What is threat detection and response (TDR)?

Threat detection and response (TDR) refers to the tools and processes organizations use to detect, investigate and mitigate cybersecurity threats. It combines advanced detection methods, automated response capabilities and integrated security solutions to help organizations reduce risk and adapt to an evolving threat landscape.

TDR helps security teams contain incidents quickly and restore systems with minimal disruption. As threats like ransomware, phishing and zero-day exploits become more frequent and sophisticated, organizations need proactive strategies to catch malicious activity before it causes harm.

The stakes are high, and urgency is warranted: Microsoft detects roughly 600 million cyberattacks every day across its ecosystem, averaging more than 6,900 per second. For organizations, that translates into a near-constant barrage of attempted data breaches.

Digital transformation and emerging technologies like the Internet of Things (IoT) and artificial intelligence (AI) have dramatically expanded the attack surface for today’s organizations.

Generative AI, in particular, has introduced a new dimension to the threat landscape and is being exploited through methods such as prompt injection. And yet, research from the IBM Institute for Business Value says only 24% of generative AI initiatives are secured.

Endpoint security has improved, but threat actors continue to evolve. Modern adversaries target sensitive data in increasingly complex and covert ways, from creating subtle anomalies in network traffic to launching distributed denial-of-service (DDoS) campaigns.

Many threat actors are now leveraging AI to automate attacks, evade detection and exploit vulnerabilities at scale. Even insider threats—perpetrated by employees and contractors—are on the rise, with 83% of organizations experiencing at least one insider attack in 2024.

Security teams need a layered approach that integrates threat detection and response tools alongside intrusion detection systems (IDS) and threat intelligence platforms to enable continuous monitoring and rapid response. Beyond the technical lift, the business case is clear: better detection means fewer false positives, faster triage and shorter recovery times when incidents inevitably do occur.

Threat detection and response solutions defend against a broad spectrum of security incidents, including:

• Malware and ransomware: Malicious software and encryption-based attacks that disrupt operations or demand payment to restore access.

• Phishing and credential theft: Social engineering schemes that trick users into revealing login credentials or sensitive data.

• Insider threats and privilege escalation: Malicious or negligent insiders who exploit their access to compromise systems or leak confidential information.

• Advanced persistent threats (APTs): Sophisticated, targeted attacks where hackers use stealthy techniques to maintain long-term access within a network.

• Zero-day exploits: Attacks that exploit previously unknown software vulnerabilities before a patch is available.

• DDoS attacks: Attacks that flood target systems with an overwhelming amount of traffic, disrupting normal operations.

• Data breaches: Unauthorized access to sensitive information that results in loss, exposure or theft of data.

To combat cyber threats, organizations can rely on a layered TDR strategy built around four core components:

• Threat intelligence integration
• Continuous monitoring and correlation
• Threat hunting and behavior analytics
• Automated response and remediation

Threat intelligence provides detailed, actionable information about known and emerging threats. By integrating threat intelligence feeds—data streams that highlight current and potential cyberattacks—organizations can identify attacker tactics. They can also reduce false positives using frameworks like MITRE ATT&CK, a continuously updated knowledge base for combatting cybersecurity threats based on cybercriminals’ known adversarial behavior.

Continuous monitoring enables security operations center (SOC) teams to detect suspicious activity in real time. Tools like threat intelligence platforms can help aggregate and correlate data like network traffic patterns and user behavior analytics (UBA) to uncover indicators of compromise (IOC) and potential threats.

Proactive threat hunting involves searching for hidden or unknown threats using telemetry, intelligence and anomaly detection. UBA can help detect suspicious activity by identifying deviations from baseline behavior, such as accessing sensitive data at unusual times.

When a threat is detected, automated response tools isolate endpoints and disable compromised accounts. Effective incident response plans include playbooks, integrated security tools, stakeholder coordination and post-incident analysis to prevent recurrence.

While the core components explain what needs to happen, specific tools and technologies define how those actions are carried out at scale. Capabilities generally fall into two categories: detection technologies, which surface potential security threats, and response technologies, which contain and remediate them.

