How Hackers Find Gaps through Network Detection and Response (NDR) Systems

In this final article in 2023, I will touch and focus on the exploration of Network Detection and Response (NDR) solutions. I will aim to unravel the layers of defense promised by these solutions and shed light on potential vulnerabilities that elite hackers can exploit. Despite substantial investments in cutting-edge Cybersecurity products and solutions, businesses continue to grapple with targeted and sophisticated attacks that the 1% can do which cannot be protected. This necessitates a shift from automated security assessments to true manual pentesting, allowing hackers to stress-test the system in ways automation cannot emulate in order to fine tune these Secure mechanisms to work better.

I will weigh in my thoughts based on the experience I have from an Offensive Security perspective, mindset, and sophisticated techniques skilled hackers possess vs others, because you cannot protect what you cannot see.

Understanding NDR: A Brief Overview

Network Detection and Response (NDR) solutions leverage artificial intelligence (AI), machine learning (ML), and data analytics to identify Cyber threats within corporate networks. These technologies analyze both north/south and east/west traffic, creating models of normal behavior to pinpoint anomalous or suspicious patterns. While NDRs boast advanced features like incident response, the question arises:

How effective are these defenses against determined hackers?

So, from an attacker's perspective, we can understand that an NDR communicates and receives data from other secure products such as firewalls and others. Needless to say, firewalls can be bypassed. That is because if you find the right tamper for a given firewall you can then send packets through without being detected. So this is just a quick tip of how an attacker can understand the mechanisms in which an NDR works, and find a way to bypass it, especially when it comes to network traffic monitoring, from a hacker's perspective.

Everyone is confident about their infrastructure being non-penetrable until they get penetrated by l33t hackers, and wonder what went wrong, at that point it is too late.

The Need for an NDR Solution

Most Cyberattacks occur over the network, which is both good and bad for defenders. On the one hand, attacks over the network can be detected and mitigated by network-level defenses. On the other, the complexity and scale of the average organization’s network and the growing sophistication of cyber threat actors can make it difficult to pick out attacks from legitimate traffic.

Deep network visibility and advanced threat prevention and detection capabilities are essential to protect the enterprise against Cyber threats. Traditional, signature-based detection methods are often ineffective against modern threats, leaving the organization with a false sense of security. NDR security solutions provide an additional layer of network-level security and threat prevention capabilities that organizations require, but it does not protect you 100%.

Let us now dig a bit deeper into what an NDR provides, and how each feature can be bypassed:

How does NDR Work?

NDR solutions should be able to monitor both north-south and east-west traffic flows with strategically placed sensors. This provides deep network visibility which supports an NDR solution’s other features, including:

?A) Cyber Incident Detection: Peering into the Blind Spots

NDR solutions pride themselves on transcending traditional signature-based detection by employing advanced technologies such as artificial intelligence (AI), machine learning (ML), and data analytics. While this approach enhances their ability to identify patterns and anomalies in network traffic, it is essential to recognize the potential blind spots that skilled attackers can exploit. Let's dissect how cyber incident detection, touted as a stronghold of NDRs, can be bypassed from a technical perspective.

How can this be bypassed?

NDRs are only as effective as the data they analyze. Zero-day attacks and stealthy maneuvers that mimic legitimate traffic remain elusive, evading detection. The 5% of undetected threats pose a significant risk, emphasizing the limitations of AI and ML. These technologies, while intelligent, can be outsmarted by sophisticated offensive tactics, leaving gaps in the defensive perimeter.

AI and ML are smart but they miss a lot. These features can also be used by attackers from an offensive side and not just defensive sides. AI and ML can also be used by attackers, so it's not good enough to market it and must also talk about the stuff AI can miss.

Here are some technical tactics leet hackers would use to bypass it:

1. Crafted Evasion Techniques:

Technical Example: Attackers can manipulate the characteristics of their malicious activities to deliberately evade the detection algorithms employed by NDRs. Crafting attacks with intentional variations that do not trigger typical anomaly thresholds allows adversaries to slip through undetected. This could involve subtly altering communication patterns or payload structures to avoid triggering alerts.

