for AI to affect every stage of the attack lifecycle. As such, defenders will likely need to focus on preparing for a world where threats are unique and are coming faster than ever before.
Are security stakeholders concerned about AI’s impact on cyber threats and risks?
The results from our survey showed that security practitioners are concerned that AI will impact organizations in a variety of ways. There was equal concern associated across the board – from volume and sophistication of malware to internal risks like leakage of proprietary information from employees using generative AI tools.
What this tells us is that defenders need to prepare for a greater volume of sophisticated attacks and balance this with a focus on cyber hygiene to manage internal risks.
One example of a growing internal risks is shadow AI. It takes little effort for employees to adopt publicly-available text-based generative AI systems to increase their productivity. This opens the door to “shadow AI”, which is the use of popular AI tools without organizational approval or oversight. Resulting security risks such as inadvertent exposure of sensitive information or intellectual property are an ever-growing concern.
Are organizations taking strides to reduce risks associated with adoption of AI in their application and computing environment?
71.2% of survey participants say their organization has taken steps specifically to reduce the risk of using AI within its application and computing environment.
16.3% of survey participants claim their organization has not taken these steps.
These findings are good news. Even as enterprises compete to get as much value from AI as they can, as quickly as possible, they’re tempering their eager embrace of new tools with sensible caution.
Still, responses varied across roles. Security analysts, operators, administrators, and incident responders are less likely to have said their organizations had taken AI risk mitigation steps than respondents in other roles. In fact, 79% of executives said steps had been taken, and only 54% of respondents in hands-on roles agreed. It seems that leaders believe their organizations are taking the needed steps, but practitioners are seeing a gap.
Do security professionals feel confident in their preparedness for the next generation of threats?
A majority of respondents (six out of every ten) believe their organizations are inadequately prepared to face the next generation of AI-powered threats.
The survey findings reveal contrasting perceptions of organizational preparedness for cybersecurity threats across different regions and job roles. Security administrators, due to their hands-on experience, express the highest level of skepticism, with 72% feeling their organizations are inadequately prepared. Notably, respondents in mid-sized organizations feel the least prepared, while those in the largest companies feel the most prepared.
Regionally, participants in Asia-Pacific are most likely to believe their organizations are unprepared, while those in Latin America feel the most prepared. This aligns with the observation that Asia-Pacific has been the most impacted region by cybersecurity threats in recent years, according to the IBM X-Force Threat Intelligence Index.
The optimism among Latin American respondents could be attributed to lower threat volumes experienced in the region, but it's cautioned that this could change suddenly (1).
What are biggest barriers to defending against AI-powered threats?
The top-ranked inhibitors center on knowledge and personnel. However, issues are alluded to almost equally across the board including concerns around budget, tool integration, lack of attention to AI-powered threats, and poor cyber hygiene.
The cybersecurity industry is facing a significant shortage of skilled professionals, with a global deficit of approximately 4 million experts (2). As organizations struggle to manage their security tools and alerts, the challenge intensifies with the increasing adoption of AI by attackers. This shift has altered the demands on security teams, requiring practitioners to possess broad and deep knowledge across rapidly evolving solution stacks.
Educating end users about AI-driven defenses becomes paramount as organizations grapple with the shortage of professionals proficient in managing AI-powered security tools. Operationalizing machine learning models for effectiveness and accuracy emerges as a crucial skill set in high demand. However, our survey highlights a concerning lack of understanding among cybersecurity professionals regarding AI-driven threats and the use of AI-driven countermeasures indicating a gap in keeping pace with evolving attacker tactics.
The integration of security solutions remains a notable problem, hindering effective defense strategies. While budget constraints are not a primary inhibitor, organizations must prioritize addressing these challenges to bolster their cybersecurity posture. It's imperative for stakeholders to recognize the importance of investing in skilled professionals and integrated security solutions to mitigate emerging threats effectively.
