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In 1869, Charles Darwin introduced the term “Survival of the fittest” in his book, talking about how organisms that best read their environment and adapt accordingly are more likely to survive.
Back then, this involved collecting visual, auditory inputs from the environment, identifying threats (potential predators) based on that information, and then responding to the threat (hiding or defending). Threat detection was an indispensable trait that helped early organisms survive and evolve. 150 years later, the theory that applied to organic entities now applies to digital (human and non-human) identities in a software ecosystem.
Identity explosion due to remote work, cloud adoption and rapid digital transformation has created new attack avenues that remain unaddressed.
Attackers have found it easier to exploit an internal identity rather than trying to break into multiple layers of external enterprise security. This has made identities the #1 attack vector in the current cybersecurity landscape.
Organizations need to up the ante and adapt their security controls – implementing identity-based defense strategies to thrive. Companies find themselves dealing with two major types of identity attackers
ITDR is but an extension of Threat Detection and Response that is specific to digital identities. This new term comes into play especially because identities have become the primary target of cyberattacks.
This stems from the idea that it is easier to find login credentials to access a critical system rather than forcefully hacking into it. Getting access to digital identities not only reduces the effort involved but also raises lesser alerts as the malicious attackers are now considered as a known, trusted identity.
Unlike hardware entities identities cannot simply be turned off if a compromise is detected. They are more difficult to track, properly audit, and control.
Once an identity has been breached, hackers laterally move into your network without making much ‘noise’. They only use the access rights that identities already have - to gain a stronger foothold of privileged accounts, making it impossible to identify an identity as malicious. The goal of ITDR is to create an identity security posture that is impossible to crack into.
What is ITDR?
ITDR at its core is not a specific software or technology, but rather a cybersecurity strategy that lays emphasis on continuously monitoring identities, detecting and analyzing malicious incidents, and then responding to them. Identity threat detection & response aims to fend attackers who abuse credentials to breach identities and eventually the entire network through methods like passwords spraying, lateral movement, and privilege escalation.
Statistics, analyst reports, and the increasing number of identity-based breaches re-emphasize that identity is the new perimeter for security. While analysts mention ITDR as just another ‘category’ in cybersecurity, the crux of the problem it tries to solve remains the same.
There isn't a clear strategy to properly counter identity attacks. To understand the problem its core, we shall go back to the fundamentals of security.
Security = Prevention + Analysis + Detection + Response
Most organizations have solutions in place to prevent identity attacks, some of them include:
Identity and Access Management (IDAM): To provision and deprovision identities, constantly assess permissions to ensure least privilege.
Privileged Access Management (PAM): To enforce role-based access controls, integrate multifactor authentication for privileged access, define access control policies etc.
Supportive Solutions like MFA and SSO: To authenticate and verify identities and help users seamlessly logon to applications and services.
All these solutions are focused on prevention - and in some cases, a basic analysis of identities, credentials and access.
To perform threat detection, SIEM solutions come into play. They gather insights from security tools and correlate data to try and detect malicious incidents.
SIEM solutions, however, lack the intelligence required to properly identify an identity-based attack. SIEM analyzes activity according to certain fixed artifacts like application logs and endpoint activities. They are unable to properly utilize input from identity security tools and identify clear signs of a threat.
For example, SIEM has no way of seeing if a resource has multiple factors of authentication enforced, or if an identity has managed to bypass MFA by configuring MFA settings.
ITDR however, would be able to scan user accounts in IdPs and end systems like applications and SaaS platforms. This allows it to detect if there was an MFA bypass or misconfiguration.
There is a clear lag in the Detection and Response part of identity security because of the complexity of identifying identity threats, making ITDR an important inclusion for a solid cybersecurity strategy.
To have a solid identity security posture, your ITDR strategy is recommended to be built upon certain key components. These components need to work together for an effective detection and response framework.
Monitoring identities continuously helps gain real-time visibility over identities across a hybrid network with on-premises and cloud systems. Constant monitoring ensures that anomalies in systems, user accounts, and other machine accounts are identified so that response systems can act quickly to prevent damage from becoming critical.
Identity monitoring leverages behavioral analytics using machine learning (ML) and Artificial Intelligence (AI) to define a baseline of normal activity for each individual identity and then observe patterns to find anomalies. The deviation from the normal baseline is often used to define the level of risk/threat that the hijacked identity could pose.
As soon as malicious activity is identified, ITDR must ensure that alerts are sent out real-time. ITDR can also benefit from Threat Intelligence which will help define common attack patterns to anticipate oncoming attacks. Dashboards with these conclusive patterns will help SOC teams double down on the exact identity or identities that are compromised and take corrective action.
Threat detection must also focus on eliminating the generation of false positives. This may end up causing an alarming number of alerts for incidents that are not necessary a threat, for example a user who has forgotten his password and is carrying out several incorrect attempts.
While this may be inevitable, with a good amount of training data over time – detection of threats can be consistently accurate. Attributes like location of the incident, time of the occurrence, change in typing patterns etc. will help differentiate legitimate threats with false alarms.
Once a threat has been confirmed, ITDR solutions must proactively trigger response actions to contain potential damage. These actions can be pre-defined like deprovisioning an identity, revoking ongoing privileged access, segmenting affected systems etc.
The ITDR solution must have enough ‘smarts’ to automate execution of a pre-defined playbook with certain scripts according to the type of incident that has occurred. For example, if the threat is found out to have roots as excessive folder access permissions – the ITDR solution can run the pre-defined script that revokes folder access.
The three components working in tandem can help organizations gain better visibility over identities, detect true threats, automate corrective actions and ultimately fortify their identity security posture.
