Identify and Analyze Anomalies in
Cloud and Container Environments
Anomaly Detection and Behavioral Analytics for Cloud Container Environments
Detect, track and alert on anomalies and potential threats by focusing on user and application behavior and how it changes over time
Public clouds enable enterprises to implement infrastructure-as-code, allowing for the rapid development, testing, and deployment of services at scale. In this environment, network resources are in constant flux, providing ample opportunities for attackers. Unfortunately, legacy security solutions are ill-equipped to handle these challenges and often leave organizations vulnerable. Instead, IT security teams need solutions that leverage anomaly detection to safeguard cloud data.
Securing the Cloud with Big Data
Traditional security solutions rely on signatures, or rule-based approaches, where rules are readily understandable – but the drawbacks are that these rules are manually entered and do not catch new attack profiles, meaning that they fail to protect against zero-day threats. To reduce false-positive rates, the rules are often written for very well-defined threat scenarios, limiting their effectiveness in production environments.
Lacework takes a completely different approach to anomaly detection. We collect high fidelity process, network, file, and user data to form a base model of normal infrastructure behavior. We then use sophisticated analytics and machine learning techniques to detect anomalies that may indicate threats. Our anomaly detection system is as adaptive as your environment is dynamic. In addition, because these baselines are generated automatically, we have fine-tuned our solution to reduce false positives.
Use Lacework’s Polygraph® to Bolster Security
Polygraph, our security foundation and deep temporal baseline, is built from collecting machine, process, and user interactions. It detects anomalies, generates appropriate alerts, and provides a tool for users to investigate and triage issues.
This Polygraph technology dynamically develops a behavioral model of your services and infrastructure. Our model understands natural hierarchies including processes, containers, pods, and machines. It then develops behavioral models that Polygraph monitors in search of activities that fall outside the model’s parameters. In addition, the Polygraph continually updates its models in order to:
- Pinpoint exactly how a file changes
- Investigate anomalous events and activities related to FIM signals.
- Provide cloud-wide capabilities for search, file type summaries, and detection of new files.
Get Integrated and Comprehensive Anomaly Detection
- Pinpoint exactly how a file changed: content, metadata, and whether the file was modified or simply appended
- Extended information on executables, such as files created without a package installation, command lines used at launch, currently running processes (with users and network activity), and suspect versions
- Expanded file intelligence with integrated threat feeds from ReversingLabs’ library of five billion files
- One-click investigation of anomalous events and activities related to FIM signals
- Cloud-wide capabilities for search, file type summaries, and detection of new files
Use Cloud-Scale and Speed to See More
- Automated configuration, file discovery, and operations
- Scalable architecture with no added complexity or performance penalties
- Anomaly detection included with all Lacework Cloud Security agents
Meet Your Compliance Mandates
- Protect log and configuration files against tampering
- Daily re-check of all monitored files
- Monitor critical files and directories with predefined directory maps
- Add directories to the watch list for an easily configurable platform
Detect and resolve anomalous changes in behavior across your workloads, containers, and IaaS accounts that represent a security risk or an IOC with Lacework’s comprehensive anomaly detection system for enterprise DevOps teams.
FAQs About Lacework's Anomaly Detection Solution
Lacework’s approach uses automation and unsupervised machine learning. The Lacework anomaly detection system is adaptive as your environment changes. In addition, because these baselines are generated automatically, and our system continually tunes, Lacework is able to deliver high fidelity alerts.
The Lacework Security Platform eliminates false positives and significantly reduces the number of alerts generated and the amount of time needed to investigate all alert events without sacrificing fidelity. We do this by maintaining a rich contextual understanding of each client environment, along with detecting and scoring meaningful changes to nominal behavior.
The Lacework Policy Editor can be used to build customized workload policies which trigger alerts on matching criteria.
Once deployed, the Lacework Cloud Security Platform immediately starts building a contextual understanding of each customer environment. For most environments, Lacework will create a complete contextual map and baseline understanding of each monitored environment within 24-48 hours, depending on the level of activity.