Detection technologies and platforms usually rely on one of four approaches:

Most modern detection platforms layer these approaches to improve visibility and reduce false positives. Detection tools bringing these approaches to life include:

• Endpoint detection and response (EDR): EDR solutions monitor endpoint devices—such as laptops and mobile devices—for signs of compromise. They provide isolation, rollback and telemetry for deeper investigation.

• Network detection and response (NDR): NDR tools examine internal and external traffic for patterns associated with lateral movement or data exfiltration.

• Extended detection and response (XDR): XDR tools integrate telemetry across endpoints, network, identity and cloud environments to enable coordinated detection and response.

• Security information and event management (SIEM): SIEM tools collect and correlate alerts across the environment to uncover potential threats and suspicious activity.

• Security orchestration, automation and response (SOAR): SOAR tools automate alert enrichment, triage and escalation to accelerate incident response and reduce manual workload.

These tools are most effective when combined with advanced technologies like AI and machine learning (ML). Together, they help security teams prioritize threats, investigate IOCs and streamline response across multiple use cases. They also enable advanced TDR capabilities such as identity threat detection and response (ITDR) and data security posture management (DSPM):

Identity threat detection and response (ITDR): ITDR focuses on protecting identity systems by continuously monitoring login activity, access behavior and privilege escalation. It helps detect attacks like credential stuffing and account takeovers, triggering real-time containment actions such as account lockdown or session termination.

Data security posture management (DSPM): DSPM helps discover, classify and assess sensitive data across cloud and hybrid environments. By feeding data context into TDR workflows, DSPM allows teams to prioritize and remediate high-risk threats more effectively.

Once a threat is confirmed, response efforts typically focus on containment, remediation and recovery. These efforts span a range of activities—from real-time actions to long-term investigation and process refinement—and include:

These methods are supported by a range of technologies, including:

• Ticketing and case management integration: These response platforms connect with IT service management (ITSM) tools to coordinate investigation and documentation.

• Forensic and audit tools: These tools capture artifacts and chain-of-custody data for post-incident analysis or legal review.

• Security orchestration platforms: These platforms ensure cross-tool coordination so that containment, communication and recovery efforts are consistent and repeatable.

Detection and response aren’t static: they evolve. In response to these rapidly shifting threats, an approach called "advanced threat detection and response" has emerged which typically incorporates AI, behavior analytics, cross-domain correlation and automated response. The goal is not only to detect threats faster, but to outmaneuver adversaries.

Advanced strategies improve accuracy and help security operations teams adapt to emerging threats, protecting sensitive data and strengthening overall posture. With core technologies in place, organizations can enhance detection and response capabilities through approaches such as:

• AI-powered detection: Artificial intelligence-powered detection leverages ML to identify subtle patterns, anomalies and outliers that may signal an advanced attack. These tools evolve with exposure to new data, enabling faster recognition of emerging threats and zero-day exploits.

• Data correlation: Data correlation unites insights from endpoint, network, identity and cloud telemetry. Correlating multiple signals helps reveal complex, multi-stage attacks and reduces false positives by providing full attack context.

• Managed detection and response: Managed detection and response (MDR) amplifies in-house capabilities using third-party experts for monitoring, investigation and response. MDR providers often layer their services on XDR platforms to offer visibility across the entire attack surface and accelerate incident remediation.

• Deception technologies: Deception technologies use decoys, honeypots and synthetic data to lure attackers and detect stealthy activity early. These systems provide high-fidelity alerts while revealing attackers' methods and intent.

• Feedback loops and iterative tuning: Feedback loops capture analyst input and incident outcomes to refine detection thresholds and improve response playbooks. Iterative tuning systematically adjusts models, thresholds or rules to reduce false positives and respond to advanced threat patterns.

An effective threat detection and response process includes automated actions to stop active threats. However, the most effective teams also account for the human side of response: reducing alert fatigue, tuning alerts over time and documenting lessons learned. These security measures—combined with continuous security posture evaluation—can help teams stay ahead of evolving threats.