With rising trends and forms of attacks, most organizations today deploy a Security Incident and Event Management (SIEM) solution as a proactive measure for threat management, to get a centralized view of their organization’s security posture and for advanced reporting of security incidents. This article discuss the use cases that every organization should practice at the minimum to reap the true benefits of a SIEM solution.

For this article, I will be using Splunk’s Search Processing Logic (SPL) wherever possible in the below mentioned use cases, to illustrate how they correlate among various security events. I will feed the Splunk with logs from my local machine.

About Splunk and SPL:
Splunk correlates real-time data in a searchable index from which it can generate graphs, reports, alerts, etc. SPL is a search processing language prepared by Splunk for searching, filtering, and inserting data.

Use Case 1

Detection of Possible Brute Force Attack

With the evolution of faster and more efficient password cracking tools, brute force attacks are on a high against the services of an organization. As a best practice, every organization should configure logging practices for security events such as invalid number of login attempts, any modification to system files, etc., so that any possible attack underway will get noticed and treated before the attack succeeds. Organizations generally apply these security policies via a Group Policy Object (GPO) to all the hosts in their network.

To check for brute force pattern, I have enabled auditing on logon events in the Local Security Policy and I will be feeding my System Win:Security logs to Splunk to check for a brute force pattern against local login attempts.

Below is the correlation search (SPL) that is created in Splunk against Win:Security logs to monitor real time login attempts. In this search, brute force criteria gets matched with two failure attempts.

sourcetype="WinEventLog:Security" (EventCode=4625 AND "Audit Failure") NOT (User_Name="*$" OR Account_Name="*$") NOT Failure_Code=0x19 | stats count by Account_Name | where count > 2

Note: EventCode: 4625 is used in new versions of the Windows family like Win 7. In older versions, the event code for invalid login attempts is 675, 529.

After this, I log off my machine, and entered the password incorrectly three times in attempt to impersonate a brute force attack.

Since these activities gets logged in Win:Security, which in turn is feeding Splunk in real time, an alert will be created in Splunk, giving analysts an incident to investigate and take responsive actions, like changing the firewall policy to blacklist that IP.

Use Case 2

Detection of Insider Threat

Reportedly, more than 30 percent of attacks are from malicious insiders in any organization. Therefore, every organization must keep the same level of security policies for insiders also.

Acceptable Use Monitoring (AUP)

Acceptable Use Monitoring covers a basic questions, i.e. what resource is being accessed by whom and when. Organizations generally publish policies for users to understand how they can use the organization’s resources in the best way. Organizations should develop a baseline document to set up threshold limits, critical resources information, user roles, and policies, and use that baseline document to monitor user activity, even after business hours, with the help of the SIEM solution.

For example, the below illustration is of logging a user activity on an object. For demonstrative purposes, I have created a file named “Test_Access” on my system. Auditing on object access is enabled in my system, like below in the Local Security Policy.

Enabling auditing on security policies is not enough, and now I have to enable the auditing on the respective file, also named “Test_Access” in this case. I have enabled auditing for Group Name –”Everyone” on this file. Organizations should fingerprint all the sensitive files and corresponding privileges and user group access on them.

For demonstrative purposes, I have selected all the object properties to be audited.

After this, I accessed the “Test_Access” file, which generates an event in Security logs with Event ID 4663, giving user name, action performed, time it was accessed, etc. This useful information can be fed into the SIEM solution through security logs to detect any unauthorized or suspicious object access.

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Organizations should develop fingerprints on all the sensitive documents, files and folders, and feed all this information to respective security solutions such as data leakage prevention solutions, application logs, WAF, etc. into the SIEM solution to detect a potential insider threat. Organizations can develop the below use cases in the SIEM solution under AUP.

  • Top malicious DNS requests from user.
  • Incidents from users reported at DLP, spam filtering, web proxy, etc.
  • Transmission of sensitive data in plain text.
  • 3rd party users network resource access.
  • Resource access outside business hours.
  • Sensitive resource access failure by user.
  • Privileged user access by resource criticality, access failure, etc.

Use Case 3

Application Defense Check

Besides network, perimeter, and end point security, organizations must develop security measures to protect applications. With attacks like SQL injection, Cross site scripting (XSS), Buffer overflow, and insecure direct object references, organizations have adopted security measures like secure coding practices, use of Web Application Firewall (WAF) which can inspect traffic at layer 7 (Application layer) against a signature, pattern based rules, etc. Along with the log of applications, organizations must also feed SIEM with logs of technologies such as WAF, which can correlate among various security incidents to detect a potential web application attack. One of the very important points to check for in a sensitive application is that the application should encrypt the sensitive information like PII in the logs as well, as these logs will be fed into SIEM, and if unencrypted, sensitive information could be exposed in SIEM.

Organizations must also develop a strategy to secure the operating system (OS) platform onto which the application is hosted. OS as well as application performance logging features must also be enabled. Below are some of the use cases that can be implemented in SIEM to check Application defense.