1. IBM, X-Force Threat Intelligence Index 2024, Available at: https://www.ibm.com/downloads/cas/L0GKXDWJ
2. ISC2, Cybersecurity Workforce Study 2023, Available at: https://media.isc2.org/-/media/Project/ISC2/Main/Media/ documents/research/ISC2_Cybersecurity_Workforce_Study_2023.pdf?rev=28b46de71ce24e6ab7705f6e3da8637e
Sliver C2: How Darktrace Provided a Sliver of Hope in the Face of an Emerging C2 Framework
17
Apr 2024
Offensive Security Tools
As organizations globally seek to for ways to bolster their digital defenses and safeguard their networks against ever-changing cyber threats, security teams are increasingly adopting offensive security tools to simulate cyber-attacks and assess the security posture of their networks. These legitimate tools, however, can sometimes be exploited by real threat actors and used as genuine actor vectors.
What is Sliver C2?
Sliver C2 is a legitimate open-source command-and-control (C2) framework that was released in 2020 by the security organization Bishop Fox. Silver C2 was originally intended for security teams and penetration testers to perform security tests on their digital environments [1] [2] [5]. In recent years, however, the Sliver C2 framework has become a popular alternative to Cobalt Strike and Metasploit for many attackers and Advanced Persistence Threat (APT) groups who adopt this C2 framework for unsolicited and ill-intentioned activities.
The use of Sliver C2 has been observed in conjunction with various strains of Rust-based malware, such as KrustyLoader, to provide backdoors enabling lines of communication between attackers and their malicious C2 severs [6]. It is unsurprising, then, that it has also been leveraged to exploit zero-day vulnerabilities, including critical vulnerabilities in the Ivanti Connect Secure and Policy Secure services.
Given its open-source nature, the Sliver C2 framework is extremely easy to access and download and is designed to support multiple operating systems (OS), including MacOS, Windows, and Linux [4].
Sliver C2 generates implants (aptly referred to as ‘slivers’) that operate on a client-server architecture [1]. An implant contains malicious code used to remotely control a targeted device [5]. Once a ‘sliver’ is deployed on a compromised device, a line of communication is established between the target device and the central C2 server. These connections can then be managed over Mutual TLS (mTLS), WireGuard, HTTP(S), or DNS [1] [4]. Sliver C2 has a wide-range of features, which include dynamic code generation, compile-time obfuscation, multiplayer-mode, staged and stageless payloads, procedurally generated C2 over HTTP(S) and DNS canary blue team detection [4].
Why Do Attackers Use Sliver C2?
Amidst the multitude of reasons why malicious actors opt for Sliver C2 over its counterparts, one stands out: its relative obscurity. This lack of widespread recognition means that security teams may overlook the threat, failing to actively search for it within their networks [3] [5].
Although the presence of Sliver C2 activity could be representative of authorized and expected penetration testing behavior, it could also be indicative of a threat actor attempting to communicate with its malicious infrastructure, so it is crucial for organizations and their security teams to identify such activity at the earliest possible stage.
Darktrace’s Coverage of Sliver C2 Activity
Darktrace’s anomaly-based approach to threat detection means that it does not explicitly attempt to attribute or distinguish between specific C2 infrastructures. Despite this, Darktrace was able to connect Sliver C2 usage to phases of an ongoing attack chain related to the exploitation of zero-day vulnerabilities in Ivanti Connect Secure VPN appliances in January 2024.
Around the time that the zero-day Ivanti vulnerabilities were disclosed, Darktrace detected an internal server on one customer network deviating from its expected pattern of activity. The device was observed making regular connections to endpoints associated with Pulse Secure Cloud Licensing, indicating it was an Ivanti server. It was observed connecting to a string of anomalous hostnames, including ‘cmjk3d071amc01fu9e10ae5rt9jaatj6b.oast[.]live’ and ‘cmjft14b13vpn5vf9i90xdu6akt5k3pnx.oast[.]pro’, via HTTP using the user agent ‘curl/7.19.7 (i686-redhat-linux-gnu) libcurl/7.63.0 OpenSSL/1.0.2n zlib/1.2.7’.