Implementing an ITDR strategy will strengthen the identity security posture, and eliminate loopholes that attackers leverage the most to successfully breach an organization.
With an effective ITDR organizations can mitigate a wide range of identity-based cyberattacks including phishing and vishing attacks, malware, data breaches, password spraying, brute force, etc.
Better protection of sensitive information related directly to the organization or client information, thus preventing expensive lawsuits and penalties that may come from the leakage of customer data.
Proactive detection of threats can help quickly identify and better respond to potential data breaches. This also means there is lesser downtime in the event of a security breach – enabling companies to get back on their feet in no time.
ITDR intelligence can prevent insider threats that lean on the advantage of having authorized user access by studying attack patterns and rooting out identities that have been compromised.
Attacks are moving from being carried out primarily on-premises to the cloud. ITDR seamlessly integrates with the cloud to provide comprehensive visibility for identities that include applications, users containers, AI agents, and other IT assets.
ITDR helps organizations comply with regulations that enforce strict identity management practices. ITDR helps organizations maintain compliance with standards like HIPAA, PCI DSS, and GDPR.
ITDR eliminates manual processes, such as incident response workflows and remediation actions, improving the overall efficiency of operations. SoC teams can shift their focus on higher-value tasks, like fine-tuning response workflows.
EDR – Endpoint Detection and Response solely focuses on the monitoring, analysis and detection of incidents on workstations and endpoints (laptops, servers, switches, etc.). It detects attacks like malware and ransomware.
The input it receives is only taken from endpoints (system logs, application logs, system behavior etc.) and the response is also carried at the endpoint level (malware removal, endpoint isolation etc.).
XDR – Extended Detection and Response takes a wider set of input – taking into consideration data from endpoints, cloud services, email addresses, and networks. This helps with a broader set of variables to correlate and detect threats. It can help detect attack such as zero-day exploits and system vulnerabilities.
ITDR – Identity Threat Detection and Response in contrast, monitors identity-related activities by collecting information from several sources – IdPs, PAM, SIEM, directories (AD/Azure/LDAP), and flow data. This comprehensive range of input allows ITDR to track the complete attack chain, detect lateral movement and mitigate threats like privilege escalation, phishing, and credential spraying.
While the need for ITDR is well established, there are a number of roadblocks that organizations may face when implementing an ITDR framework. Some of these are:
ITDR requires a wide range of information from various tools to detect threats. But the depth of information that the tools provide may not be sufficient to arrive at conclusive detections. Organizations must therefore have comprehensive logging capabilities which they can provide as input for ITDR.
Being a new space, there will be difficulty in integrating ITDR with other security solutions and providing the exact details of the logs along with context. Organizations must ensure that they are able to feed ITDR solutions with audit logs in the correct format.
Difficulty in assigning security personnel, traditional SecOps (SoC) teams are new to the identity space – as identities have been managed by system administrators up until now. IAM teams and infrastructure teams must work together in initiating an ITDR strategy and maintaining it. Organizations can also consider taking help of a managed service provider to work with ITDR implementation and maintenance.
Inaccuracy in threat detection – there is a good chance that at an early stage, ITDR systems may trigger alerts for a lot of normal activity tagging them as security incidents. However, not all anomalies are threats - but every threat starts with an anomaly.
Companies must make sure that they properly define thresholds and making custom rules to fine-tune ITDR to eliminate false alarms over anomalies. Over time, with the help of machine learning – ITDR solutions can make use of information history and become more accurate.
Artificial Intelligence and User Behavior Analytics would be a huge part of an ITDR strategy. AI would help with automation of manual analysis by reading through several amounts of data quicker to detect anomalies.
Behavior analytics will leverage ML (Machine Learning) to study user behavior, identify patterns and flag any type of deviation as suspicious behavior. Together, AI and UBA will work to prevent insider threats, zero-day attacks, and maintain zero-trust.
Privileged Access Management tools handle the subset of IAM which involves accounts that generally have more access permissions than a normal account. With capabilities like session monitoring, credential logs and privileged activity logs – the events that occur through a PAM solution play a vital role in feeding critical information to ITDR which will in turn detect identity threats and automatically respond to them. PAM solutions must be able to integrate with ITDR tools and must themselves have a level of threat detection as part of the solution. Most solutions in the market now offer a layer of UBA and AI analysis within PAM.
Organizations now have different tools for different security functions such as PAM, endpoint detection, network traffic analysis, and SIEM, creating security gaps and manual integration effort.
The future of security is moving toward consolidated ITDR (Identity Threat Detection and Response) platforms that deliver end-to-end coverage across the threat detection and response life cycle. These products make security simpler, close visibility gaps, and enhance overall security posture.
With perimeter defenses fading away, identity has now taken center stage. Next-generation ITDR offerings will focus first on detecting and responding to attacks against user credentials and access permissions. Identity analytics, user behavioral monitoring, and privileged access management capabilities will increase, with identity threat detection forming the core of most organizations' ITDR solutions.
These technologies will provide full visibility into attack paths, resolving all facets of adversary tactics ranging from malware, stolen credentials, and hijacked identities.
ITDR (Identity Threat Detection and Response) is a critical component of cybersecurity that assists organizations in responding to and detecting identity-based threats rapidly. Thereby mitigating threats such as loss of data, financial loss, and reputational damage. ITDR cannot be implemented in a single go - it calls for ongoing monitoring, periodic updating, and evolution with changing threats and IT infrastructure.
Effective ITDR involves employing multiple tools and keeping pace with best practices, but it's an investment that's worthwhile for robust cybersecurity that will keep you protected.
