Category: siem

Lacework Intrusion Detection System – Cloud IDS

Lacework Polygraph is a Host based IDS for cloud workloads. It provides a graphical view of who did what on which system, reducing the time for root cause analysis for anomalies in system behaviors. It can analyze workloads on AWS, Azure and GCP.

It installs a lightweight agent on each target system which aggregates information from processes running on the system into a centralized customer specific (MT) data warehouse (Snowflake on AWS)  and then analyzes the information using machine learning to generate behavioral profiles and then looks for anomalies from the baseline profile. The design allows automating analysis of common attack scenarios using ssh, privilege changes, unauthorized access to files.

The host based model gives detailed process information such as which process talked to which other and over what api. This info is not available to a network IDS. The behavior profiles reduce the false positive rates. The graphical view is useful to drill down into incidents.

OSQuery is a tool for gathering data from hosts, and this is a source of data aggregated for threat detection. https://www.rapid7.com/blog/post/2016/05/09/introduction-to-osquery-for-threat-detection-dfir/

Here’s an agent for libpcap https://github.com/lacework/pcap

It does not have an intrusion prevention (IPS) functionality. False positives on an IPS could block network/host access and negatively affect the system being protected, so it’s a harder problem.

Cloud based network isolation tools like Aviatrix might make IPS scenarios feasible by limiting the effect of an IPS.

SIEM and UEBA analytics

“A fortune 500 enterprise’s infrastructure can easily generate 10 terabytes of plain-text data per month. So how can enterprises effectively log, monitor, and correlate that data to obtain actionable insight? Enter the Security Information and Event Management (SIEM) solution”  – quote from Jeff Edwards, in a Solutions Review’s 2016 SIEM buyer’s guide covering AccelOps, Alert Logic, Alien Vault, Assuria, BlackStratus, CorreLog, EiQ Networks, EMC (RSA), Event Tracker, HP, IBM QRadar, Intel Security, Logentries, LogPoint, LogRhythm, Manage Engine, NetGuardians, NetIQj, Silver Sky, SolarWinds, Splunk, Sumo Logics, Tenable, and Trustwave .

SIEM and related acronyms –

SIEM – Security Information and Event Management, consists of SIM and SEM.

SIM – Security information management (SIM) is also referred to as log management, log storage, analysis and reporting.

SEM – Real-time monitoring, correlation of events, notifications and console views

Practical application of SIEM – Automating threat identification: SANS publication.

UBA – User Behavior Analytics

UEBA –  User and Entity Behavior Analytics. This is growing in importance, for example Exabeam focusses on behavioral analytics. The key idea in UEBA is it extends analytics to cover non-human processes and machines entities.

IDS – Intrusion Detection System. Detects and notifies about an intrusion.

IPS – Intrusion Prevention System. Such a device may shut off traffic based on an attack detection.

WAF – web application firewall.

Splunk https://www.splunk.com/pdfs/technical-briefs/splunk-for-advanced-analytics-and-threat-detection-tech-brief.pdf

https://www.splunk.com/en_us/data-insider/user-behavior-analytics-ueba.html

https://www.slideshare.net/databricks/deep-learning-in-securityan-empirical-example-in-user-and-entity-behavior-analytics-with-dr-jisheng-wang

https://github.com/topics/ueba

https://siliconangle.com/2017/07/25/detecting-malicious-insiders-behavioral-analytics-sparksummit/

https://www.analyticsvidhya.com/blog/2018/02/demystifying-security-data-science/ (good overview of evolution of solutions)

https://github.com/jivoi/awesome-ml-for-cybersecurity