Darktrace further identified that the URI requested during these connections was ‘/’ and the top-level domains (TLDs) of the endpoints in question were known Out-of-band Application Security Testing (OAST) server provider domains, namely ‘oast[.]live’ and ‘oast[.]pro’. OAST is a testing method that is used to verify the security posture of an application by testing it for vulnerabilities from outside of the network [7]. This activity triggered the DETECT model ‘Compromise / Possible Tunnelling to Bin Services’, which breaches when a device is observed sending DNS requests for, or connecting to, ‘request bin’ services. Malicious actors often abuse such services to tunnel data via DNS or HTTP requests. In this specific incident, only two connections were observed, and the total volume of data transferred was relatively low (2,302 bytes transferred externally). It is likely that the connections to OAST servers represented malicious actors testing whether target devices were vulnerable to the Ivanti exploits.
The device proceeded to make several SSL connections to the IP address 103.13.28[.]40, using the destination port 53, which is typically reserved for DNS requests. Darktrace recognized that this activity was unusual as the offending device had never previously been observed using port 53 for SSL connections.
Figure 1: Model Breach Event Log displaying the ‘Application Protocol on Uncommon Port’ DETECT model breaching in response to the unusual use of port 53.
Figure 2: Model Breach Event Log displaying details pertaining to the ‘Application Protocol on Uncommon Port’ DETECT model breach, including the 100% rarity of the port usage.
Further investigation into the suspicious IP address revealed that it had been flagged as malicious by multiple open-source intelligence (OSINT) vendors [8]. In addition, OSINT sources also identified that the JARM fingerprint of the service running on this IP and port (00000000000000000043d43d00043de2a97eabb398317329f027c66e4c1b01) was linked to the Sliver C2 framework and the mTLS protocol it is known to use [4] [5].
However, it was not just during the January 2024 exploitation of Ivanti services that Darktrace observed cases of Sliver C2 usages across its customer base. In March 2023, for example, Darktrace detected devices on multiple customer accounts making beaconing connections to malicious endpoints linked to Sliver C2 infrastructure, including 18.234.7[.]23 [10] [11] [12] [13].
Darktrace identified that the observed connections to this endpoint contained the unusual URI ‘/NIS-[REDACTED]’ which contained 125 characters, including numbers, lower and upper case letters, and special characters like “_”, “/”, and “-“, as well as various other URIs which suggested attempted data exfiltration:
This anomalous external connectivity was carried out through multiple destination ports, including the key ports 443 and 8888.
Darktrace additionally observed devices on affected customer networks performing TLS beaconing to the IP address 44.202.135[.]229 with the JA3 hash 19e29534fd49dd27d09234e639c4057e. According to OSINT sources, this JA3 hash is associated with the Golang TLS cipher suites in which the Sliver framework is developed [14].
Schlussfolgerung
Despite its relative novelty in the threat landscape and its lesser-known status compared to other C2 frameworks, Darktrace has demonstrated its ability effectively detect malicious use of Sliver C2 across numerous customer environments. This included instances where attackers exploited vulnerabilities in the Ivanti Connect Secure and Policy Secure services.
While human security teams may lack awareness of this framework, and traditional rules and signatured-based security tools might not be fully equipped and updated to detect Sliver C2 activity, Darktrace’s Self Learning AI understands its customer networks, users, and devices. As such, Darktrace is adept at identifying subtle deviations in device behavior that could indicate network compromise, including connections to new or unusual external locations, regardless of whether attackers use established or novel C2 frameworks, providing organizations with a sliver of hope in an ever-evolving threat landscape.
Credit to Natalia Sánchez Rocafort, Cyber Security Analyst, Paul Jennings, Principal Analyst Consultant