2. Adversarial Machine Learning:

Technical Example: A more sophisticated hacker may exploit the same AI and ML algorithms employed by NDRs. By adopting adversarial machine learning techniques, attackers can subtly manipulate network traffic features to confuse the detection models. This adversarial crafting aims to deceive the AI and ML components, making it challenging for NDRs to distinguish between genuine and malicious activities.

3. Zero-Day Exploits:

Technical Example: Zero-day exploits, which target vulnerabilities unknown to security vendors, pose a significant challenge for NDRs. Since these exploits lack established signatures or patterns, traditional detection methods struggle to identify them. A well-crafted zero-day attack can penetrate NDR defenses by exploiting undiscovered vulnerabilities without triggering anomaly alerts.

?4. Covert Communication Channels:

Technical Example: Attackers may employ covert communication channels to disguise malicious traffic within seemingly legitimate network activity. Techniques like steganography or tunneling through uncommon protocols can be used to conceal the true nature of the communication. NDRs, relying on patterns and anomalies, may struggle to discern these covert channels, providing attackers with an avenue to operate undetected.

5. Behavioral Mimicry:

Technical Example: Skilled adversaries can study the normal behavior patterns captured by NDRs and design attacks that mimic these patterns. By orchestrating activities that align with the baseline behaviors learned by the AI and ML models, attackers can operate stealthily within the expected parameters, avoiding triggers that would typically raise suspicion.

Acknowledging the Limits: Beyond Anomaly Detection

It's crucial to acknowledge that while NDRs excel at identifying anomalies, the dynamic nature of Cyber threats introduces challenges. A relentless commitment to innovation by attackers, combined with the complexity of crafting detection algorithms, means that blind spots persist. Organizations must embrace a more comprehensive Cybersecurity strategy that not only leverages advanced technologies but also acknowledges the human element in the ongoing battle against sophisticated Cyber threats.

B) Investigation: Automated Responses and Human Analysis

NDR security solutions monitor network traffic and extract patterns that can point to anomalous or suspicious connections. This information is used to generate automated responses by the NDR solution and is provided to Security Operations Center (SOC) analysts to facilitate their incident investigation activities.

How can this be bypassed?

1. Evasion through Encrypted Channels:

Technical Example: Attackers can leverage encrypted communication channels to obfuscate malicious activities. By encrypting the traffic, they make it challenging for NDR solutions to inspect the content, allowing malicious payloads to traverse undetected. Well-known techniques like HTTPS-based covert channels or leveraging legitimate encrypted protocols, such as TLS, can be employed.

?2. Mimicking Legitimate Protocols:

Technical Example: Sophisticated attackers can craft traffic patterns that closely mimic legitimate protocols. By studying and replicating the communication signatures of commonly used applications, they can camouflage malicious activities within the noise of regular network traffic. This technique, known as protocol mimicry, poses a significant challenge for NDRs reliant on pattern recognition.

?3. Polymorphic Malware:

Technical Example: Attackers can deploy polymorphic malware designed to dynamically change its appearance. This constant mutation ensures that the malware avoids detection by signature-based systems. NDRs, relying on predefined patterns and signatures, may struggle to keep pace with the ever-changing characteristics of polymorphic malware, allowing it to slip through the automated investigation.

?4. Time-Triggered Attacks:

?Technical Example: A well-timed attack can exploit the limitations of NDRs that rely on periodic analysis. By executing malicious activities during periods of low scrutiny or strategically orchestrating attacks with timed triggers, attackers can circumvent the investigation process. This aligns with the concept of low-and-slow attacks that aim to avoid immediate detection.