  • Top Web application Attacks per server.
  • Malicious SQL commands issued by administrator.
  • Applications suspicious performance indicator, resource utilization vector.
  • Application Platform (OS) patch-related status.
  • Web attacks post configuration changed on applications.

Use Case 4

Suspicious Behavior of Log Source

Expected Host/Log Source Not Reporting

Log sources are the feeds for any SIEM solution. Most of the SIEM solution these days comes with an agent-manager deployment model, which means that on all the log sources, light weight SIEM agent software is installed to collect logs and pass them to a manager for analysis. An attacker, after gaining control over a compromised machine/account, tends to stop all such agent services, so that their unauthorized and illegitimate behavior goes unnoticed.

To counter such malformed actions, SIEM should be configured to raise an alert if a host stops forwarding logs after a threshold limit. For example, the below search query (SPL) in Splunk will raise an alert if a host has not forwarded the logs for more than one hour.

| metadata type=hosts| where recentTime < now() -3600 | convert cTime(recentTime) as "Last time the log source reported" | rename host as "Log Sources" | table " Log Sources" "Last time the log source reported"

As soon as an alert is received with the IP address of the machin under attack, the Incident Response Team (IRT) can start mitigating this issue.

Unexpected Events Per Second (EPS) from Log Sources

Another common pattern found among compromised log sources is that attackers tends to change the configuration files of endpoint agents installed and forward a lot of irrelevant files to the SIEM manager, causing a bandwidth choke between the endpoint agent and manager. This affects the performance of real time searches configured, storage capacity of underlying index for storing logs, etc. Organizations must develop a use case to handle this suspicious behavior of log sources. For example, below is the search (SPL) created in Splunk which can detect unusual forwarding of events from log sources in one day.

index= _internal earliest="-1d@d" latest="-0d@d" source=*license_usage.log type=Usage h != "*ip*" | eval Mb= b/1024/1024 | bucket span=1h _time| search Mb > 5 | stats sum(Mb) as MB by _time,h | sort -MB,h | dedup h | rename h as " Workload" MB as "Total events"

An alert will be configured with it to get triggered whenever the amount of EPS from a log source exceeds a threshold value for the IRT team to investigate.

Use Case 5

Malware Check

These days, organizations believe in protecting their network end to end, i.e. right from their network perimeter with devices like firewall, Network Intrusion Prevention System (NIPS), till the endpoints hosts with security features like antivirus and Host Intrusion Prevention System (HIPS), but most organizations collect reports of security incidents from these security products in a standalone mode, which brings problem like false positives, etc.

Correlation logic is the backbone of every SIEM solution, and correlation is more effective when it is built over the output from disparate log sources. For example, an organization can correlate various security events like unusual port activities in firewall, suspicious DNS requests, warnings from Web Application firewall and IDS/IPS, threats recognized from antivirus, HIPS, etc. to detect a potential threat. Organizations can make following sub-use case under this category.

  • Unusual network traffic spikes to and from sources.
  • Endpoints with maximum number of malware threats.
  • Top trends of malware observed; detected, prevented, mitigated.
  • Brute force pattern check on Bastion host.

Use Case 6

Detection of Anomalous Ports, Services and Unpatched Hosts/Network Devices

Hosts or network devices usually get exploited because they often left unhardened, unpatched. Organizations first must develop a baseline hardening guideline that includes rules for all required ports and services rules as per business needs, in addition to best practices like “default deny-all”.

For example, to check for the services being started, systems logs from event-viewer must be fed into the SIEM solution, and a corresponding correlation search must be created against the source name of “Service Control Manager” to detect what anomalous services got started or stopped.

Organizations can also check out for vulnerable ports. Services can be exposed by deploying a vulnerability manager and running a regular scan on the network. The report can be fed into the SIEM solution to get a more comprehensive report encompassing risk rate of the machines in the network. Some use cases that an organization can build from reports are:

  • Top vulnerabilities detected in network.
  • Most vulnerable hosts in the network with highest vulnerabilities.

Another important aspect that an organization should constantly monitor as part of the SIEM process is that all clients or endpoints are properly patched with software updates and feed the client patch status information into the SIEM solution. There are various ways an organization can plan out for this check.

  • Organizations can plan out to check the patch–related status by deploying a Vulnerability Manager and running a regular scan to check out for unpatched endpoints.
  • Organizations can deploy a “centralized update manager” like WSUS and feed the results of the updated status of endpoints into the SIEM solution or can feed the logs of the manager endpoint deployed on endpoints directly into SIEM to detect all unpatched endpoints in the network.

Conclusion

Above use-cases are not a comprehensive SIEM security check list, but in order to have success with SIEM, the above listed use cases must be implemented at the minimum on every organization’s check list.

References

http://en.wikipedia.org/wiki/Splunk

http://technet.microsoft.com/en-us/library/cc730601.aspx