As cyber threats evolve, organizations are left grappling with the growing complexity of protecting their digital assets. To safeguard themselves, many companies turn to either Managed Security Service Providers (MSSPs) or build their own internal cybersecurity teams. However, despite these efforts, cyber risks remain persistent – and in many cases, they are growing.

Three fundamental factors contribute to why organizations, regardless of their chosen security approach, still face substantial cyber risks:

• an over-reliance on defensive tooling;
• diminishing efficacy of detection rules;
• the underutilization of innovative proactive technologies.

Let’s delve into each of these challenges and why they are critical to address in today’s threat landscape.

The status quo

Over-reliance on defensive tooling and traditional approaches most companies – whether through an MSSP or in-house security team – focus heavily on deploying a suite of defensive security tools such as firewalls, multi-factor authentication (MFA), vulnerability management programs, endpoint protection platforms (EDRs), security information and event management platforms (SIEMs) and more. While these tools are essential, they often fall into a reactive security strategy that plays catch-up with adversaries constantly evolving their attack methods.

In particular, adversaries are well aware of the defenses organizations typically deploy. This leads to attack techniques specifically designed to evade detection by these very tools.

For example, patch management and firewalls are vital components of security but offer no visibility or control over post-exploitation tactics used by attackers once inside the network. While great at identifying weaknesses, vulnerability management tools are often limited to providing a list of vulnerabilities, rather than preventing exploitation from sophisticated attackers who can still find ways to leverage zero-day vulnerabilities. Furthermore, these tools rely on hashes and signatures of known weaknesses rather than looking for malicious or abnormal behavior.

Traditional defensive approaches are static by design, meaning they fail to provide real-time adaptability in response to the fluidity of cyberattacks. Without supplementing these tools with proactive measures, companies may never know whether their security stack is genuinely effective against an adversary.

Built-in detection rules

Endpoint Detection and Response (EDR) tools are commonly touted as one of the best ways to detect and mitigate adversarial behavior in real time. However, in a bid to reduce false positives and claim higher accuracy rates, many EDR vendors have been cutting down or minimizing their behavioral detection rules without directly saying so.

But, seeing threats more commonly pass EDRs (from BAS tools), the proof is in the data. While this makes their products appear more attractive to buyers, it also makes organizations more vulnerable to missing key threat behaviors.

In a bid to reduce false positives and claim higher accuracy rates, many EDR vendors have been cutting down or minimizing their behavioral detection rules without directly saying so.

The same trend is often seen with Managed Detection and Response (MDR) services, putting this work back on clients, stating that clients only know group (employee behavior and permissions) patterns. I call foul here. By reducing behavioral detection capabilities, EDR and MDR solutions become less proactive in identifying subtle threat patterns that could lead to a successful breach or insider threat attack.

Instead of focusing on spotting a wide range of suspicious behaviors, they narrow their focus to avoid noisy alerts. While this might reduce alert fatigue for cybersecurity teams, it also leaves significant gaps in the organization’s detection capabilities.

When adversaries know that a certain type of activity will not be flagged, it gives them the upper hand. In a world where attackers are increasingly sophisticated, reducing detection coverage in favor of fewer alerts is a significant trade-off that often leaves organizations with critical blind spots.

Proactive security technologies

One of the biggest challenges is the lack of focus and investment in truly innovative security technologies – particularly those that take a proactive approach to defense. Solutions like anomaly detection, adversarial threat validation (aka BAS), and Attack Surface Management can transform an organization’s security posture by identifying threats that traditional defensive tools would miss.

For example, anomaly detection solutions use machine learning to identify abnormal patterns that could indicate a potential compromise, even before the attack fully materializes. These technologies go beyond signature-based detection, allowing organizations to detect novel or sophisticated attacks that haven’t been seen in the wild before.

Similarly, adversarial threat validation provides a critical, real-world perspective on how effective an organization’s defenses truly are. By simulating advanced persistent threats (APTs) and other adversarial behaviors within a controlled or production environment, these solutions test how the existing security stack responds to specific attack scenarios.

Unlike static vulnerability management programs, adversarial threat validation is dynamic and continuously challenges the organization’s defenses, providing actionable insights into areas where security controls are failing or underperforming.

Adopting proactive security solutions shifts organizations from a reactive to a preventative mindset. It also provides clear visibility into the efficacy of security tools, eliminating assumptions that their defenses will hold up against real-world attacks.

Prioritizing proactivity

To stay ahead of cyber adversaries, organizations must pivot toward a balanced approach – one that integrates both defensive and offensive strategies. Defensive tools alone cannot protect against advanced, constantly evolving threats, especially when they are being compromised by reduced detection capabilities and predictable configurations.

Instead, forward-thinking companies invest in proactive security technologies such as adversarial threat validation and anomaly detection that actively test and validate their defenses, pinpointing gaps and continuously providing essential insights into potential impact and business risk.

Anomaly detection offers a significant advantage by continuously monitoring network traffic and endpoint user behavior to identify deviations from the norm. This allows organizations to detect and investigate potential threats before they escalate into full-scale incidents, even if the attack leverages novel or unknown techniques.

On the other hand, adversarial threat emulation and validation replicate real-world attack scenarios, giving security teams critical insights into how their defenses will hold up against sophisticated adversaries. Organizations can quickly identify gaps, optimize their security stack, and better prepare their teams for real-world incidents by testing their detection and response capabilities. These combined approaches create a more dynamic, resilient cybersecurity posture capable of adapting to the ever-evolving threat landscape.