5. Context-Aware Attacks:

Technical Example: Attackers may orchestrate context-aware attacks that adapt to the environment. By studying the behavior of NDRs and understanding their response patterns, adversaries can design attacks that exploit blind spots or vulnerabilities in the automated investigation process. This requires a nuanced understanding of the specific NDR implementation and response mechanisms.

The Human Factor: Unraveling the Complexities

While NDRs excel in automating responses to detected threats, the human factor remains crucial. Attackers can exploit the nuances of human analysis in conjunction with automated responses. For instance:

1. Social Engineering Techniques:

Technical Example: Crafty attackers can manipulate analysts through social engineering tactics, leading them to misinterpret or downplay certain alerts. By blending sophisticated technical maneuvers with persuasive social engineering, attackers can exploit the collaborative nature of human-machine analysis.

2. Deceptive False Positives:

Technical Example: Attackers may intentionally trigger false positives to divert attention. By overwhelming analysts with a barrage of seemingly malicious alerts, they can create confusion and distract from the actual attack. This strategic use of false information exploits the reliance on human judgment in the investigation process.

In essence, the combination of technical evasion techniques and understanding the intricacies of human-machine collaboration poses a formidable challenge to NDRs. As organizations strive to fortify their defenses, it becomes imperative to address these nuanced vulnerabilities and acknowledge the targeted tactics of leet hackers.

C) Intelligence Management:

Network detection and response (NDR) solutions derive their strength from consuming threat intelligence both within and outside the organization. This intelligence serves as a key ingredient in identifying potential threats within network traffic and fostering collaboration with other security solutions. However, the reliance on threat intelligence introduces vulnerabilities that adept attackers can exploit. Let's dissect how intelligence management, a pivotal aspect of NDRs, can be bypassed from a technical standpoint.

How can this be bypassed?

1. Manipulation of Threat Feeds:

Technical Example: Attackers may infiltrate the channels through which NDR solutions receive threat intelligence feeds. By injecting false information or manipulating existing threat feeds, adversaries can deceive NDRs into misidentifying benign activities as malicious or vice versa. This manipulation exploits the trust placed in external threat intelligence sources.

2. Falsifying Indicators of Compromise (IoCs):

?Technical Example: A crafty attacker can intentionally introduce false Indicators of Compromise (IoCs) into the network. By mimicking known malicious behaviors or characteristics, they can mislead NDRs by relying on threat intelligence to flag potential threats. Falsifying IoCs adds a layer of complexity to the detection process, allowing attackers to operate undetected.

3. Targeting Internal Threat Intelligence Sources:

Technical Example: Attackers may compromise internal systems responsible for generating threat intelligence. By infiltrating and manipulating the information within an organization's threat database, adversaries can effectively control the narrative fed to NDRs. This internal manipulation undermines the accuracy of threat intelligence, rendering NDRs susceptible to false positives or negatives.

?4. Dynamic Threat Tactics:

?Technical Example: Sophisticated attackers can dynamically adapt their tactics in response to observed threat intelligence patterns. By constantly evolving their strategies based on the information available to NDRs, adversaries can exploit the temporal gap between intelligence updates and real-time attacks. This dynamic approach challenges the static nature of threat intelligence, making it a potential weak link.

5. Honeypot Misdirection:

Technical Example: Attackers may set up decoy systems, known as honeypots, to misdirect and manipulate the threat intelligence collected by NDRs. By deliberately triggering alerts in these deceptive environments, adversaries can divert attention away from their actual activities. This misdirection can be particularly effective when NDRs are overly reliant on threat intelligence without comprehensive validation.

Beyond the Data: Ensuring Intelligence Integrity

As organizations embrace the power of threat intelligence to fortify their security posture, it's imperative to recognize the vulnerabilities inherent in the process. The dynamic nature of Cyber threats demands constant vigilance, not only in gathering intelligence but also in validating and securing the sources of that intelligence. The interplay between external and internal threat data underscores the need for a multi-layered defense strategy that anticipates and mitigates the potential manipulation of intelligence sources by cunning adversaries.