Studies have shown that 20% to 30% of all cybersecurity incidents are attributed to insider threats.

Interestingly, an increasingly concerning vector of attack is the rise in insider threats – intentional or unintentional. Studies have shown that 20% to 30% of all cybersecurity incidents are attributed to insider threats. With privileged access, insiders can bypass traditional security controls, causing breaches leading to significant financial, reputational, and operational damage.

As with novel external cyber attacks, companies must turn to proactive tools designed to detect and mitigate internal risks early. Leveraging anomaly detection helps to identify suspicious actions that deviate from normal patterns, even when initiated by trusted employees. Additionally, adversarial emulation can simulate insider threat scenarios to evaluate how prepared an organization is to detect and respond to these risks, further minimizing potential damage and ensuring comprehensive protection against both external and internal adversaries.

By moving beyond the status quo of traditional defensive strategies and embracing a proactive approach, organizations can better detect, mitigate, and respond to the cyber threats of today and tomorrow. MSSPs and internal teams must recognize that no defense is infallible, and ongoing security validation is essential for staying resilient in an era of rising cyber threats. Knowing the offenses will significantly strengthen an organization’s ability to execute its defense.

Seven key takeaways

So, to conclude, here are some recommended actions tio mitigate cyber risks through anomaly detection and adversarial threat emulation/validation tools. Organizations facing increasing cyber risks – whether they outsource to MSSPs or build internal teams – must pivot towards proactive security measures to combat the evolving threat landscape. Below is a step-by-step guide on how companies can effectively evaluate and adopt anomaly detection and adversarial threat emulation/validation tools to enhance their security posture:

1. Evaluate your current security posture

• Conduct a gap analysis: Assess your existing security controls and tools, focusing on defensive measures (EDR, vulnerability management, firewalls, etc.). Identify areas that rely too heavily on traditional, reactive defenses.
• Assess incident response capabilities: Understand how your organization currently detects and responds to threats, especially insider or advanced persistent threats (APTs), by performing a hybrid tabletop and purple team exercise. Evaluate how well your MSSP or internal team manages incident detection and response timelines.

2. Research anomaly detection solutions

• Understand the benefits: Anomaly detection tools leverage AI and machine learning to identify deviations from normal behavior across your systems. This proactive approach can catch early warning signs of insider threats, malware, or other malicious activities before they cause damage.
• Evaluate features: Look for solutions that offer real-time monitoring, behavior analysis, machine learning, and integration with your existing SIEM or EDR systems.
• Choose a tool that aligns with your environment: Ensure the anomaly detection tool can operate effectively in your specific environment (on-prem, cloud, hybrid, etc.). It should be able to handle the volume and complexity of your network data without overwhelming your team with false positives.

3. Explore adversarial threat emulation/validation tools

• Understand threat emulation: Unlike traditional Breach and Attack Simulation (BAS) tools, adversarial threat emulation goes beyond simple atomic tests, simulating the full lifecycle of a sophisticated adversary. This enables you to evaluate your organization’s security controls against real-world attack scenarios.
• Customization and integration: Look for a platform that allows you to build modular threat campaigns that can evolve based on intelligence and integrate with your existing security architecture (EDR, SIEM, firewalls, etc.).
• Real-time reporting and smart tagging: Consider platforms that provide real-time insights into detection gaps and raise automated tickets (for example, ServiceNow) for unaddressed vulnerabilities or misconfigurations.

4. Pilot the solutions

• Run a pilot program: Start with a small-scale implementation, focusing on critical areas of your network where gaps in detection and response are most likely to occur.
• Test against known threats: Use your pilot to simulate both recent and advanced persistent threats (APTs). This will give you a clear picture of how well the tools identify, report, and respond to real-world attacks.
• Track effectiveness: Monitor the performance of the tools in real-time. Evaluate whether the anomaly detection solution reduces noise by improving false positive rates and if the threat emulation tool highlights previously undetected attack paths.

5. Establish metrics for continuous improvement

• Measure success with KPIs: Define key performance indicators (KPIs) that align with the goals of reducing mean time to detect (MTTD) and mean time to respond (MTTR). Also, track improvements in your incident detection rate and the effectiveness of your security controls.
• Adjust based on insights: Use insights from your pilot to refine your processes. Adapt the tools to your specific environment and threat landscape, and identify ways to automate redundant or inefficient security tasks.

6. Train your teams

• Purple teaming exercises: Adopt a collaborative approach by conducting purple teaming exercises using adversarial emulation. This helps foster a deeper understanding of attack techniques and improves team preparedness.
• Ongoing education: Ensure that your teams (both red and blue) are trained to leverage these new tools to their full potential. Regular workshops and simulated attack exercises will reinforce their ability to detect and mitigate evolving threats.

7. Review and adapt regularly

• Stay ahead of new threats: Continuously review and adapt your anomaly detection and threat emulation tools based on emerging cyber threats. As cyber adversaries evolve, your tools and strategies must evolve too.
• Commit to continuous testing: Cybersecurity is not static. Regularly validate your defenses using adversarial threat emulation to identify potential gaps introduced by new attack techniques, insider threats, or system changes.

By adopting anomaly detection and adversarial threat emulation/validation tools, teams can drastically reduce their cyber risks and exposure to emerging threats.