?D) Feed Creation:

?The creation of security feeds is a critical function of Network Detection and Response (NDR) solutions, serving as a conduit for Security Operations Center (SOC) analysts to gain insights into the prevailing security landscape. However, this process, while informative, is not immune to exploitation. Let's dig into the technical intricacies of how leet hackers can bypass the feed creation mechanism, potentially concealing their activities from SOC analysts.

How can this be bypassed?

?1. Pattern Deception Techniques:

Technical Example: Attackers may employ sophisticated techniques to deliberately mimic normal traffic patterns within the network. By orchestrating activities that closely resemble benign behaviors, they can manipulate NDRs into generating false positives or overlooking genuine threats. This pattern deception exploits the reliance on predefined security alerts, allowing attackers to operate stealthily within the noise.

2. Traffic Saturation Tactics:

Technical Example: Adversaries can flood the network with a high volume of seemingly benign traffic, overwhelming the NDR's capacity to process and analyze data effectively. This tactic aims to create a diversionary environment, causing the NDR to focus on the voluminous noise while potentially missing or delaying the identification of genuinely malicious activities.

?3. Dynamic Attack Strategies:

Technical Example: Skilled attackers can dynamically alter their attack strategies based on the insights provided by the NDR's security feeds. By understanding how their activities are being flagged, adversaries can adapt and evolve their tactics to avoid detection. This dynamic response challenges the static nature of security feeds, requiring continuous adaptation from SOC analysts.

?4. Seed Misdirection:

Technical Example: Attackers may strategically deploy false positive-generating activities, also known as "seeds," to mislead NDRs. These deceptive signals divert the attention of SOC analysts towards fabricated threats, potentially creating a blind spot for the real, more subtle malicious activities occurring concurrently. The misdirection exploits the trust placed in the accuracy of the generated security feed.

?5. Automated Response Evasion:

Technical Example: Adversaries can study the automated response patterns triggered by NDR-generated alerts. By understanding how the NDR responds to specific types of threats, attackers can devise strategies to circumvent or manipulate the automated responses. This tactic requires a nuanced understanding of the NDR's response mechanisms, allowing attackers to persist undetected.

?Navigating the Intricacies: A Balancing Act

As organizations leverage NDR solutions to enhance their security posture, it's imperative to acknowledge the potential weaknesses in the feed creation process. The delicate balance between generating informative alerts and mitigating the risk of false positives or misdirection requires constant scrutiny. SOC analysts play a pivotal role in discerning genuine threats from the noise, emphasizing the need for a human-driven approach that complements the capabilities of NDRs.

?E) Threat Prevention:

While Network Detection and Response (NDR) solutions excel in alerting security analysts and autonomously preventing Cyber attacks, the efficacy of these automated safeguards is not foolproof. Advanced attackers, armed with sophisticated tactics, can find ways to bypass these preventive measures. Let's dissect the technical nuances of how threat prevention, a pivotal function of NDRs, can be circumvented.

How can this be bypassed?

?1. Encryption Evasion Techniques:

Technical Example: Attackers can leverage encryption to obfuscate the true nature of their communication. By encrypting malicious payloads or disguising communication within legitimate encrypted protocols, adversaries can navigate through the NDR's preventive measures undetected. This evasion tactic challenges the ability of NDRs to inspect encrypted traffic for malicious intent.

?2. Traffic Fragmentation:

Technical Example: Adversaries may employ traffic fragmentation techniques to divide malicious payloads into smaller, seemingly harmless fragments. This fragmentation aims to bypass the NDR's inspection capabilities, as each fragment individually appears benign. Once past the inspection point, these fragments can be reassembled to reconstruct the malicious payload within the network, evading prevention measures.

?3. Polymorphic Malware Evolution:

Technical Example: Polymorphic malware, capable of dynamically changing its code structure, poses a significant challenge to NDRs. As the malware evolves with each iteration, it can outsmart signature-based detection and prevention mechanisms. The continuous mutation of the malware's characteristics renders preventive measures less effective, allowing it to persistently adapt to evade detection.

?4. IP Spoofing and Identity Masquerading:

Technical Example: Attackers may employ IP spoofing to disguise the true source of their malicious traffic. By falsifying the IP address, attackers can make it appear as if the traffic is originating from a trusted source. Additionally, identity masquerading techniques, such as mimicking legitimate user credentials, can be used to deceive NDRs into allowing malicious activities, bypassing the preventive measures.

?5. Time-Triggered Attacks:

Technical Example: Timing is crucial in evading preventive measures. Adversaries may synchronize their attacks with periods of low NDR scrutiny or during routine maintenance windows when security measures are temporarily relaxed. By executing attacks during these opportune moments, attackers can exploit the temporal gaps in NDR surveillance, allowing malicious traffic to pass undetected.

Strengthening the Defense: A Constant Evolution

As organizations entrust their defensive NDR solutions with the responsibility of proactively preventing Cyber attacks, it's imperative to acknowledge the evolving strategies employed by adversaries. The cat-and-mouse game between defenders and attackers necessitates a continuous evolution of security measures. While NDRs play a vital role in automated threat prevention, the human factor remains pivotal in staying one step ahead of the relentless innovation exhibited by sophisticated attackers.

Last Thoughts

Why Implementing NDR Solutions is not enough

Defensive security measures can only go so far in protecting an organization, as there is no such thing as a completely secure system. Cyber Criminals are always looking for new ways to exploit vulnerabilities and gain access to sensitive data.

Implementing Network Detection and Response (NDR) solutions is a strategic step in enhancing organization defenses. However, it is vital to understand potential weaknesses and critical considerations associated with this advanced security approach.

While NDRs leverage Artificial intelligence, Machine learning, and data analytics to identify threats, manual testing is essential due to its adaptability and creativity. Skilled hackers can employ techniques that automated tools will overlook, making it crucial for dynamic scenarios.

The Offensive Approach

Offensive Security Solutions such as Manual Penetration Testing is an essential part of a comprehensive security strategy. It can help uncover misconfigurations, design flaws, and unknown vulnerabilities that automated scans are not capable or programmed to detect in an organization's security posture that an attacker could exploit and strengthen their security measures, especially when it comes to showcasing true impact in post-exploitation scenarios.

Manual penetration testing is indispensable for addressing the limitations of automated solutions, particularly in the context of advanced attacks targeting Network Detection and Response (NDR) systems.

Each payload generated by hackers has a unique new signature unknown to any heuristic security device, only after it has affected a machine and gets caught it will be logged, making each crafted payload succeed every time. Human-like decision-making capabilities in manual testing allow hackers to emulate adversaries more effectively, considering nuanced factors that automated systems might miss.

It enables the exploration of Zero-Day exploits, uncharted territory, and the simulation of advanced persistent threats (APTs), providing a proactive approach to emerging threats.

Additionally, manual testing evaluates the human factor in security, assessing how security analysts interpret and respond to various scenarios. By emulating real-world scenarios with tailored assessments, manual penetration testing ensures organizations are well-prepared to defend against the dynamic and creative tactics of and sophisticated adversaries, complementing the role of automated security solutions like NDRs, MDRs, or XDRs.

Countless breaches happen because companies failed to understand the methods of the adversary.

Disclaimer:

The information provided by Black Hat Ethical Hacking and anyone associated with it is intended for Educational purposes only. The techniques discussed are meant to be used responsibly, with proper consent, and authorized access. The findings do not disclose any client information or information that is sensitive, its all well edited to keep only the necessary. BHEH and its members do not accept any responsibility for the misuse or illegal use of these techniques. It is essential to abide by applicable laws, regulations, and ethical guidelines when conducting any security assessments or penetration testing activities. Always seek proper authorization and obtain consent before performing any actions that may impact the security or privacy of systems and networks.